Proceedings of ACEID-2014!6!7 February, 2014

Proceedings of the National Conference on

Advances in Civil Engineering and Infrastructure Development ACEID-2014

6 - 7 February, 2014

Editors G. Shravan Kumar, Associate Professor

Dr. B. Sridhar, Head of the Department

Organised by

DEPARTMENT OF CIVIL ENGINEERING

VASAVI COLLEGE OF ENGINEERING (Sponsored by Vasavi Academy of Education)

Affiliated to Osmania University and Approved by AICTE 9-5-81, Ibrahimbagh, Hyderabad 500 031, A.P., INDIA Ph: +91 – 40 - 2314 6010

PROCEEDINGS OF THE NATIONAL CONFERENCE ON ADVANCES IN CIVIL ENGINEERING AND INFRASTRUCTURE DEVELOPMENT

© Vasavi College of Engineering, Hyderabad. February 2014

No part of the material protected by this Copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical including photocopying, recording or by any information storage and retrieval system, without prior written permission from the Copyright owner.

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Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

21 January, 2014

P.Ramamohan Rao President

It

gives

me

a two-day National

immense

pleasure

Conference on

to

learn

that

ACEID-2014,

“Advances in Civil Engineering and

Infrastructure Development”, is being organised by the Department of Civil Engineering, Vasavi College of Engineering during 6-7 February, 2014. I am happy to note that good quality technical papers are selected for presentation at the conference.

The outcome of the conference will

particularly benefit the faculty and students in understanding the importance of research and development so as to foster national growth and development by making rapid strides in the field of Civil Engineering and Infrastructure Development.

I hope that the delegates from various colleges of India will have fruitful deliberations at the conference.

I wish the conference all success.

(P.Ramamohan Rao)

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Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

23 January, 2014

T.V.Subba Rao Vice-President

I am happy to know that the Civil Engineering Department of Vasavi College of Engineering is organising a two-day National Conference on Advances

in

Civil

Engineering

and

Infrastructure

Development

(ACEID-2014) during 6-7 February, 2014. The Department of Civil Engineering has had the distinction of organising two International conferences and three National conferences in the past. Indeed, the Department has always been striving to be at the forefront

of

rapid

technological

advances

in

diverse

areas

of

Civil

Engineering. The National Conference being organised now aims at bringing about an awareness of the advances made in various fields of specialization in Civil Engineering and Infrastructure Development. The outcome of the conference, I am sure, will benefit the faculty and students of the Department

I hope all the delegates from various colleges of India will have fruitful deliberations at the conference. I wish the conference all success.

(T.V.Subba Rao)

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Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

21 January, 2014

M.Krishna Murthy Secretary

I am happy to know that the Civil Engineering Department of Vasavi College of Engineering is organising a two-day National Conference on Advances

in

Civil

Engineering

and

Infrastructure

Development

(ACEID-2014) during 6-7 February, 2014. Founded in 1981 by the Vasavi Academy of Education, Vasavi College of Engineering is constantly striving to realise the dreams and aspirations of its founding fathers to foster national development by promoting technical education and research. I am sure that the deliberations of the Conference will benefit the Civil Engineering community at large and help them focus their efforts towards understanding the importance of Civil Engineering in fostering national growth and Infrastructure development. I wish the Civil Engineering Department all success in making the conference a memorable one.

The conference will provide an excellent

opportunity to the students of our Civil Engineering Department to benefit by interacting with experts and students from other colleges. I wish the conference a success.

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Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

21 January, 2014

P.V.Ratnam Treasurer

I am happy to note that ACEID-2014, a two-day National Conference on Advances in Civil Engineering and Infrastructure Development, is being organised by the Department of Civil Engineering, Vasavi College of Engineering during 6-7 February, 2014. I am glad that the Conference has received excellent response from all over India. I hope that the deliberations held at the Conference will be useful in making further progress in the Infrastructure development of the nation.

I wish the conference a great success.

 : 040-23146010 Fax : 040-23146090

Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

21 January, 2014

K.V.Rangaiah Joint Secretary

I am very happy to know that the Civil Engineering Department of our college is organizing a two-day National Conference on “Advances in Civil Engineering

and

Infrastructure

6-7 February, 2014.

Development

(ACEID-2014)”

during

The objective of the conference is to bring together

faculty members and researchers from various educational institutions from all over India onto a common platform to exchange ideas from their experiences. I am happy to know that the conference has evoked excellent response from various colleges of India. I wish Civil Engineering Department all the success in making the conference a memorable one.

This gives an opportunity to the staff and

students of Civil Engineering Department to get benefited from the proceedings of the conference. I wish the conference a success.

 : 040-23146010 Fax : 040-23146090

Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

21 January, 2014

Prof. I.V. Rao

Director & I/c Principal

I am glad to note that the Department of Civil Engineering is poised to conduct conference, a two-day National Conference on “Advances in Civil Engineering and Infrastructure Development (ACEID-2014)” during 6th-7th February,

2014.

I

am

confident

that

the

Department

of

Civil

Engineering will use this opportunity to its advantage and make it a memorable event. The enthusiasm and zeal shown by the Civil Engineering fraternity across the country is heartening and rewarding. I am told that the Technical Committee has received a good number of quality papers. I am sure that the deliberations held during the Conference will be purposeful, educative and useful to the society in general and academic fraternity in particular. I congratulate the staff and students of Department of Civil Engineering for their ceaseless efforts and wish the conference a grand success.

 : 040-23146010 Fax : 040-23146090

Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

21 January, 2014

Dr. B.Sridhar H.O.D.(Civil)

Established in the year 1981, Vasavi College of Engineering has attained fame as one of the top Engineering Colleges in Andhra Pradesh. The Department of Civil Engineering is one of the oldest departments established in the College. With dedicated and talented faculty and staff, the department earned its fame as one of the best in AP College offering Civil Engineering program at under graduate level for the past three decades. The present two day National Conference will focus on spreading of knowledge in the frontier areas of Civil Engineering and Infrastructure Development. My colleagues have put in their best efforts to make all arrangements for the Conference. I am proud that the faculty of Civil Engineering, VCE has been able to fulfill their desire to hold this two-day National Conference on “Advances in Civil Engineering and Infrastructure Development (ACEID-2014)”. The contributors have also agreed to participate and present papers. We have received papers from various parts of India. I wish the conference a great success.

(Dr. B.Sridhar)

 : 040-23146010 Fax : 040-23146090

Vasavi College of Engineering

(Sponsored by VASAVI ACADEMY OF EDUCATION) (Affiliated to Osmania University, Hyderabad and Approved by A.I.C.T.E.) 9-5-81, Ibrahimbagh, HYDERABAD – 500 031 (A.P.) www.vce.ac.in

21 January, 2014

Prof G.V.Ramana Murty Coordinator, TEQIP-II

I am very happy to know that ACEID-2014, a two-day National Conference

on

Advances

in

Civil

Engineering

and

Infrastructure

Development, is being organised by the Department of Civil Engineering, Vasavi College of Engineering during 6-7 February, 2014. The conference is being financially supported through TEQIP-II (Technical Education Quality Improvement Programme- Phase II) funds. I am happy to note that several good quality technical papers have been received for presentation at the conference. It is very important to note that rapid strides made in the field of Civil Engineering and Infrastructure Development will strengthen the country’s economy and help in creation of jobs in various sectors of growth. I sincerely believe that the deliberations of the Conference will benefit the Civil Engineering community at large and help them focus their efforts towards understanding the importance of research and development in the progress of the Nation. I appreciate the efforts of the department Civil Engineering in organising the conference. I wish the Conference all success.

(Prof. G.V.Ramana Murty)

Preface The strength, prestige and economic might of a nation depends on the quality of its infrastructure and also on the scientific temper, the intellectual and creative skills of its citizens. The importance of making rapid progress in the areas of science and technology has been emphasized time and again. Good infrastructural facilities promote economic activity and ensure well-being of people. The growth and progress of a nation is heavily dependent upon the application of science and technology to bring about creation of physical infrastructure and a knowledge-based society. Creation of physical infrastructure is no mean task and requires great will and concerted efforts on the part of the government and people to build roads, buildings, bridges, airports, industries, dams, power plants, transmission line towers, communication towers, airplanes, missiles, nuclear power reactors, thermal and hydroelectric power plants etc. The only way, a nation can do this is by having a pool of dedicated engineers with access to the latest advances in materials, construction, analysis and design of various structures. In this context, the role of a Civil engineer in the nation-building activity is paramount. India is a nation, poised to become the superpower of the present century. India has the distinction of having the third largest pool of engineers in the world and is blessed by Mother Nature with an abundance of natural resources. In addition, we also have the youngest workforce in the world. India is placed in the top-most position in the world in the area of information technology. This is the right moment for the civil engineers to contribute to the nation’s progress by making rapid strides in various forays of Civil Engineering. This can be done only when people from various walk of Civil Engineering profession viz academia, industry, research centers and construction pool their synergies to create a symbiosis of experience and innovation with advanced technology and continuous research. This will further help in creating a massive infrastructural base so that the nation can surge ahead along the path of progress and become super power even. Since its inception in 1981, Vasavi College of Engineering focused on achieving excellence. The Department of Civil Engineering, being the oldest department of the college is actively involved in furthering the frontiers of knowledge by creating a pool of young Civil Engineers for the past three decades. The present national conference on the ''Advances in Civil Engineering and Infrastructure Development'' is yet another step in its saga of continuous success, offering quality education to the students. The present conference focuses on various aspects of Civil Engineering with a special emphasis on development of infrastructural facilities which plays a very important part in realizing the dream of making India a super power. The main objective of the conference is to provide a platform for the meeting of experts from academia, industry and the field of construction to present their views on the latest advances made in the fields of Civil Engineering and infrastructure development. It is sincerely hoped that the two day national conference will provide a platform at the national level for the exchange of ideas and make the College a fertile ground for minds filled with imagination and innovation to create cost-effective and eco-friendly technologies that facilitate the creation of infrastructure for this great nation. Our humble efforts aimed at aiding national progress will prove to be fruitful only with the active support, involvement and participation of all delegates. A series of fruitful exchange of ideas during the technical sessions are bound to make the two day conference a great success and will keep us poised to conduct more such purposeful conferences in the years to come.

xix

The conference emphasizes the need for growth and development in specific areas of civil engineering, hence in keeping with the main objective which reads "Advances in Civil Engineering and Infrastructure Development", the following themes have been suggested for presentations:1. Concrete Structures and Materials, Pre Engineered Structures 2. Construction Techniques and Management 3. Transportation Systems. 4. Water Resource Management 5. Foundation Techniques 6. Environmental Facilities 7. Emerging Technologies in Infrastructure The response for paper presentations on these themes has been overwhelming and from the 65 papers received 47 papers were finally shortlisted. The quality of papers will certainly encourage purposeful discussions further providing topics for research and academic development among students. The papers came in from experts, research scholars, students and academicians from various parts of the country. I would like to thank all the members of the management committee of Vasavi Academy of Education and Vasavi College of Engineering for their support. I thank Prof. I.V. Rao, Director & I/c Principal, Vasavi College of Engineering for his timely suggestions and encouragement. I also thank Dr. G.V. Ramana Murthy, Coordinator, TEQIP-II for his motivation and cooperation, as this conference is being organized under TEQIP-II. (G. Shravan Kumar) Convener, ACEID-2014

xx

About the Institute VASAVI COLLEGE OF ENGINEERING Vision Striving for a symbiosis of technological excellence and human values. Mission To arm young brains with competitive technology, nurturing holistic development of individuals for a better tomorrow. Vasavi College of Engineering (VCE) was founded in 1981 by the Vasavi Academy of Education. It is located at Ibrahimbagh, Hyderabad, which is 9 km from Mehdipatnam, and in close vicinity to Taramati Baradari, en route to Gandipet. With the dedicated efforts for over 30 years, Vasavi College of Engineering has emerged as a reputed centre of learning in engineering education and is currently offering 6 UG and 6 PG programmes. The undergraduate programmes of Civil, Mechanical, ECE, EEE, CSE, IT are accredited by the National Board of Accreditation in the year 2013. The college is adequately supported by about 380 staff members which include Professors, Associate Professors, Assistant Professors and supporting staff. Besides, the College offers consultancy in various fields.

About the Department DEPARTMENT OF CIVIL ENGINEERING Mission of the Department To dedicate ourselves to strive and impart in-depth knowledge of Civil Engineering and prepare the students to meet the challenges of growing construction activity with confidence and competence. The department has 20 teaching faculty and 15 members as supporting staff. The areas of teaching expertise of the faculty include various specializations of Civil Engineering i.e. Structural Engineering, Water Resources Engineering, Transportation Engineering, Geo-technical Engineering, Environmental Engineering and Engineering Geology. The Department has 9 full-fledged Civil Engineering laboratories in addition to a Centre for Geomatics. The Department also has in its gamut an exclusive computing facility with the latest software in Design, Planning and Management, Remote Sensing, GIS, Land & Water Management etc. The Department undertakes consultancy work in order to promote Industry–Institute Interaction. The department conducts conferences regularly so as to keep abreast with the latest technological advancements. It has to its credit two international conferences and many national conferences that have fostered new ideas and research activities.

xxi

Vasavi Academy of Education (VAE) VAE GOVERNING BODY MEMBERS Sri. P. Ramamohan Rao Prof. T.V. Subba Rao Sri. M. Krishna Murthy Sri. K. Vasudeva Gupta Sri. P.V. Ratnam Sri. K. Ashok Kumar Sri. P. Balaji Sri. P. Gouri Prasad Smt. P. Indrani Sri. V.M. Parthasarathi Sri. K.V. Rangaiah Sri. L. Subba Gurumurthy

President Vice President Secretary Joint Secretary Treasurer Member Member Member Member Member Member Member

INSTITUTIONS SPONSORED BY VASAVI ACADEMY OF EDUCATION Name of the Institute

Year of Establishment

Vasavi College of Engineering

1981

Vasavi Public School

1983

Vasavi Polytechnic

1984

Pendekanti Law College

1990

Pendekanti Institute of Management

1991

Vasavi College of Music and Dance

1996

xxiii

Conference Committee ORGANIZING COMMITTEE Chairman Dr. I.V.Rao

Director & I/c Principal, VCE

Co-Chairman Dr. B.Sridhar

Prof. & Head, Dept. of Civil Engg, VCE

Convener Sri G.Shravan Kumar

Assoc. Prof., Dept. of Civil Engg, VCE

Members All staff of Civil Engineering Department, VCE ADVISORY & TECHNICAL COMMITTEE Dr. Michael Beer Dr. Michael Hanss Dr. Andrzej Pownuk Er. C. Muralidhar Er. C. Shekar Reddy Md. Ziauddin Dr. K. Ravande Kishore Dr. N. Murali Krishna Dr. V. Bhikshma Dr. M. Kumar Dr.K.V.L. Subramaniam Dr. R. Pradeep Kumar Dr. K. Srinivas Raju Dr. P.N.K. Rao Dr. P. Jagannadha Rao Dr. D.S.R. Murthy Dr. T.V. Praveen Dr. Ramana Reddy Dr. D. Ramaseshu Dr. N. Uma Mahesh Dr. M. Chandrasekhar Dr. V.B. Desai Dr. M.V. Seshagiri Rao Dr. M. Anji Reddy

Prof., School of Engg, University of Liverpool, UK

Dr. K. Rammohan Rao

Director, BICS, JNTU, Hyderabad

Prof., University of Stuttgart, Germany Asst. Prof., University of Texas, El Paso, USA Engineer-in-Chief, Irrigation & CAD Dept. President, CREDAI & MD, CSR Estates Ltd Chief Engineer, HMDA Prof., Dept. of Civil Engg., OU College of Engg., Hyderabad Prof. & Head, Dept. of Civil Engg., OU College of Engg., Hyderabad Prof., Dept. of Civil Engg., OU College of Engg., Hyderabad Prof., Dept. of Civil Engg., OU College of Engg., Hyderabad Prof., Dept. of Civil Engg., IIT, Hyderabad Prof., Dept. of Civil Engg., IIIT, Hyderabad Prof., Dept. of Civil Engg., BITS-Pilani, Hyderabad Prof., Dept. of Civil Engg., BITS-Pilani, Hyderabad Prof., Dept. of Civil Engg., ACE Engg. College, Hyderabad Prof., Dept. of Civil Engg., Andhra University Prof., Dept. of Civil Engg., Andhra University Prof., Dept. of Civil Engg., S V University, Tirupati Prof., Dept. of Civil Engg., NIT, Warangal Prof., Dept. of Civil Engg., NIT, Warangal Prof., Dept. of Civil Engg., NIT, Warangal Prof., Dept. of Civil Engg., JNTU, Anathapur Prof., Dept. of Civil Engg., JNTU, Hyderabad Professor of Environmental Science & Technology and Director of University Foreign Relations, JNTU, Hyderabad

xxv

Dr. K.M. Laxmana Rao Dr. P. Srinivasa Rao Dr. P. Madhusudhan Reddy Er. A. Saibaba Er. K. Veerraju Dr. K. Balaji Rao Er. S.P. Anchuri Er. Yedukondalu Dr. V. Ramachandra Col. R.V. Rao (Retd) Er. Srinivas Bonala Er. P. Rajasekhar Reddy Dr. B.L.P. Swami Dr. M.V. Rama Rao Dr. N. Mantha Sri. M. Bhasker Dr. M. Srinivas Sri. D. Swamy Gupta Dr. T. Srinivas Sri. C. Mohanlal Sri. S. Vijaya Kumar Sri. M.V.S.S. Sastri

Prof. & Head, Dept. of Civil Engg., JNTU, Hyderabad Prof., Dept. of Civil Engg., JNTU, Hyderabad Prof., Dept. of Geology, Dr. B.R.Ambedkar University, Hyderabad Chief Engineer, Indian Railways General Manager (Technical), NCC Ltd SERC, Chennai Chairman, ICI, AP-Hyd Chapter Secretary ICI, AP-Hyd Chapter Zonal Head(Tech),Ultra Tech Cement Ltd Coordinator Projects, Shapoorji Pallonji Engineer & Construction Additional CE (Projects), Pune Municipal Corporation DGM, M/s. Haridwar Infra Ltd, Hyderabad Prof., Dept. of Civil Engg., VCE, Hyderabad Prof., Dept. of Civil Engg., VCE, Hyderabad Prof., Dept. of Civil Engg., VCE, Hyderabad Assoc. Prof., Dept. of Civil Engg., VCE, Hyderabad Assoc. Prof., Dept. of Civil Engg., VCE, Hyderabad Assoc. Prof., Dept. of Civil Engg., VCE, Hyderabad Assoc. Prof., Dept. of Civil Engg., VCE, Hyderabad Assoc. Prof., Dept. of Civil Engg., VCE, Hyderabad Assoc. Prof., Dept. of Civil Engg., VCE, Hyderabad Assoc. Prof., Dept. of Civil Engg., VCE, Hyderabad

xxvi

Contents Messages

iii

Preface

xix

About the Institution and About the Department

xxi

Vasavi Academy of Education (VAE) – Governing Body Members and Sponsored Institutions Conference Committees

xxiii xxv

CONCRETE STRUCTURES AND MATERIALS, PRE-ENGINEERED STRUCTURES 1.

A Study on Mechnanical Properties of Polypropylene Fiber Reinforced Recycled Aggregate Concrete (PFRRAC) M.L.V. Prasad and P. Rathish Kumar

3

2.

Bacteria Based High Performance Concrete V. Srinivasa Reddy, M.V. Seshagiri Rao, Ch. Sasikala and N.C. Maulika

7

3.

An Experimental Investigation on Strength Properties of Artificial Light Weight Aggregate Concrete using Agricultural by Product such as Ground Nut Shell Ash V. Bhaskar Desai, K. Mallikarjunappa and A. Sathyam

15

4.

Effect of Shear Wall on Response of Multi-Storied Building Frame Nilesh Sawakare, Hemant S. Chore, Prasad A. Dode and R.M. Fuke

24

5.

Triple Blended High Strength Concrete Mixes-Studies on Compressive and Impact Strengths D. Jayasree, M. Bhasker and B.L.P. Swami

28

6.

Study on Effect of MFRC for Flexural Strength and Ductility Urooj Masood, B.L.P. Swami and A.K. Asthana

33

7.

Effect of Fly Ash Addition on Properties of Concrete with Portland Pozzolana Cement A. Chandrashekar, P.D. Maneeth, B.S. Mantesh and Nausha

41

8.

Experimental Investigation on the Performance of Concrete with GGBS as Admixture at Complete Replacement of Fine Aggregate with Steel Slag Chandana Sukesh, D. Kishore Babu, Polina V.V.S. Sivarama Krishna and C. Ravi Kumar Reddy

49

9.

Fibrous Triple Blended Concrete : Study of Elastic Properties M. Bhasker, B.L.P. Swami and B. Dean Kumar

56

10.

Influence of Super Plasticizers on High Early Strength Concretes Made with Special Cements M. Kishore Kumar, P.S. Rao and B.L.P. Swami

63

11.

Fibre Reinforced Self Compacting Concrete Admixtured with Fly Ash and Silica Fume – Behaviour and Properties S. Vijaya Kumar, M. Jaganaiah, P. Sravana and B.L.P. Swami

71

12.

Influence of Fine Aggregate to Total Aggregate Ratio on Mechanical Properties of Self Compacting Concrete K.L. Radhika

76

xxvii

13.

Analysis and Design of Steel and PSC Composite Girder for Cost Comparison D. Annapurna and L. Ajay Kumar

81

14.

Effect of a Member on Global Performance of a Structure — A Case Study on 5 Storey RC Frame Anthugari Vimala and Ramancharla Pradeep Kumar

89

15.

Damage Based Life of Heritage Structures in Seismic Environment: A Case Study on Golkonda Fort Vrushali Kamalakar and Ramancharla Pradeep Kumar

97

16.

A Review on Seismic Analysis of Vertical Geometric Irregularities of Buildings Allasab Gudihal and T.H. Sadashiva Murthy

103

17.

Seismic Behavior of Isolated R.C.C Bridges Rajesh Kodurupaka

107

18.

Use of Pervious Concrete in Increasing Ground Water Table Sowjanya and J. Jaya Vardhan

113

19.

Durability Studies on Pumice Light Weight Aggregate Concrete with and without Silica Fume N. Sivalingarao, V. Bhasker Desai and B.L.P. Swami

118

20.

Seismic Behaviour of Fixed and Flexible 2D RC Frame: A Case Study S. Bhargavi and Ramancharla Pradeep Kumar

124

21.

Effect of Back Face Shape of Retaining Wall on Earth Pressure Anant I. Dhatrak and Rushali D. Virulkar

130

22.

Behavior of Buildings Due to Tunneling under Seismic Loading Condition Anant I. Dhatrak and Sagar D. Dhengle

134

23.

Mechanical Properties of High Strength Concrete Composites with Mineral Admixtures M.V.S.S. Sastri, K. Jagannadha Rao, B.L.P. Swami and V. Bhikshma

142

24.

Performance of Existing RC Building by Pushover Analysis S.T. Jadhav, H.S.Chore and S.B. Patil

148

25.

Comparing the Empirical Time Period Formula Given in Seismic Code of Different Countries with Indian Seismic Code IS 1893:2002 Pulkit D. Velani and Ramancharla Pradeep Kumar

153

26.

Analysis and Design of Elevated Storage Reservoir A. Mukherjee and S.B. Patil

160

WATER RESOURCES MANAGEMENT 27.

Geospatial Based Watershed Planning and Impact Assessment of Mahendragarh Watershed in Bhilwar District of Rajasthan State T. Phanidra Kumar, P. Kesava Rao, V. Madhava Rao and DSR Murthy

167

28.

Reservoir Sedimentation and Controlling Measures H. Mahabaleswara and H.M. Nagabhushan

176

29.

Flood Forecasting using Mike 11 P. Raja Sekhar, P. Lakshmi Sruthi and K. Rekha Rani

183

30.

Integration of Remote Sensing & GIS Techniques for Site Suitability Analysis of Rain Water Harvesting Structures G. Shravan Kumar

188

xxviii

ENVIRONMENTAL FACILITIES 31.

General Circulation Models: Are They Useful in Projecting Future Climate? K. Shashikanth and P. Rajasekhar

197

32.

Fuzzy Based Approach of Water Quality Assessment in Hussain Sagar Lake P. Raja Sekhar, G. Shiva Kumar and M. Aditya

201

33.

Automatic Cleaning of Drainage & Production of Biogas, Electricity, Biomanure P. Ramu and U. Ramesh

206

34.

Pollution Impact Assessment in Hussain Sagar Lake P. Raja Sekhar, G. Rakesh Kumar and G. Shiva Kumar

210

35.

Analysis of Water and Assessment of its Quality for Drinking around Rajiv Gandhi International Air Port — A Case Study M. Rajasekhar and N. Venkat Rao

214

36.

Hydrogeochemistry of Ground Water in Jeedimetla Industrial Area, Greater Hyderabad, Andhra Pradesh G. Sharavan Kumar, M. Anji Reddy and P. Madhusudhana Reddy

217

FOUNDATION TECHNIQUES 37.

Performance of Geotextile Reinforced Slopes of Zoned Earth Dam Sanjay W. Thakare and Rani B. Wath

227

38.

A Study on the Geotechnical Properties of Tannery Effluent on Black Cotton Soil K.V.N. Laxma Naik, S. Bali Reddy and A.V. Narashima Rao

230

39.

Problematic Soils and Mitigative Measures - A Review M. Nagalakshmi, D.V. Sivasankara Reddy, E. Anusha and M. Chittaranjan

234

40.

Characterisation and Behavioural Analysis of Granular Pile Anchors in Terms of Heave and Strength Aswari Sultana, B.R. Phani Kumar and A. Srirama Rao

240

TRANSPORTATION SYSTEMS 41.

Lane Distribution Factors – A Case Study on NH7 &NH9 S. Ramesh Kumar and K.V. Krishna Reddy

249

42.

Use of “Trip Generation and Trip Distribution Analysis” in Solving Transportation Problems for Selected Areas of Kurnool City Sowjanya and Shaheena Parveen

253

43.

Cost Effective Method for Short-Term Aging of Bitumen M. Rajesh, P. Ramu, I. Hussen and G. Krishna Parandhama

259

44.

Analysis of Flexible Pavement using Kenlayer Software for Bypass in Kurnool City Sowjanya and P. Manjula

262

EMERGING TECHNOLOGIES IN INFRASTRUCTURE 45.

Review of Sensor Technologies in Infrastructure Construction K. Madhavi Reddy, K. Jayasree and B. Sridhar

xxix

269

CONSTRUCTION TECHNIQUES AND MANAGEMENT 46.

Cost Estimation using Fuzzy Logic M. Venu Gopal and V.S.S. Kumar

277

47.

Comparision of MCDM Methods in Project Selection S.V.S.N.D.L. Prasanna and C. Nutan Kumar

282

AUTHOR INDEX

289

xxx

Concrete Structures and Materials, Pre-Engineered Structures

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.3-6.

A Study on Mechnanical Properties of Polypropylene Fiber Reinforced Recycled Aggregate Concrete (PFRRAC) M.L.V. Prasad1 and P. Rathish Kumar2 1

Assistant Executive Engineer, Irrigation Circle, I&CAD Department, Kurnool, A.P. 2 Associate Professor, Department of Civil Engineering, NIT,Warangal, A.P. Email: [email protected]

ABSTRACT Now the time came to think in the direction of sustainability which is nothing but preservation of the environment and conservation of the rapidly diminishing natural resources and creating Green Concrete. The enormous amounts of demolished concrete produced from deteriorated and obsolete structures creates severe ecological and environmental problem. One of the ways to solve this problem is to use this Building Demolished Waste (BDW) concrete as aggregates in structural concrete. Concrete is a versatile material with numerous application, but the only problem with concrete is its brittle behaviour. This brittleness of concrete can be overcome by spreading fibers discretely in concrete. In the present work, Fiber Reinforced Recycled Aggregate Concrete (FRRAC) was developed using Polypropylene Fiber which is having good applications. The mechanical properties of fiber reinforced M40 grade concrete, for different replacements of Recycled Concrete Aggregate (RCA) in Natural Aggregate (NA) are presented. It was observed that there was 7.32 % increase in split tensile strength and about 5.29 % improvement in flexural strength with fiber addition in recycled aggregate concrete. fibers bridge crack surfaces and delay the onset of the extension of localized crack [4 & 5].

INTRODUCTION Crushing concrete to produce coarse aggregate for the production of new concrete is one common means for achieving a more environment-friendly concrete [1]. This reduces the consumption of the natural resources as well as the consumption of the landfills required for waste concrete. Recycling is the act of processing the used material for use in creating new product. The usage of natural aggregate is getting more and more intense with the advanced development in infrastructure area. In order to reduce the usage of natural aggregate, recycled aggregate can be used as the replacement materials [2]. The technology today has advanced so far that it is forcing us to think of new concept called sustainability.

AIM AND OBJECTIVES An effort has been made in this present work to describe the salient properties of coarse aggregate when natural aggregate is replaced with recycled aggregate with 50% & 100% and the Mechanical properties of concrete with replacement of Recycled Concrete Aggregate in Natural Aggregate with 0%, 50% & 100% replacements for no fiber and fibrous concrete. The Fly ash available locally was used as a partial replacement for cement in optimum dosages for improving the strength and workability properties of recycled concrete. The present work provides very useful information for the practical use of recycled aggregate in new concrete production including fibrous concretes.

Concrete is brittle under tensile loading and the mechanical properties of concrete may be improved by randomly oriented short discrete fibers which prevent or control initiation and propagation or coalescence of cracks. The character and performance of Fiber Reinforced Concrete (FRC) change depending on the properties of concrete and the fibers. The properties of fibers that are usually of interest are fiber concentration, fiber geometry, fiber orientation, and fiber distribution. Polypropylene fiber have various applications in concrete like crack control, prevent coalescence of cracks, and to change the behaviour of the material by bridging of fibers across the cracks [3]. In other words, ductility is provided with fiber reinforced cementitious composites because

Properties of Recycled Coarse Aggregate (RCA) Aggregates occupy bulk of the volume of concrete. Their size, grading, shape and surface texture have significant influence on properties of concrete. Moreover, in the present study recycled aggregate from building demolished waste was crushed and classified before use. For qualifying the utility of recycled aggregate in concrete, the important parameters like bulk density, voids ratio, specific gravity, water absorption, crushing and impact value, angularity and IAPST were determined based on IS Codal provisions[6&7]. There properties were determined for different replacement of RCA in NA. 3

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 1: Properties of Natural & Recycled Aggregate Concretes (RCA)

Properties Bulk Density % of Voids Void Ratio Specific Gravity Fineness Modulus Water absorption Flakiness Index Elongation Index Agg.Impact Value(%) Agg.Crushing Value(%) IAPST Angularity Number

100% Natural Aggregate 1.46 44.26 0.79 2.78 7.100 1.00 3.56 7.13 32.20 22.77 18.10 10.31

50% Recycled Aggregate 1.39 45.21 0.825 2.68 7.135 3.52 4.06 7.75 33.68 24.21 19.29 12.09

The properties are shown in Table 1. It can be observed that there is a decrease in bulk density, increase in water absorption, impact and crushing value. These values are with in the IS Codal provisions and they have also satisfied Rilem Specification Rilem TC 121[8]. From this it can be concluded that the recycled aggregate can be used for structural concrete.

100 %Recycled Aggregate 1.28 48.26 0.93 2.55 7.150 5.68 4.6 8.4 34.48 28.16 20.41 13.99

concrete was replaced for natural aggregate and the second, the influence of replacements of Recycled concrete Aggregate & Natural Aggregate in case of without and with Polypropylene fiber on the behavior in compression, Split tension and Flexure is being investigated. For all the studies, 150x150mm cubes for compressive strength, 150mm diameter and 300mm height cylinders for split tensile strength and 100x100x400mm prism specimens for studying the modulus of rupture were employed. The designation of the specimens is indicated in Table 2. The mix was designed as per ACI method of mix design. All the specimens were demoulded after 24 hrs and kept in water for curing for 28days.The specimens were capped using plaster of paris to ensure plane-testing surface.

EXPERIMENTAL PROGRAM An experimental program was designed to compare the strength properties of recycled aggregate concrete with out with and fiber addition. Cubes, cylinders and prisms of standard dimensions were cast and tested to determine the compressive strength, Split tensile strength flexural strength and modulus of elasticity of Fiber Reinforced Recycled Aggregate Concrete (FRRAC).

INTERPRETATION AND DISCUSSION OF TEST RESULTS

Materials

Compressive Strength of Fibrous Recycled Aggregate Concrete

Ordinary Portland cement of 53 grade (compressive strength not less than 53 N/mm2) was used in the study. The cement was selected as per IS-12269 [9]. Fine aggregate was standard river sand procured locally and was confirming to zone-II as per IS-2386. Crushed granite was used as coarse aggregate. The recycled aggregate used was obtained by crushing and processing concrete cubes, cylinders and the corresponding reinforced concrete beams. The aggregate was passed through standard sieves of 20mm and retained on 4.75mm sieve. For M40 grade the ACI mix design procedure [10] is adopted. Poly Propylene Fiber (PF) was used and the Polypropylene fiber with a cut length of 12 mm, melting point of greater than 250o and the dosage in concrete is 1000 grams per cubic meter is used.

Table 2 shows the details of mechanical properties of 40 grade concrete cast without and with RCA and without and with Polypropylene Fiber (PF) additions. The dosage of PF in concrete was found based on experimental results. Two aspects can be determined here, one is the effect of different replacement of RCA in NA on no fibrous concrete and the other one is in fibrous concrete. The 28 days compressive strength values are shown in Table 2, column (2) for M40 grade concretes. One notable observation is that the target compressive strength could be easily achieved. In control mixes that is without fiber and natural aggregate and with Polypropylene Fiber and natural aggregate the compressive strength could be easily achieved. With replacement of RCA in NA the compressive strength has decreased but was always above the target strength. This gives a conclusion that recycled aggregate concretes are not inferior to normal concretes.

Casting of Specimens The scheme of casting the specimens was done in two stages. First, the percentage of recycled aggregate in

4

A Study on Mechnanical Properties of Polypropylene Fiber Reinforced Recycled Aggregate Concrete (PFRRAC) Table 2: Strength Details of M40 Grade Concretes (Without and with Polypropylene Fiber)

Specimen Designation

Comp. Strength (MPa) M40 (2) 54.96 51.98 47.87 55.86 52.71 48.34

M40 (1) B00 B50 B100 BP00 BP50 BP100

Split Tensile Strength (MPa) M40 (3) 4.15 3.94 3.69 4.75 4.32 3.96

Flexural Strength (MPa) M40 (4) 4.32 4.09 3.78 4.61 4.32 3.98

Additions of fibers have definitively increased the compressive strength, though marginally.

The tensile strength of concrete is relatively much lower than its compressive strength because it can be developed more quickly with crack propagation. The decrease is more so in case of recycled concrete aggregate. Hence, it is important to improve the tensile strength of such a

Comp. Strength (MPa)

56

54.96

M40

55.86

51.98

52 50

47.87

48

48.34

44 42 50 100 % Replacem ent of RCA

Fig. 1: Comp. Strength vs %Repl. of RCA

3.94

M40-PF

4.32

M40 (7) 0.68 0.65 0.60 0.73 0.68 0.63

3.69 3.96

3 2

M40

4.61 4.32

Flex. Strength (MPa)

Split. Strength (MPa)

4.15 4

5

M40

4.75

5

M40 (6) 0.56 0.55 0.53 0.64 0.60 0.57

Tables 2 and Figs 5 and 6 shows the details of flexural strength for M20 & M40 grade concretes for different replacement of RCA in NA for no fiber and Polypropylene Fiber additions. There is an increase in flexural strength of fibrous concretes at all percentage replacements of RCA in NA as compared to no fiber concretes. In case of no fibers and fibrous concretes the flexural strength is dropping with increase RCA in NA. Columns 13, 14 of Table 2 show the ratio of flexural

46

0

Flexure/√fck

Effect of Polypropylene Fiber Addition on Flexural Strength of RAC

M40-PF 52.71

54

Split/√Comp.

recycled aggregate concrete. The split tensile strength of recycled aggregate concrete decreases with increase in the dosage of replacement of RCA in NA, while fibers improve the behaviour. This is as high as 14.46 % in normal concrete to 7.32 % in recycled aggregate concrete. The variation of split tensile strength with recycled aggregate replacement and with fiber additions for M40 grade concrete is plotted in Fig 2. Columns 6 and 7 shows the ratio of split to square root of compression for M40 grade for different replacement of RCA in NA without and with optimum dosage of polypropylene fiber additions.

Influence of Polypropylene Fiber on Split Tensile Strength of RAC

58

Modulus of Elasticity (MPa) M40 (5) 33350 31256 26373 33525 32248 29563

4

M40-PF

4.32 4.09

3.78

3 2 1

1

0 0

0 0

50 % Replacem ent of RCA

100

50 % Replacem ent of RCA

100

Fig. 3: Flexural Strength vs % Repl. of RCA

Fig. 2: M40 Split. Strength vs %Repl. RCA

5

3.98

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

compressive strength for different replacements of RCA in NA without and with polypropylene fiber is suggested. 6. The modulus of elasticity increased slightly with polypropylene fiber addition, while it decreased with increased recycled aggregate in natural aggregate concrete. The fibrous specimens failed only by splitting the fiber but there was no debonding of fibers noticed in any of the specimens.

strength to square root of fck. It can be noted that there is a general decrease in the value with increasing in replacement of RCA in NA. This is true for both M20 and M40 grade concretes. The values are close to 0.7*sqrt(fck) as given by standard codes for the relationship between flexural strength sqrt(fck) for normal concrete. The value of flexural strength to sqrt(fck) is more for polypropylene concrete. Effect of Polypropylene Fiber Addition on Modulus of Elasticity of RAC

REFERENCES

Table 2 column 5 shows the details of modulus of elasticity for M40 Grade concrete without and with Polypropylene fiber respectively. A comparison shows that an increase in the % of recycled concrete aggregate in Natural Aggregate, there is a decrease in the value of Modulus of Elasticity. This trend is similar in the case of Polypropylene also. A comparison of values shows an increase in the value of E with the addition of Polypropylene fiber, in case of 50%, 100% replacement of RCA also. It may be concluded that the addition of fiber in general increases the value of E of Recycled Concrete Aggregate for M40grades of concrete. These values are close to 5000*√fck in case of no fiber concrete & higher in case of polypropylene fibrous concretes.

[1]

[2]

[3]

[4]

[5]

CONCLUSIONS Based on experimental and analytical results of Polypropylene Fiber Reinforced Recycled Aggregate Concrete (PFRAC) the following conclusions can be drawn.

[6]

1. The 28 day Target compressive strength could be achieved in case of M40 grade even at 100% replacement of RCA in NA. This means recycled aggregate concrete is in no way inferior to natural aggregate concrete.

[7]

2. The split tensile strength in Recycled Aggregate Concrete could be improved with optimum addition polypropylene fibers in concrete. The increase is 7.32 % in M40 grade concrete.

[9]

[8]

[10]

3. There is a marginal increase in compressive strength of recycled aggregate concrete with fiber additions. The compressive strength however, decreased with increasing % replacement of RCA in NA. This is true for both grades of concrete and with polypropylene fibrous concrete also.

[11] [12]

4. There is an increase in flexural strength of natural and recycled aggregate concrete with polypropylene fiber additions. The increase is about 6.71 % & 5.29 % for natural and recycled aggregate concrete respectively for M40 grade concrete.

[13]

[14]

5. The relationship between compressive strength and split tensile strength and flexural and characteristic

6

Ilker Bekir Topcu et.al, “Properties of concrete produced with waste concrete aggregate”, Cement and Concrete Research 34(2004) 1307-1312. Topcu Bekir Ilker, Guncan Fuat Nedim. “Using waste concrete as aggregate”, Cement and Concrete Research 1995; 25(7):1385-90. Kiyoshi Eguchi et.al, “Application of recycled coarse aggregate by mixture to concrete construction”, Construction and Building Materials, Volume 21, Issue 7, July 2007, Pages 1542-1551. G. D. Manolis et.al,“Dynamic properties of polypropylene fiber-reinforced concrete slabs”,Cement and Concrete Composites, Vol. 19, Issue 4, 1997, Pages 341-349, P. J. İlker Bekir Topçu and Mehmet Canbaz, “Effect of different fibers on the mechanical properties of concrete containing fly ash” Construction and Building Materials, Volume 21, Issue 7, July 2007, Pages 1486-1491 P.Rathish Kumar and M.L.V.Prasad, “Utilisation of Recycled Aggregate from Demolished waste for Structural Concrete”, Journal of ING-IABSE Vol. 38, No 1, March 2008. Indian Standard Code IS: 2386, Methods of test for Aggregates for Concrete, reprinted 1997. Hansen T.C,” Recycling of demolished concrete and masonry”, RILEM Report 6, RILEM TC-37-DRC, E&FN Spon Publication. Indian Standard Code IS: 12269, Specifications for 53 Grade Ordinary Portland Cement. ACI Method of Mix Design. 211.1-91: Standard Practice for Selecting Proportions for Normal, Heavyweight and Mass Concrete (Reapproved 2002). Forster SW, “Recycled Concrete as aggregate”, Concrete International 1986; 8(10), pp 34-40. K.K.Sagoe-Crentsil et.al, “Performance of concrete made with commercially produced coarse recycled concrete aggregate”. Cement & Concrete Research 31(2001) 707712. Ch.F.Hendriks and G.M.T.Janssen, “Use of recycled materials in construction”, Materials and Structures Constructions, Vol.36, November 2003,pp 604-608. Khalaf FM, Devenny AlanS,”Recycling of demolished masonry rubble as coarse aggregate in concrete”, ASCE Journal of Materials in Civil Engineering 2004:331-40.

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.7-14.

Bacteria Based High Performance Concrete V. Srinivasa Reddy1, M.V. Seshagiri Rao2, Ch. Sasikala3 and N.C. Maulika4 4 BTech Student, Departmentof Civil Engineering, GRIET, Hyderabad 2 Department of Civil Engineering, JNTUH College of Engineering, Kukatpally, Hyderbad 3 Centre for Environment, JNTU, Hyderbad Email: [email protected] 1,4

ABSTRACT The micro-cracks and porosity of concrete structures are very common problems due to the fact that this material has a high permeability which allows water and other aggressive media to enter thus leading to deterioration. The use of traditional organic polymer based crack sealers is a common way of contributing to concrete durability. However, the most common organic polymers have some degree of toxicity and are not environmental friendly. Shortcomings of conventional surface treatments have drawn the attention to alternative techniques for the improvement of the durability of concrete. Recently research done at JNTU Hyderabad has shown that specific species of bacteria can actually be useful as a tool to repair cracks in already existing concrete structures. Calcite precipitation due to microbial chemical process by specific alkali resistant microorganisms can act as a self healing agent when induced into concrete. This mechanism is of great interest for repair in concrete structures without human intervention. A new type of alkaliphilic aerobic microorganism belonging to Bacillus species, which when added to concrete enhances the strength and durability characteristics of concrete structures significantly due to growth of filler material called calcite(CaCO3) within the pores of the cement–sand matrix leading to pore refinement and enhanced concrete microstructure. This paper reports the effects of bacterial carbonate precipitation (bio-deposition) on the strength and durability of concrete specimens of ordinary (M20), standard (M40) and High strength (M60) grades.. Keywords— Bacterial Concrete, Bacillus Subtilus, Bio-mineralization, self healing concrete, SEM. enhances corrosion resistance in concrete automatically (self healing), which could increase and ensure durability and functionality of structures enormously results in the conception of “Bacterial Concrete”[1]. An innovation based on biomimicry and biotechnology has lead to the method of sealing up of micro cracks in concrete by itself using microorganisms as a sustainable alternative to other available chemical methods of crack repair such as epoxy treatment etc [2]. Compared with the commonly used repair method which follows the procedure of detection, monitoring and repair, the self-healing method is cheaper over the structure’s life-cycle since the later maintenance would be greatly saved. Organic polymer, super absorbent polymer, expansive agents and so on are being investigated as self-healing materials for cracks. Another alternative self-healing material is microbial carbonation precipitation [3]. Some bacteria can produce or induce bio-minerals during their growth and metabolism [4]. Under suitable conditions, most bacteria are capable of inducing carbonate precipitation. The precipitated bioCaCO3 has a good potential to be used to heal concrete cracks because it is natural, environmentally friendly and compatible with the concrete matrix [5]. Compared to natural carbonation of concrete, bio-deposition is a relatively quick process. Natural carbonation occurs from

INTRODUCTION Reinforcement corrosion is one of the major durability problems, mainly when the rebar in the concrete is exposed to the chlorides either contributed from the concrete ingredients or penetrated from the surrounding chloride-bearing environment. From the perspective of durability the cracks formed should be repaired conventionally using epoxy injection, latex treatment etc or by providing extra reinforcement in the structure to ensure that the crack width stays within a certain limit. Especially with current steel prices on steep rise, providing extra steel is not economically viable. Use of synthetic agents such as epoxies for remediation of cracks in these structures introduces a different material system of doubtful long term performance and moreover they may damage the aesthetic appearance of the structures. Sometimes repair is carried out in the areas where it is not possible to shut down the plant or hazardous for human beings such as nuclear power plants where fuel storages should be leak proof, repair of waste water sewage pipes etc. Hence, in treating surfaces of structures with strategic and historic heritage importance, self healing materials could be an ideal choice. So, If in some way a reliable method could be developed that repairs cracks and

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

the dissolution of atmospheric CO2 in the pore solution and formation of CaCO3 from CSH or portlandite. In the bio-deposition treatment however, calcium ions are also provided by an externally added calcium source, while the carbonate ions result from the microbiological hydrolysis of amino acids [6].

understand the crack healing ability of Bacterial concrete and its characteristics (Strength and Durability). Effect of Bacterial Cell Concentration on Strength Effect of cell concentration of Bacillus subtilis JC3 on the strength is studied by determining the compressive strength of standard cement mortar cubes incorporated with various bacterial cell concentrations as per IS: 4031part 6 as shown in Figure 1.

MECHANISM OF BIO-BASED CONCRETE CRACK REPAIR In nature, microorganisms can induce calcite mineral precipitation through nitrogen cycle either by ammonification of amino acids/ nitrate reduction/ hydrolysis of urea [7]. Bacillus subtilis JC3 is able to precipitate calcium carbonate (CaCO3) in its microenvironment by the ammonification of amino acids into ammonium (NH4+) and carbonate (CO32-) ions. The precipitated bio-CaCO3 has a great potential ability to heal concrete cracks because it is natural, environmentally friendly and compatible with the concrete matrix [8]. Bacillus subtilis JC3 a non-pathogenic alkalophilic microorganism commonly found in soil and is known to deposit the calcite minerals when it is supplied with nutrients and right conditions to grow. The bacteria introduced into the concrete during mixing process will form spores in the highly alkaline environment of concrete. Once a crack forms, the pH level at the cracked surface will drop due to the exposure to air. The combination of the pH drop and a flow of oxygen, moisture and carbon dioxide at the crack face will activate the microorganisms and will provide the conditions favorable for growth [9]. The microorganisms will deposit calcium carbonate, and as the crack fill up, the supply of oxygen and carbon dioxide will be interrupted, causing the microorganisms to hibernate again, ensuring the continual effectiveness of the microorganisms in filling up cracks at the same location [10]. Bio-mineralization by Ammonification (Ammo acid degradation) is mediated by Bacillus subtilis JC3. Ammonification usually occurs under aerobic conditions (known as oxidative deamination) with the liberation of ammonia (NH3) or ammonium ions (NH4) when dissolved in water. The ammonia liberated will provide the conditions favorable for growth and also maintains the pH of concrete.The chemical equations involved in microbial activity are:

Strength Studies on Bacterial Concrete To study compressive strength characteristics, standard cubes (100mm x 100mm x 100mm) were cast with distilled water and the require amount of microorganisms (i.e. 105/ml cell concentration were used) with media as mixing water. The compressive strength of the bacterial concrete cubes at 28 days is compared with corresponding controlled specimens. Similarly 28 days split tensile strength and flexural strength is determined from cylinders (150 mm x150 mm x 300 mm) and prisms (100mm x 100mm x 500mm) respectively. Modulus of Elasticity is computed from the stress- strain curves of controlled and bacterial concrete. Ultrasonic Pulse Velocity Test (USPV) The test is performed as per IS code 13311 (Part 1) 1992 to find out the homogeneity of bacterial concrete, presence of cracks, voids & other imperfections and changes in concrete structure with time. In this method, velocity is co-related to strength and quality of bacterial concrete specimens as shown in Table 5. Table 1: Quality of concrete based on Ultrasonic pulse velocity

Velocity > 4.5 km/s 3.5 to 4.5 km/s 3.0 to 3.5 km/s < 3.0 km/s

Quality of concrete excellent Good medium doubtful

Rebound Hammer As per IS 13311, (Part 2): 1992, this test measures the surface hardness of concrete and is co-related to the strength and quality of concrete. Harder the surface of the material tested, greater is the rebound. Table2 shows Guidelines for qualitative interpretation of rebound hammer test results as tabulated in Table 6.

Ca2+ + B.subtilis Cell → B.subtilis Cell- Ca2+ CH3CH(NH2)COOH (Peptone) + ½O2 ---> C2H2 + H2CO3 + NH3 H2CO3 ----------> H+ + HCO3-

Table 2: Quality of concrete based on Average Rebound Hammer

NH3 + H2O --------> NH4+ + OH-

Average rebound number > 40 30 to 40 20 to 30 < 20

B.subtilis Cell- Ca2+ + CO32- → B.subtilis Cell- CaCO3 EXPERIMENTAL INVESTIGATIONS The main aim of the present experimental investigations is to obtain specific experimental data, which helps to 8

Quality of concrete Very good hard layer Good layer Fair Poor concrete

Bacteria Based High Performance Concrete

Chloride Diffusivity Studies

Table 3: RCPT and Resistivity Criteria Ratings

The chloride resistance of concrete is governed primarily by the pore structure and the concrete diffusivity. Chloride ion penetration is one of the main parameter affecting the durability of reinforced cement concrete structures. The most important concrete characteristic, apart from permeability, is diffusion. The mode of transport of chloride ion through concentration gradient is called Diffusion. The rate at which chloride ions penetrate into concrete determines the time period after which the passivity of reinforcing bars begin to break down. Chloride diffusivity in terms of charge passed of bacterial concrete using Rapid Chloride Penetration Test (RCPT) as per ASTM C 1202 is investigated. In the AASHTO T277 (ASTM C1202) test (Electrical indication of concrete’s ability to resist chloride ion penetration), a water-saturated, 50-mm thick, 100-mm diameter concrete specimen is subjected to a 60 V applied DC voltage for 6 hours. In upstream reservoir is a 3.0% NaCl solution of 2.4N concentration (Cathode) and in the downstream reservoir is a 0.3 M NaOH solution (chloride free) (Anode). The total charge passed is determined and this is used to rate the quality of the concrete according to the criteria rating mentioned in the code. The total charge passing through from one reservoir to another reservoir through centrally placed concrete specimen in 6 hrs was measured, at an interval of 30 min, indicating the degree of resistance of the specimen to chloride ion penetration as shown in Table 7. The following formula, based on the trapezoidal rule can be used to calculate the average current flowing through one cell.

Permeability Class High Moderate Low Very Low Negligible

Rapid Chloride Permeability Charge Passed (Coulombs) as per ASTM C1202 > 4,000 2,000 - 4,000 1,000 - 2,000 100 - 1,000 < 100

Acid Attack Resistance To study durability characteristics, the specimens are subjected to 3% and 5% concentrated solutions of HCL and H2SO4 using acid immersion test. The response of the specimens to the solutions was evaluated through change in appearance, weight, compressive strength, thickness and solid diagonals. For determining the resistance of concrete specimens to aggressive environment such as acid attack, the durability factors are proposed by the author, with the philosophy of ASTM C 666–1997, as the basis. In the present investigation, the author derived the “Acid Durability Factors” directly in terms of relative strengths. The relative strengths are always with respect to the 28 days value (i.e. at the start of the test). The “Acid Durability Factors” (ADF) can be designed as follows: Acid Durability Factor (ADF) = Sr (N / M )

Q = 900(I0+2I30+2I60+2I90+2I120+…+2I300+2I330+I360)

where, Sr = relative strength at corresponding N days, N = number of days at which the durability factor is needed and M = number of days at which the exposure is to be terminated.

Where, Q = current flowing through one cell (coulombs); I0 = Current reading in amperes immediately after voltage is applied, and It = Current reading in amperes at t minutes (30 min interval) after voltage is applied

The extent of deterioration at each corner of the struck face and the opposite face is measured in terms of the acid diagonals (in mm) for each of two cubes and the “Acid Attack Factor” (AAF) per face is calculated as follows:

The electric charge passed, Q in coulombs, obtained from Rapid chloride ion penetrability test was used to calculate Chloride Migration Diffusion Coefficient in steady state conditions from Berke’s empirical Equation.

AAF = (Loss in mm on eight corners of each of 2 cubes) / 4 Acid Durability Factors (ADF), Acid Attack Factors (AAF), percentage weight loss and strength loss at various days of immersion are evaluated.

DC=0.0103 x 10-12 x Q0.84 m2/s

Cost Analysis

The calculated diffusion coefficient values, in Table 8, are used to classify the concrete in terms of their permeability as per the recommendations of the Concrete Society, UK:

The cost/benefit analysis of bacterial concrete balances the increased cost of the concrete against substantial repair material costs, enhanced durability and aesthetic benefits. The benefits are apparent at strength and performance of the finished product. Only expensive component in the development of bacterial concrete is nutrients. In this project, one litre of nutrients mixed bacterial culture costs Rs 60.

High permeability concrete: >5x10-12 m2/s. Average permeability concrete: (1 to 5) x 10-12 m-/s. Low permeability concrete :< 1 x 10-12 m2/s.

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

TEST RESULTS Table 4: Effect of bacteria on Compressive Strength, Split tensile Strength, Flexural strength and Modulus of Elasticity of concrete

Age of Concrete (28 days) Compressive Strength (MPa) Split tensile Strength (MPa) Flexural strength (MPa) Secant Modulus Of Elasticity (GPa)

Ordinary grade (M20) Controlled Bacterial Concrete Concrete 29.55 33.11 3.26 3.73 4.68 6.11 16.42 27.21

Standard grade (M40) Controlled Bacterial Concrete Concrete 52.01 61.06 4.51 5.13 6.11 7.73 26.52 37.15

High strength grade (M60) Controlled Bacterial Concrete Concrete 72.61 94.21 4.63 5.63 8.64 10.44 36.31 47.11

Table 5: Ultrasonic pulse velocity test results of various grades of normal and bacterial concretes

Type of Concrete

Age of Concrete (in days) 28 60 90 28 60 90

Normal Concrete Bacterial Concrete

M20 Quality of Velocity Concrete 3.26 medium 3.36 medium 3.41 medium 4.27 Good 4.33 Good 4.39 Good

M40 Quality of Velocity Concrete 4.39 Good 4.43 Good 4.50 Good 4.73 Excellent 4.89 Excellent 4.92 Excellent

M60 Quality of Velocity Concrete 4.89 Excellent 4.92 Excellent 4.99 Excellent 5.22 Excellent 5.36 Excellent 5.41 Excellent

Table 6: Rebound hammer test results of various grades of normal and bacterial concrete specimens

Type of Concrete

Normal Concrete

Bacterial Concrete

Age of Concrete (in days)

M20 Average Rebound Number

28

M40

M60

Quality of Concrete

Average Rebound Number

Quality of Concrete

Average Rebound Number

25

Fair

34

Good Layer

46

60

28

Fair

36

Good Layer

49

90

29

Fair

38

Good Layer

51

28

33

Good Layer

44

60

35

Good Layer

47

90

37

Good Layer

49

10

Very Good Hard Layer Very Good Hard Layer Very Good Hard Layer

53 55 58

Quality of Concrete Very Good Hard Layer Very Good Hard Layer Very Good Hard Layer Very Good Hard Layer Very Good Hard Layer Very Good Hard Layer

Bacteria Based High Performance Concrete Table 7: Chloride ion Permeability of Normal and Bacterial Concretes

Charge Passed (Coulombs) Age(days)

28

M20 M40 M60

2419 2008 1022

M20 M40 M60

367 238 173

Chloride Permeability as per ASTM C1202

Charge Passed (Coulombs)

Chloride Permeability as per ASTM C1202

60 Concrete without Bacteria Moderate 2213 Moderate Moderate 1991 Low Low 997 Low Concrete with Bacteria Very Low 351 Very Low Very Low 222 Very Low Very Low 159 Very Low

Chloride Permeability as per ASTM C1202

Charge Passed (Coulombs) 90 2100 1817 943

Moderate Low Low

327 202 96

Very Low Very Low Very Low

Table 8: Chloride Diffusion Coefficients of Normal and Bacterial Concretes

Chloride Migration Diffusion Coefficient (DC) Age(days)

Chloride Permeability as per Concrete Society,UK 28

M20 M40 M60

7.16E-12 6.12E-12 3.47E-12

M20 M40 M60

1.47E-12 1.02E-12 0.78E-12

Chloride Migration Diffusion Coefficient (DC)

Chloride Permeability as per Concrete Society,UK

60 Concrete without Bacteria High 6.64E-12 High High 6.08E-12 High Medium 3.40E-12 Medium Concrete with Bacteria Medium 1.41E-12 Medium Medium 0.96E-12 Low Low 0.73E-12 Low

Chloride Migration Diffusion Coefficient (DC)

Chloride Permeability as per Concrete Society,UK 90

6.36E-12 5.63E-12 3.24E-12

High High Medium

1.33E-12 0.89E-12 0.66E-12

Medium Low Low

Table 9: Weight loss and Strength loss of concrete in Acid Immersion Test

Grade of Concrete

Weight and Compressive Strength of cube

M20 M20 M40 M40 M60 M60

% Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength

M20 M20 M40 M40 M60 M60

% Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength

Period of Immersion in 3% H2SO4 30 days 60 days 90 days Normal Concrete 0.28 1.06 4.99 2.31 6.70 9.27 0.31 1.58 3.28 1.52 5.62 9.01 0.39 2.54 2.74 0.14 4.35 8.61 Bacterial Concrete 0.28 1.34 5.29 0.36 3.41 5.28 0.25 1.44 3.96 0.19 2.72 4.51 0.12 2.27 2.58 0.03 1.51 3.61

11

Period of Immersion in 3% HCL 30 days 60 days 90 days 0.35 0.30 0.21 0.22 0.08 0.11

1.86 1.92 1.16 0.86 0.43 0.21

2.07 3.38 2.01 2.19 1.61 0.99

0.35 0.14 0.17 0.09 0.16 0.05

1.50 0.99 0.93 0.74 0.87 0.24

2.29 1.93 2.11 1.30 2.00 0.54

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

Grade of Concrete

Weight and Compressive Strength of cube

M20 M20 M40 M40 M60 M60

% Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength

M20 M20 M40 M40 M60 M60

% Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength % Weight loss % loss in Compressive Strength

Period of Immersion in 5% H2SO4 30 days 60 days 90 days Normal Concrete 0.99 2.96 6.33 2.71 7.68 11.20 1.14 5.59 8.87 0.94 7.93 16.45 0.55 3.09 3.99 0.28 4.91 8.95 Bacterial Concrete 0.47 1.69 5.48 0.46 3.59 7.09 0.91 4.66 7.73 0.68 4.92 10.2 0.51 3.05 4.54 0.13 2.18 4.02

Period of Immersion in 5% HCL 30 days 60 days 90 days 0.51 0.47 0.55 0.43 0.28 0.17

2.57 2.33 2.46 1.92 1.22 0.73

4.31 4.63 4.75 3.56 2.28 1.76

0.51 0.39 0.48 0.32 0.32 0.16

1.89 1.99 2.10 1.71 1.29 0.76

3.27 3.32 3.88 3.01 2.32 1.05

Table 10: The Acid Durability Factors and Acid Attack Factors of Controlled concrete and Bacterial concrete

Ordinary Grade (M20) Concrete 3% HCL 5% H2SO4 ADF AAF ADF AAF Controlled Concrete 0.13 33.23 0.09 32.43 0.16 0.50 64.73 0.28 61.48 0.59 0.84 96.62 0.44 88.80 0.94 Bacterial Concrete 0.06 33.28 0.06 33.18 0.13 0.31 65.35 0.25 63.63 0.41 0.47 98.07 0.41 92.91 0.66

3% H2SO4 ADF AAF

5% HCL ADF AAF

30 60 90 (=M)

32.56 61.58 91.73

32.84 64.46 95.37

0.13 0.34 0.59

30 60 90(=M)

33.18 63.75 94.72

32.87 64.69 96.68

0.09 0.31 0.50

Days of immersion N

Days of immersion N

3% H2SO4 ADF AAF

30 60 90 (=M)

31.92 62.35 92.56

0.13 0.52 0.91

30 60 90(=M)

32.66 62.99 96.01

0.07 0.28 0.549

Days of immersion N 30 60 90 (=M) 30 60 90(=M)

Standard Grade (M40) Concrete 3% HCL 5% H2SO4 ADF AAF ADF AAF Controlled Concrete 33.12 0.11 28.30 0.19 63.11 0.33 52.61 0.78 98.56 0.54 71.61 1.28 Bacterial Concrete 33.25 0.07 28.38 0.16 62.77 0.31 54.33 0.47 99.71 0.48 76.97 0.91

High Strength Grade (M60) Concrete 3% H2SO4 3% HCL 5% H2SO4 ADF AAF ADF AAF ADF AAF Controlled Concrete 33.95 0.13 33.96 0.13 32.91 0.19 63.13 0.59 65.86 0.41 62.76 0.72 91.39 0.97 99.01 0.66 91.05 1.09 Bacterial Concrete 33.99 0.09 33.98 0.09 33.29 0.16 65.00 0.31 65.84 0.34 64.56 0.34 96.39 0.53 99.46 0.50 95.92 0.59

5% HCL ADF AAF 28.45 56.05 82.66

0.19 0.59 0.97

28.48 56.17 83.13

0.16 0.50 0.84

5% HCL ADF AAF 33.27 65.52 98.24

0.16 0.53 0.81

33.28 65.50 98.95

0.13 0.38 0.66

compressive strength, split tensile strength, flexural strength and secant modulus of elasticity of controlled and bacterial concrete at 28 days were given in Table 4.

The compressive strength of cement mortar specimens are presented in Figure 1 to optimize the cell concentration of bacteria to be used in further investigations. The 12

Bacteria Based High Performance Concrete

chloride ions decreases with increase in higher grades in normal concrete but with introduction of bacteria into concrete further decreased the effective diffusion coefficient. Reduction in chloride ion permeability values indicates that bacteria induced concrete has shown between 85% to 90 % higher resistance against the chloride ion movements in bacterial concrete as compared to the chloride movements in normal concrete. The relationship between stress and strain is important in understanding the basic elastic behavior of concrete in hardened state. It is observed that Modulus of Elasticity(E) is relatively more for all grades of concrete in which bacteria is induced than the controlled concrete by about 35-65%. Bacterial Concrete mixes have shown improved stress values for the same strain levels compared to that of conventional concrete mixes.

Fig. 1: Effect of bacterial cell concentration on the strength of concrete

Percentage of loss in weight and compressive strength of bacterial concrete when compared with conventional concrete when immersed in acids HCL and H2SO4 were given in Table 9. The Acid Durability Factor and Acid Attack Factor of concrete with and without bacteria were shown in Table 10.

Durability studies carried out in this investigation through acid attack resistance for all grades of concrete with 3% and 5% concentrated solutions of H2SO4 and HCL revealed that Bacterial Concrete is more durable in terms of “Acid Durability Factors” and less attacked in terms of “Acid Attack Factors” when compared to the controlled concrete.

DISCUSSION OF RESULTS It is observed that the Compressive Strength of cement mortar showed significant increase by about 17% for cell concentration of 105 cells per ml of mixing water. So, for the further investigation bacteria with a optimum cell concentration of 105 cells per ml of mixing water is used. It is noted that pores are partially filled up by material growth with the addition of the bacteria. Reduction in pore due to such material growth will obviously increase the material strength.

CONCLUSIONS Based on the present experimental investigation, the following conclusions are drawn 1. Deposition of a layer of calcite on the surface of the specimens resulted in a decrease of capillary suction. 2. The addition of Bacillus subtilis JC3 strain improves the hydrated structure of cement in concrete for a cell concentration of 105 cells per ml of mixing water. So, bacteria with a cell concentration of 105 cells per ml of mixing water was used in the investigation.

With the addition of bacteria the Compressive Strength at 28 days showed significant increase by 16-30 % for all grades of concrete. The percentage of Compressive Strength is improved as the age of the concrete increases due to continues bacterial calcification of Bacillus Subtilus JC3, which fills up the pores in the concrete making dense microstructure.Split Tensile and Flexural strength of concrete at 28 days increased by about 1422% and 21-30% respectively.

3. The addition of Bacillus subtilis JC3 strain increases the compressive strength, split tensile strength and flexural strength of concrete when compared to controlled concrete. Bacteria induced concrete has substantially high modulus of elasticity. 4. From the durability studies, the percentage weight losses and percentage strength losses revealed that Bacterial concrete has less weight and strength losses than the conventional concrete against any acid attacks. It is revealed that bacterial concrete is more durable in terms of “Acid Durability Factor” than conventional concrete and less attacked in terms of “Acid Attack Factor” than conventional concrete.

In bacterial concrete, as it gains strength, hardness increases and as a result, the rebound hammer values are more because of greater elastic rebound. In order to assess particle continuity inside the concrete specimen, USPV test is recommended. Grades of Normal concrete have higher current flow when compared to Grades of Bacterial concrete. Bacterial concrete will have dense microstructure due to precipitation of mineral in pores of concrete. The impermeability of concrete can be represented by the rate of flow or diffusion coefficient of chloride ions through the unit area of concrete. Diffusion Coefficient (DC) of

5. In bacterial concrete, induction of microorganisms inside the concrete has enormous effect on the porosity within the cement matrix paste, on the particle size distribution of the crystalline phases and on the presence of in-homogeneities within the hydrated paste due to mineral precipitation. Calcite

13

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

mineral precipitation results in less capillary porosity in the hardened paste and hence a greater strength. This reduced capillary porosity also favours the formation of fine-textured hydration products with optimized particle size distribution of the cementitious materials in order to increase the potential packing density. So bacteria incorporated concrete has increased packing density and reduced capillary porosity. The calcite crystals formed will glue together the hydrated particles which reduce the interstitial porosity between them. 6. Furthermore the effect of mineral precipitation homogenously in bacterial concrete leads to a reduction in inhomogeneities within the paste and hence improved paste strength. The strength of the paste will be limited by the flaws that form the weakest link, be the inhomogeneities or capillary pores. In order to improve the strength of the paste as a whole, all such flaws must be minimized. Therefore bacterial concrete is a new approach to enhance the strength and durability of the concrete economically. 7. The incorporation of microorganisms into concrete confers enhanced durability on the concrete. In bacterial concrete significant reductions in water permeability and chloride ingress have been observed along with its increased resistance to attack by aggressive chemicals.From the investigation, it has been revealed that bacterial concrete has better resistance against strength deterioration for all curing conditions and curing ages. REFERENCES [1]

[2]

Bang SS, Galinat JK, and Ramakrishnan V. Calcite precipitation induced by polyurethaneimmobilized Bacillus pasteurii” Enzyme and Microbial Technology, 28(2001) 404-09

[3]

De Muynck, W., D. Debrouwer, N. De Belie, and W. Verstraete. 2008. “Bacterial carbonate precipitation improves the durability of cementitious materials.” Cement Concrete Res. 38: 1005-1014.

[4]

Knorre, H. and W. Krumbein. 2000. “Bacterial calcification,” pp. 25-31. In R. E. Riding and S. M Awramik (eds.). Microbial Sediments. Springer-Verlag, Berlin, Germany.

[5]

Ramakrishnan V, Ramesh KP, and Bang SS. South Dokata School of Mines and Technology, USA, Bacterial Concrete, Proceedings of SPIE, Vol. 4234 pp. 168-176, Smart Materials.

[6]

Ramikrishnan V, Panchalan RK, Bang, SS. Improvement of concrete durability by bacterial mineral precipitation” Proceedings ICF 11, Torino, Italy, 2005.

[7]

S.K. Ramachandran, V. Ramkrishnan, S.S. Bang, “Remediation of concrete using microorganisms”, ACI Materials Journal 98 (1) (2001) 3–9.

[8]

Santhosh KR, Ramakrishnan V, Duke EF, and Bang SS, SEM Investigation of Microbial Calcite Precipitation in Cement Proceedings of the 22nd International Conference on Cement Microscopy, pp. 293-305, Montreal, Canada, 2000.

[9]

V.Ramakrishnan, S.S. Bang, K.S. Deo, “A novel technique for repairing cracks in high performance concrete using bacteria”, Proceeding of the International Conference on High Performance, High Strength Concrete, Perth, Australia, 1998, pp. 597– 617.

[10] Day JL, Panchalan RK, Ramakrishnan V. Microbiologically induced sealant for concrete crack remediation Proceedings of the 16th Engineering Mechanics conference, Seattle, WA, 2003.

Bachmeier K, Williams A E, Warminton J and Bang, S.S. Urease activity in Microbiologically-induced calcite precipitation” Journal of Biotechnology,93(2002)171-181.

14

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.15-23.

An Experimental Investigation on Strength Properties of Artificial Light Weight Aggregate Concrete using Agricultural by Product such as Ground Nut Shell Ash V. Bhaskar Desai1, K. Mallikarjunappa2 and A. Sathyam3 1

Professor, Dept. of Civil Engineering, 2,3Research Scholar JNTUA College of Engineering, Anantapuramu, A.P. 2 Dy. Executive Engineer, Dharmavaram Municipality, Dharmavaram 3 Conservation Assistant Gr-I, Archaeological Survey of India, Anantapuramu Sub Circle, Anantapuramu

ABSTRACT Light weight aggregate concrete has become more popular in recent advancements owing to the tremendous advantages it offers over the conventional concrete but at the same time strong enough to be used for structural purpose. The most important characteristic of light weight concrete is its low thermal conductivity, lower density, internal curing property etc. Groundnut Shell Ash (GSA) is a waste material obtained from oil mills as an agricultural waste. Pelletized Groundnut Shell Ash aggregate can be used as one type of coarse aggregate in the production of stronger, more durable and more ductile concrete used in certain places where natural aggregate is not available or costly or recycling of the agricultural wastes is aimed at or where the dead weight of the structure is to be reduced. But a limited work on the study of strength property has been carried out on replacement of conventional granite aggregate in different percentages (0, 25, 50,75,100) with light weight aggregates such as pelletized Groundnut Shell Ash(GSA), cinder, pumice, perlite etc. So true need of wide range of investigation in this direction is needed to explain the exact behaviour of the light weight aggregate in partial and full replacement of conventional granite aggregate by light weight aggregate. In the present experimental investigation an attempt has been made to study the compressive strength, split tensile strength, flexural strength properties etc., are to be studied to have a comprehensive understanding by replacing natural aggregate with pelletized GSA aggregate in different percentages (0,25,50,75 and 100) by volume of concrete. Keywords— light weight aggregate, ground shell ash, pellets. INTRODUCTION

prepared by mixing 47% GSA, 47% lime and 6% cement as binding material with 12.50% water by overall weight, and by rotation of this mixture in a drum type pelletizer machine. This machine is designed especially for making artificial aggregate in pellets form.

Groundnut Shell is agricultural waste product produced from oil mills and by burning this Ground nut shell (GS) it gets converted in to Groundnut Shell Ash (GSA) which is the material with fully fused particles. After burning of 1 kg of ground nut shell, the ash quantity obtained is 145 gm. This ground nut shell ash powder is crushed by machine. It is then sieved through 90 micron sieve. Due to continuous usage of naturally available aggregate, within a short length of time natural resources get depleted and it will be left nothing for future generations. Hence there is a necessity for artificially preparing both the normal and artificial aggregate making use of waste materials from agricultural products and industries. From the earlier studies it appears that much less attention has been paid towards the study using artificial coarse aggregates.

The GSA aggregate can be really brought under light weight aggregate because the concrete made with this aggregate will come under the category of light weight aggregate concrete. Since the weight of such concrete will be less than the weight of normal concrete. Pelletizing Process— The Pelletization process is used to manufacture light weight Coarse aggregate. Some of the parameters that need to be considered for the efficiency of the production of pellets such as speed of revolution of pelletizer disc, moisture content, angle of pelletizer disc and duration of Pelletization (HariKrishnan and RamaMurthy, 2006). Usually the different types of pelletizer machines are used in practice to make the pellets such as disc or pan type, drum type, cone type and mixer type. With mixer type pelletizer small grains are formed initially and are subsequently increased. In the cold bonded method, increase of strength of pellets

In this investigation an attempt has been made to make light weight concrete with light weight GSA aggregate as coarse aggregate which is available as an agricultural waste material. The loose densities of GSA aggregate vary from 810 to 1013 kg/m3 and the compacted densities are varying between 940 to 1075 kg/m3. GSA pellets are 15

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

depends on the increase of the lime and cement ratio by weight. Moisture content and angle of drum parameter influence the size growth of pellets. The dosage of binding agent is more important for making the GSA aggregate balls. Initially some percentage of water is added in the binder and remaining water is sprayed during the rotation Period because while rotating without water in the drum the GSA aggregate and binders (Lime & Cement) tends to form lumps and does not increase the distribution of particle size. The pellets are formed approximately in duration of 6 to 7 minutes. The cold bonded pellets are hardened by normal water cooling/curing method for 28 days. Plate 2 shows a view of drum pelletizer used for pelletization.

% of the 28 day strength within 7 days. The strength growth from 28 to 90 days is generally low and decreases with increasing concrete strength level. This is assumed to be a consequence of the strength limiting effect of the light weight aggregate. Curcio, F., Galeota, D., Gallo, A., Giammatteo, M. (8) had shown that the Norwegian design code, NS 3473 (1998) reduces the tensile strength of Light weight aggregate concrete compared with normal weight concrete of the same compressive strength multiplying with a factor (0.3 + 0.7 D/2400) if the tensile strength is not determined by testing, where D is the density of the concrete in kg/m³. For the ratio between flexural and splitting tensile strength of high performance Light weight aggregate concrete, values of 1.5 to 1.6 have been found.

REVIEW OF LITERATURE H.Bomhard (1) had reported that Structural light weight aggregate concretes are considered as alternatives to concretes made with dense natural aggregates because of the relatively high strength to unit weight ratio that can be achieved.

Alduaij et al. (9) studied light weight concrete using different unit weight aggregate including light weight crushed bricks, light weight expanded clay and normal weight gravel without the use of natural fine aggregate (no-fines concrete). They obtained a light weight concrete with 22 MPa cylinder compressive strength and 1520 kg/m³ dry unit weight at 28 days.

F.W.Lydon (2) stated that for light weight aggregate concrete, it is more relevant for mix design purpose to relate strength to cement content.

Expermental Investigation— An experimental study has been conducted on concrete with partial replacement of conventional coarse aggregate i.e., granite by light weight aggregate i.e., GSA aggregate. The test program consists of carrying out compressive tests on cubes, split tensile tests on cylinders, modulus of elasticity tests on cylinders, flexural strength on beam elements. Analysis of the results has been done to investigate effect of GSA aggregate on the compressive strength, split tensile strength, flexural strength and modulus of elasticity properties. Variations of various combinations have been studied.

In Japan JASS (3) reported that, light weight concretes do not specify any density values, and properties are only provided for concrete made with light weight coarse and fine aggregates. FIP, 1983 (4) stated that in general the effect of using super plasticizer in light weight aggregate concrete is similar to that of using them in normal weight concrete. It is possible that part of the fluid admixtures may be absorbed by light weight aggregate, thus reducing their action if the light weight aggregate is unsoaked. The absorption of a part of the free water with the dissolved additives will decrease the effectiveness of the latter.

DESCRIPTION OF CONSTITUENT MATERIALS AND PROPERTIES USED IN THE INVESTIGATION

According to Clarke, J.L (5) Tensile strength of concrete is important when considering cracking. Light weight aggregate concrete presents a flexural and tensile splitting strength slightly inferior to that of normal weight concrete of the same compressive strength.

The constituent materials are presented in plate 1. Mix Design of Concrete— The concrete mix has been designed for M20 grade concrete using ISI method. The mix proportion obtained is 1:1.55:3.04 with constant water cement ratio 0.50.

Owens, P.L. (6) had stated that Light weight aggregate concrete has been used for structural purposes since the 20th century. The Light weight aggregate concrete is a material with low unit weight and often made with spherical aggregates. The density of structural Light weight aggregate concrete typically ranges from 1400 to 2000 kg/m³ compared with that of about 2400 kg/m³ for normal weight aggregate concrete.

Mixing, Casting and Curing— In this present investigation it is aimed to study the different strength variations by modifying the conventional concrete with GSA aggregate. It is added to concrete in percentages of 0%, 25%, 50%, 75% & 100% by volume of concrete and designated as mixes GSA-0, GSA-25, GSA-50, GSA-75 & GSA-100 respectively. Hence cement, fine aggregate, coarse aggregate, i.e., Granite and GSA aggregate in required percentages are calculated and then mixed.

Thorenfeldt, E reported that (7) Light Weight Aggregate Concrete has a faster hardening factor in the initial setting phase than conventional concrete, normally reaching 80 16

An Experimental Investigation on Strength Properties of Artificial Light Weight Aggregate Concrete using Agricultural …

Required quantity of water is added to this and mixed thoroughly by hand mixing.

casted specimens are shown in plate 3. For all test specimens, moulds were kept on the vibrating table and the concrete was poured into the moulds in three layers each layer being compacted thoroughly with tamping rod to avoid honey combing. Finally all specimens were vibrated on the table vibrator after filling up the moulds up to the brim. The vibration was effected for 7 seconds and it was maintained constant for all specimens and all other castings.

Table 1: Properties of Materials

Sl. No 1

Name of the material OPC – 53 Grade

2

Fine Aggregate passing 4.75mm sieve

3

GSA Aggregate passing 20 – 10 mm

4

Natural Aggregate passing 20 – 10 mm

5

Water

Properties of Result material Specific Gravity 3.07 Initial setting 60 min time Final Setting 489 time min Fineness 4% Normal 33.50 consistency % Specific Gravity 2.60 Fineness 3.24 modulus Specific Gravity 1.43 Fineness 4.47 modulus Bulk density 1075 compacted Kg/m3 Specific Gravity 2.68 Fineness 3.37 modulus Bulk density 1620 compacted Kg/m3 Locally available potable water which is free from concentration of acids and organic substances has been used in this work.

Table 2: Details of Specimens

Replacement of conventional coarse aggregate by GSA Aggregate GSA-0 100 0 GSA-25 75 25 GSA-50 50 50 GSA-75 25 75 GSA-100 0 100 Total specimens Name of the Mix

No of specimens cast 24 24 24 24 24 120

However the specimens were demolded after 24 hours of casting and were kept immersed in a clean water tank for curing. Curing pond as shown in plate 4. After 28 and 90 days of curing the specimens were taken out of water and were allowed to dry under shade for few hours. For each age of curing at least 3-specimens were cast for each variable. TESTING OF SPECIMENS Plain Cube Specimens The compression test on the plain cubes was conducted on 3000 KN digital compression testing machine. This test set up presented in plate 5 & 6. The specimens after being removed from water were allowed to dry under shade for 24 hours and white washed for easy identification of minute cracks, while testing.

GSA aggregate is added to concrete in 5 different volumetric fractions to prepare five different mixes which are designated as follows: Super plasticizer was not used due to use of pre wetted GSA aggregate. To proceed with the experimental programmed initially all the moulds of size 150x150x150 mm and cylinders of size 150mm diameters and 300mm height were taken and these moulds were cleaned and were brushed with machine oil on all inner faces to facilitate easy removal of specimens afterwards.

The plain cube specimens were placed in the compression testing machine such that load was applied centrally. The top plate of the testing machine was brought into contact with the surface of the plain cube specimen to enable loading. The cube test results are presented in table 3.

To start with, all the materials were weighed in the ratio 1:1.55:3.04. First fine aggregate and cement were added and mixed thoroughly and then granite coarse aggregate and partially replaced pre wetted GSA aggregate was mixed in required volume and proportion. All of these were mixed thoroughly by hand mixing.

Split Tensile Strength Test on Cylinders The cylindrical specimen was kept horizontally between the compressive plates of the testing machine. The load was applied uniformly until the cylinder fails, the loads related to ultimate load are recorded. This test was conducted for cylinders with different GSA aggregate additions. This setup is presented in plate 7 & 8. The split tensile strength was calculated by the standard formula.

Each time 3 plain cubes of size 150 x 150 x 150mm, 3 flexure beams of size 500 x 100 x 100mm and 6 cylinders of size 150mm diameter, 300mm height were cast. The 17

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

Split tensile strength ( ft) =

DISCUSSION OF TEST RESULTS

Where P = Maximum load in Newton

Influence of GSA Aggregate on Cube Compressive Strength

D = Diameter of the cylinder in mm

In the present study, GSA aggregate has been added in the volumetric percentages of 0%, 25%, 50%, 75%, 100% replacing the natural conventional granite aggregate. The corresponding cube compressive strengths at 28 days and 90 days are presented in table 3. The variation of compressive strengths and percentage of increase or decrease verses percentage of GSA aggregate addition are shown in fig 1 for 28 days and 90 days. From the above figs, it may be observed that with the addition of GSA aggregate the cube compressive strength decreases continuously up to 100% replacement of Granite by GSA aggregate, but more than the target mean strength of M20 concrete has been achieved even when the natural granite aggregate is replaced with 50% of GSA aggregate as tabulated in table 3 for 90 days curing period and the design strength of M20 concrete is achieved when replaced with 25% of GSA aggregate as tabulated in table 3 for 28 days. In addition for GSA-100 mix, the design strength of M20 concrete is achieved at 90 days. At 28 days up to GSA 75 mix for all mixes design strength is achieved.

L = Length of the cylinder in mm The results are presented in table 4. Compression Test on Cylinder Specimens to Find ‘E’ Value An attempt was made to find out the modulus of elasticity has been done in this investigation for this, various GSA concrete mixes studied. The compression was effected by the 3000 KN automatic compression testing machine with 0.5KN/sec rate of loading. An automatic digital compressive testing machine gives the compression test results of the cylinder while loading. The results of modulus of elasticity are furnished in table 6. The test setup is shown in plate 11 & 12. Testing of Beams for Flexural Strength

Influence of GSA Aggregate on Split Tensile Strength on Cylinder Specimens

The loading arrangement to test the specimens for flexure is as follows. The element was simply supported over the span of 500mm. The specimen is checked for its alignment longitudinally and adjusted if necessary. Required packing is given using rubber packing. Care is taken to ensure that two loading points at the same level. The loading is applied on the specimen using 15 ton precalibrated proving ring at regular intervals. The load is transmitted to the element through the I- section and two 16mm diameter rods are placed at 166.67mm from each support. For each increment of loading the deflection at the centre and at 1/3rd points of beam are recorded using dial gauge. Continuous observations are made. Before the ultimate stage the deflection meters are removed and the process of load application is continued. As the load was increased the cracks are widened and extended to top and finally the specimen collapsed in flexure. At this stage the load is recorded as the ultimate load. Making use of the above data flexural strength has been calculated using the following formula.

With increase in percentage of replacement of granite by GSA aggregate, the percentage of decrease of split tensile strength is found to increase continuously up to 100% as shown in fig 2 for 28 days and for 90 days. These are presented in table 4 for 28 days and for 90 days. Influence of GSA Aggregate on Density The variation of density and percentage of increase or decrease in density verses percentage of GSA aggregate added in fig 3 for 28 days and for 90 days. The results are presented in table 5. From the above figs and tables, it may be observed that with the addition of GSA Aggregate the density of the specimens decreases continuously up to 100% replacement of Granite by GSA Aggregate. Also the density increases with the increase of the age. Influence of GSA Aggregate on Modulus of Elasticity The modulus of elasticity results with various percentages replacements of natural aggregate by GSA Aggregate are presented in table 6 for 28 days and 90 days respectively. From the results it is observed that modulus of elasticity has been decreasing with an increase in replacement of natural granite aggregate by GSA Aggregate. It is also observed that the modulus of elasticity are in satisfactory agreement with those calculated using as per IS code, Empirical formula. Fig 4 shows the variation of E value versus percentage of GSA for 28 days and 90 days. It also shows that E value increases with the age i.e. from 28 to 90 days

Flexural strength (f) = in N/mm2 Where M = Bending moment in N.mm Z = = Section modulus in mm3 The results have been tabulated and graphical variations have been studied. The test set up is shown in plate 9 & 10 and the results are tabulated in table 9.

18

An Experimental Investigation on Strength Properties of Artificial Light Weight Aggregate Concrete using Agricultural … Table 3: Comparision of Cube Compressive Strength Results for 28 Days and 90 Days Curing Periods

Sl. No 1. 2. 3. 4. 5.

Compressive strength (N/mm2)

Percentage replacement of coarse aggregate

Name of the mix GSA-0 GSA-25 GSA-50 GSA-75 GSA-100

Natural aggregate 100 75 50 25 0

Pelletized GSA aggregate 0 25 50 75 100

Percentage of increase or decrease in compressive strength w.r.t GSA-0

28 Days

90 Days

28 Days

90 Days

41.08 25.53 24.80 21.62 18.43

47.39 35.02 26.93 23.85 20.76

0.00 -37.85 -39.63 -47.37 -55.14

0.00 -26.10 -43.17 -49.67 -56.19

Table 4: Comparision of Split Tensile Strength Results for 28 Days and 90 Days Curing Periods

Sl. No

1. 2. 3. 4. 5.

Split tensile strength (N/mm2)

Percentage replacement of coarse aggregate

Name of the mix

Natural aggregate

GSA-0 GSA-25 GSA-50 GSA-75 GSA-100

100 75 50 25 0

Pelletized GSA aggregate 0 25 50 75 100

Percentage of increase or decrease in Split tensile strength w.r.t GSA-0

28 Days

90 Days

28 Days

90 Days

3.58 2.81 2.42 2.26 1.37

4.00 2.89 2.62 2.37 1.94

0.00 -21.51 -32.40 -36.87 -61.73

0.00 -27.75 -34.50 -40.75 -51.50

Table 5: Comparision of Density Results for 28 Days and 90 Days Curing Periods

Sl. No

Name of the mix

1. 2. 3. 4. 5.

GSA-0 GSA-25 GSA-50 GSA-75 GSA-100

Density (Kg/m3)

Percentage replacement of coarse aggregate Natural Pelletized GSA aggregate aggregate 100 0 75 25 50 50 25 75 0 100

Percentage of increase or decrease in density w.r.t GSA-0

28 Days

90 Days

28 Days

90 Days

2279 2103 2012 1932 1808

2452 2303 2202 2050 1881

0.00 -7.73 -11.71 -15.26 -20.64

0.00 -6.08 -10.20 -16.39 -23.29

Table 6: Comparision of Young’s Modulus Results for 28 Days and 90 Days Curing Periods

Sl. No 1. 2. 3. 4. 5.

Name of the mix GSA-0 GSA-25 GSA-50 GSA-75 GSA-100

Young’s modulus (N/mm2)

Percentage replacement of coarse aggregate Natural aggregate 100 75 50 25 0

Pelletized GSA aggregate 0 25 50 75 100

19

Percentage of increase or decrease in young’s modulus w.r.t GSA-0

28 Days

90 Days

28 Days

90 Days

3.20*104 2.53*104 2.49*104 2.32*104 2.15*104

3.44*104 2.96*104 2.60*104 2.44*104 2.28*104

0.00 -20.94 -22.19 -27.50 -32.81

0.00 -13.95 -24.41 -29.06 -33.72

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 7: Ratio of Cilinder Compressive Strength to Cube Compressive Strength Results for 28 Days Curing Period

Sl. No

Name of the mix

1. 2. 3. 4. 5.

GSA-0 GSA-25 GSA-50 GSA-75 GSA-100

Compressive strength (N/mm2)

Percentage replacement of coarse aggregate Natural Pelletized GSA aggregate aggregate 100 0 75 25 50 50 25 75 0 100

Cube

Cylinder

Ratio of cylinder to cube compressive strength

41.08 25.53 24.80 21.62 18.43

28.01 12.60 12.34 11.45 9.53

0.68 0.49 0.50 0.53 0.52

Table 8: Ratio of Cilinder Compressive Strength to Cube Compressive Strength Results for 90 Days Curing Period

Sl. No 1. 2. 3. 4. 5.

Name of the mix GSA-0 GSA-25 GSA-50 GSA-75 GSA-100

Compressive strength (N/mm2)

Percentage replacement of coarse aggregate Natural Pelletized GSA aggregate aggregate 100 0 75 25 50 50 25 75 0 100

Cube

Cylinder

Ratio of cylinder to cube compressive strength

47.39 35.02 26.93 23.85 20.76

28.04 18.73 17.07 16.81 12.77

0.59 0.53 0.63 0.70 0.62

Table 9: Comparision of Flexural Strength Results for 28 Days and 90 Days Curing Periods

Sl. No 1. 2. 3. 4. 5.

Name of the mix GSA-0 GSA-25 GSA-50 GSA-75 GSA-100

Flexural strength (N/mm2)

Percentage replacement of coarse aggregate Natural aggregate 100 75 50 25 0

Pelletized GSA aggregate 0 25 50 75 100

Percentage of increase or decrease in flexural strength w.r.t GSA-0

28 Days

90 Days

28 Days

90 Days

4.49 3.54 3.48 3.25 3.01

4.81 4.14 3.63 3.63 3.41

0.00 -21.16 -22.49 -27.62 -32.96

0.00 -13.93 -24.53 -24.53 -29.11

formula 0.70 √ . These values are presented in the table 9 and the graphical representation is shown in fig 5. Both results are found to be in satisfactory agreement with each other.

Influence of GSA Aggregate on Flexural Strength on Beams Concrete as we know is relatively strong in compression and weak in tension. In reinforced concrete members, little dependence is placed on the tensile strength of concrete since steel reinforcing bars are provided to resist all tensile forces. However; tensile stresses are likely to develop in concrete due to drying shrinkage, rusting of steel reinforcement, temperature gradients and many other reasons. Therefore, the knowledge of tensile strength of concrete is of importance. Flexural strength of beams of size 500 x 100 x 100mm with various percentage replacements of natural aggregate by GSA aggregate are presented in the table 9 for 28 days and 90 days. From the results it is observed that flexural strength of beams has been decreasing with an increase in replacement of natural granite aggregate with GSA aggregate. In addition flexural strength of beams is calculated based on the

Plate 1: Constituent materials

20

An Experimental Investigation on Strength Properties of Artificial Light Weight Aggregate Concrete using Agricultural …

Plate 6: Test set up of cube compressive strength (After Testing)

Plate 2: Drum pelletizer

Plate 7: Test set up of split tensile strength (before testing) Plate 3: Specimens after moulding in green state

Plate 8: Test set up of split tensile strength (after testing)

Plate 4: Spcimens curing pond

Plate 9: Test set up of flexural strength (before testing)

Plate 5: Test set up of cube compressive strength (before testing)

21

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

28 Days 90 Days Scale x-axis 1 Unit = 25% 2 y-axis 1 Unit = 1 N/mm

Split tensile strength in N/mm

2

5

4

3

2

1

0

Plate 10: Test set up of flexural strength (after testing)

0

25

50

75

100

Percentage of pelletized GSA aggregate replacing natural aggregate

Fig. 2: Superimposed variation between split tensile strength and percentage of pelletized GSA aggregate replacing natural aggregate 2500

Density Kg/m

3

2000

Plate 11: Test set up of cylinder compressive strength (before testing)

1500

1000

28 Days 90 Days Scale x-axis 1 Unit = 25% 3 y-axis 1 Unit = 100 Kg/m

500

0 0

25

50

75

100

Percentage of pelletized GSA aggregate replacing natural aggregate

Fig. 3: Superimposed variation between density and percentage of pelletized GSA aggregate replacing natural aggregate

28 Days 90 Days Scale x-axis 1 Unit = 25% 4 2 y-axis 1 Unit = 0.50x10 N/mm

4.0

Young's Modulus in N/mm

2

3.5

Plate 12: Test set up of cylinder compressive strength (after testing) 28 Days 90 Days Scale x-axis 1 Unit = 25% 2 y-axis 1 Unit = 5 N/mm

50

Cube compressive strength in N/mm

2

45 40

3.0 2.5 2.0 1.5 1.0 0.5

35 30

0.0

25

0

25

50

75

100

Percentage of pelletized GSA aggregate replacing natural aggregate

20 15 10

Fig. 4: Superimposed variation between young’s modulus and percentage of pelletized GSA aggregate replacing natural aggregate

5 0 0

25

50

75

100

Percentage of pelletized GSA aggregate replacing natural aggregate

Fig. 1: Superimposed variation between cube compressive strength and percentage of pelletized GSA aggregate replacing natural aggregate

22

An Experimental Investigation on Strength Properties of Artificial Light Weight Aggregate Concrete using Agricultural …

3) From the study it may be concluded that the young’s modulus has been observed to decrease continuously with the increase in percentage of GSA Aggregate i.e., from 0 to 100% replacement of Granite aggregate by GSA Aggregate.

28 Days 90 Days Scale x-axis 1 Unit = 25% 2 y-axis 1 Unit = 0.5 N/mm

5.0 4.5

Flexural strength in N/mm

2

4.0 3.5

4) From the study it may be concluded that the density has been observed to decrease continuously with the increase in percentage of GSA Aggregate i.e., from 0 to 100% replacement of Granite aggregate by GSA Aggregate.

3.0 2.5 2.0 1.5 1.0 0.5

5) The modulus of elasticity values calculated from experimentation and theoretical formulae are found to be more or less in satisfactory agreement.

0.0 0

25

50

75

100

Percentage of pelletized GSA aggregate replacing natural aggregate

6) The flexural strength is found to decrease continuously with the percentage increase in GSA aggregate content. The flexural strength values calculated through experimentation and calculated through empherical formula are more or less in satisfactory agreement.

Fig. 5: Superimposed variation between flexural and percentage of pelletized GSA aggregate replacing natural aggregate

Ratio of Cylinder strength to Cube strength

0.75 0.70 0.65 0.60

REFERENCES

0.55 0.50 0.45 0.40 0.35

28 Days 90 Days Scale x-axis 1 Unit = 25% y-axis 1 Unit = 0.05

0.30 0.25 0.20 0.15 0.10 0.05

[1]

H. Bombard, Light weight concrete structures, potentialities, limits and realities, The Concrete Society, The Construction Press, Lancaster, UK, 1980, pp. 227– 290.

[2]

F.W. Lydon, Concrete Mix Design, 2nd ed., Applied Science, London, 1982.

[3]

JASS 5 (Revised 1979): Japanese Architectural Standard for Reinforced Concrete, Architectural Institute of Japan, Tokyo, 1982 (March).

[4]

FIP. Manual of Light Weight Aggregate Concrete, 2nd. Edition, 1983.

[5]

Clarke, J.L. Design Requirements. Structural Light weight Aggregate Concrete, Chapman & Hall, London, pp. 45-74, 1993.

[6]

Owens, P.L. (1993). “Light weight aggregates for structural concrete,” Structural Light weight Aggregate Concrete, Chapman & Hall, London, pp.1-18.

[7]

Thorenfeldt, E., Design Criteria of Light weight Aggregate Concrete. CEB/FIP International Symposium on Structural Light weight Aggregate Concrete, Sand fjord, Norway, pp. 720- 732, 1995.

[8]

Curcio, F., Galeota, D., Gallo, A., Giammatteo, M. Highperformance Light weight concrete for the Precast Prestressed Concrete Industry. Proc.4th. Int.CANMET/ ACI/JCI Symposium, Japan, pp. 389-406, 1998

[9]

Alduaij, K. Alshaleh, M.N. Haque, K. Ellaithy, Lightweight concrete in hot coastal areas, Cem. Concr. Compos. 21 (5– 6) (1999) 453–458.

0.00 0

25

50

75

100

Percentage of pelletized GSA aggregate replacing natural aggregate

Fig. 6: Superimposed Variation Between Ratio of Cylinder Strength to Cube Strength and Percentage of Pelletized GSA Aggregate Replacing Natural Aggregate

CONCLUSIONS From the limited experimental study carried out in this investigation the following conclusions are seem to be valid. 1) From the study it may be concluded that the cube compressive strength has been observed to decrease continuously with the increase in percentage of GSA Aggregate i.e., from 0 to 100% replacement of Granite aggregate by GSA Aggregate. 2) From the study it may be concluded that the split strength has been observed to decrease continuously with the increase in percent age of GSA Aggregate i.e., from 0 to 100% replacement of Granite aggregate by GSA Aggregate.

23

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.24-27.

Effect of Shear Wall on Response of Multi-Storied Building Frame Nilesh Sawakare1, Hemant S. Chore2, Prasad A. Dode3 and R.M. Fuke4 1 P.G. Student, 2Prof. and Head, 3Assistant Professor Department of Civil Engineering/Datta Meghe College of Engineering, Airoli, Navimumbai Email: [email protected], [email protected], [email protected] 4 Assistant Professor, Department of Civil Engineering, College of Engineering, Akola (Maharashtra).

ABSTRACT Shear wall is one of the most commonly used lateral load resisting in high rise building. Shear wall has high in plane stiffness and strength which can be used to simultaneously resist large horizontal load and support gravity load. In the seismic design of buildings, reinforced concrete structural walls, or shear walls, act as major earthquake resisting members. Structural walls provide an efficient bracing system and offer great potential for lateral load resistance. In this present study, main focus is to determine the solution for shear wall location in multi-storey building. The residential medium rise building is analyzed for earthquake force by considering two type of structural system. i.e. Frame system and Dual system. Effectiveness of shear wall has been studied with the help of Four different models. Four different types of Model is used one is bare frame structural system and other three models are dual type structural system. Analysis is carried out by using standard package ETABS. The comparison of these models for different parameters like Story Shear, Story Displacement and Storey Drift has been presented by replacing column with shear wall. Keywords— Lateral displacement, Shear force, Storey drift, Storey shear, Shear wall, Time period. these place and displacement is quite heavy. Shear walls are usually used in tall building to avoid collapse of buildings. When shear wall are situated in advantageous positions in the building, they can form an efficient lateral force resisting system. In this present paper one model for bare frame type residential building and six models for dual type structural system are generated with the help of ETABS and effectiveness has been check.

INTRODUCTION Reinforced concrete shear walls are used in building to resist lateral force due to wind and earthquakes. They are usually provided between column lines, in stair wells, lift wells, in shafts that house other utilities. Shear wall provide lateral load resisting by transferring the wind or earthquake load to foundation. Besides, they impart lateral stiffness to the system and also carry gravity loads. Shear wall are one of the excellent means of providing earthquake resistance to multi storied reinforced concrete building. The structure is still damaged due to some or the other reason during earthquakes. Behavior of structure during earthquake motion depends on distribution of weight, stiffness and strength in both horizontal and planes of building. To reduce the effect of earthquake reinforced concrete shear walls are used in the building. These can be used for improving seismic response of buildings. Structural design of buildings for seismic loading is primarily concerned with structural safety during major Earthquakes, in tall buildings, it is very important to ensure adequate lateral stiffness to resist lateral load.

BUILDING DESCRIPTION A building is assumed for seismic analysis that consists of a G+12 R.C.C. Residential building. The plan of the building is regular in nature as it has all columns at equal spacing. The building is located in Seismic Zone III and is assume on hard type soil. The building is 39.0 m in height 30.0 m in length and 20m in width. The important features of this building are shown in Table 1. MODEL & ANALYSIS Building is modeled using stander package ETAB. Beams and columns are modeled as two noded beam elements with six DOF at each node. Shear wall are modeled using shell element. Equivalent static analysis or linear static analysis is performed on models. Based on analysis result parameters such as storey shear, story displacement for each model. Following the model have been considered.

The provision of shear wall in building to achieve rigidity has been found effective and economical. When buildings are tall, beam, column sizes are quite heavy and steel required is large. So there is lot of congestion at these joint and it is difficult to place and vibrate concrete at 24

Effect of Shear Wall on Response of Multi-Storied Building Frame Table 1: Salient features of the building

1.

Type of Structure

2. 3. 4. 5.

7.

Zone Layout Number of stories Ground storey height Floor-to-floor height External walls

8.

Internal walls

9. 10. 11. 12.

Live load Materials Seismic analysis Design Philosophy

6.

13.

Size of exterior column Size of interior column Size of beams in longitudinal and transverse direction Total thickness of slab

14. 15.

16.

Multi-storey pin jointed frame III As shown in Figure no 1 13 (G + 12) 3.0m Fig. 2: MODEL 2 (Frame supported by 2Bay shear wall).

3.0 m 250 mm thick including plaster 250 mm thick including plaster 3.0 kN/m2 M 30 and Fe 500 Equivalent static method Limit state method conforming to IS 456 : 2000 400 x 400 mm

Fig. 3: MODEL 3 (Frame supported by L-Type shear wall at all corner side.)

400 x 400 mm 230 x 600 mm

125 mm Fig. 4: MODEL 4 (Frame supported on central core shear wall.)

RESULTS & DISCUSSION Storey Shear The variations of base shear in X and Y direction with different models considered in the study is illustrated in Figure 8 and Figure 9. From the afore-mentioned figures, it is found that the base shear is on higher side in respect of model 2 as compared to the other cases. Fig. 1: MODEL 1 (Bare frame without shear wall).

: Bare frame without shear wall.

BASE SHEAR (KN)

Model I

BASE SHEAR IN X DIRECTION 6100

Model II : Frame supported by 2Bay shear wall. Model III : Frame supported by L-Type shear wall at all corner side. Model IV : Frame supported on central core shear wall.

6000 5900

BASE SHEAR IN X DIRECTION

5800 5700

5600 5500 5400 0

1

2

3

4

MODEL NUMBER

Fig. 8: Base shear in X- direction

25

5

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

increase in number of storeys. However, such trend is not acceptable. Further, in respect of other models, the storey drift is found to increase with number of storeys. The storey drift as found in other models is well within the limit as imposed by IS.

BASE SHEAR IN Y DIRECTION

BASE SHEAR (KN)

4950 4900 4850 4800 4750 4700 4650 4600 4550 4500

BASE SHEAR IN Y DIRECTION

STOREY DRIFT IN X DIRECTION 0

1

2

3

4

0.014

5

MODEL NUMBER

0.012

MODEL 1

0.01

DRIFT

Fig. 9: Base shear in Y- direction.

Storey Displacement

MODEL 2

0.008

MODEL 3

0.006

MODEL 4

0.004

The displacement in X and Y direction, graphical representation is shown in Fig. 10 and Fig. 11

0.002 0 0

200

DISPLACEMENT IN MM

180

2

3

4

5

6

7

8

9

10

11

12

13

NO. OF FLOOR

MODEL 1 MODEL 2 MODEL 3 MODEL 4

LATERAL DISPLACEMENT IN X DIRECTION

1

Fig. 12: Storey Drift in X direction

160 140

STOREY DRIFT IN Y DIRECTION

120 100

0.012

80 60

MODEL 1

0.01

40

MODEL 2

DRIFT

20 0 0

1

2

3

4

5

6

7

8

9

10

11

12

13

NO. OF FLOOR

0.008

MODEL 3

0.006

MODEL 4

0.004 0.002

Fig. 10: Lateral displacement in X- direction

0 0

LATERAL DISPLACEMENT IN Y DIRECTION

1

2

MODEL 1

3

4

5

6

7

8

9

10

11

12

13

NO. OF FLOOR

MODEL 2

DISPLACEMENT IN MM

MODEL 3 180 160 140 120 100 80 60 40 20 0

Fig. 11: Storey Drift in Y direction

MODEL 4

CONCLUSION

0

1

2

3

4

5

6

7

8

9

10

11

12

The behaviors of multistoried building with & without shear wall have been studied in present paper. In this present paper we got the results from analysis of model for case1 (model 1) its shows the more lateral displacement also base shear this case does not governs the case as per IS code 1893(part1) 2002. From fig. 8 & 9 shows base shear is more in X & Y direction as compared other cases. Graphical representation shown the exact result of analysis from we conclude that case 2 (Model 2) governs the as per codal requirement.

13

NO. OF FLOOR

Fig. 11: Lateral displacement in Y direction

From the graphical representation thereof as shown in Fig. 10-11, it is found that the building model 2 is stiffer than the other models. Limit of lateral storey displacement as per IS code 1893(part 1) 2002 is H/500.

From above results it is clear that shear wall frame interaction systems are very effective in resisting lateral forces induced by earthquake. Placing shear wall away from center of gravity resulted in increase in the most of the members forces. It follows that shear walls should be coinciding with the centroid of the building. For residential building shear walls can be used as a primary vertical load carrying element, thus serving the load and dividing space. Also observed that Changing the position of shear wall will affect the attraction of forces, so that

Storey Displacement The storey drift in X and Y direction, the graphical representation is shown in Fig. 12 and 13. From the storey drift in X and Y direction for seven different cases, it is seen that the model 1 is shows the higher storey drift [more than 1/250 as stipulated in IS: 1893-2002(Part-I)] at bottom and further, decreases with 26

Effect of Shear Wall on Response of Multi-Storied Building Frame

wall must be in proper position, If the dimensions of shear wall are large then major amount of horizontal forces are taken by shear wall & Providing shear walls at adequate locations substantially reduces the displacements due to earthquake.

[9]

REFERENCES [1]

[2]

[4]

[5]

[6]

[7]

[8]

[10]

IS 1893,2002,Indian standard Criteria for Earthquake Resistant design of structures(Fifth Revision),Indian Standard Institute, New Delhi. Aoyama, H., Design of Modern High Rise Reinforced Concrete Structures, Imperial College Press, London, UK, 2001. Agarwal P., and Shrikhande, M., “Earthquake Resistant Design of Structures”, Prentice hall of India Private Limited., September-2006. Ashraf, M., Siddiqi, Z.A. and Javed M.A., “Configuration Of A Multistorey Building Subjected to Lateral Forces”, Asian Journal Of Civil Engineering (Building And Housing) Vol. 9, No. 5, Pages 525-537, 2008. Cruz, E. F., and Cominetti, S., “Three-Dimensional Buildings Subjected to Bi-Directional Earthquakes. Validity Of Analysis Considering Unidirectional Earthquakes’’, Proceedings of 12 WCEE, 12th World Conference on Earthquake Engineering., 2000. Dowrick, D.J., Earthquake Resistant Design for Engineers and Architects, 2nd Edition, John Wiley & Sons, New York, NY,USA, 1987. Elnashai, A. S., and Sarno, L. D., “Structural Configurations and Systems for Effective Earthquake Resistance”, Fundamentals of Earthquake Engineering,

[11]

[12]

[13]

[14]

[15]

27

John Wiley & Sons, Ltd. ISBN: 978-0-470-02483-6, 2008. Guney, D., and Kuru çu, A. O., “Optimization of the configuration of infill walls in order to increase seismic resistance of building structures”, International Journal of the Physical Sciences Vol. 6(4), pp. 698-706, 18 February, 2011.” Haque, S., Amanat, K.M., “Seismic Vulnerability of Columns of RC Framed Buildings with Soft Ground Floor”, International Journal of Mathematical Models and Methods in Applied Sciences, Issue 3, Volume 2, 2008. Haque, S., Amanat, K.M., Strength and drift demand of columns of RC framed buildings with soft ground story”, Journal of Civil Engineering (IEB), 37 (2), 2009, pp 99110 Lucchini, A., Monti, G., and Kunnath, S.,“Nonlinear Response of Two-Way asymmetric Single-Story Building under Biaxial Excitation”, Journal Of Structural Engineering, Asc, January 2011. Laogan, B.T. and Elnashai, A.S., “Structural performance and economics of tall high strength RC buildings in seismic regions”. The Structural Design of Tall Buildings, 8 (3), 1999, pp. 171 – 204. Piazza, M., and Baldessari, C., and Tomasi, R., The Role Of In-Plane Floor Stiffness In The Seismic Behaviour Of Traditional Buildings”, The 14th World Conference on Earthquake Engineering, Beijing, China, October12-17, 2008,” Stefano, M.D., and Pintucchi, B., “A Model for Analyzing Inelastic Seismic Response of Plan-Irregular Building Structures”, 15th ASCE engineering mechanics conference, Columbia university, New York, NY, June 25, 2002.

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.28-32.

Triple Blended High Strength Concrete Mixes-Studies on Compressive and Impact Strengths D. Jayasree1, M. Bhasker2 and B.L.P. Swami3 1 Assistant Professor, 2Associate Professor, 3Professor Department of Civil Engineering, Vasavi College of Engineering, Ibrahimbagh, Hyderabad.

ABSTRACT The requirement of cement has increased due to more development in the infrastructure and hence, there is a need to use other materials than cement without changing the properties of concrete. Thus blending the concrete with other material is called supplementary material. The blended cement will produce stronger and more durable concrete than ordinary Portland cement concrete. Silica fume is also referred to as micro silica or condensed silica fume (CSF). Silica fume is a by-produce from electric arc furnaces used in the manufacture of silicon metal of silicon alloys. The addition of ultra fine particles in concrete improves strength of concrete. The optimum proportion of silica fume is found in between 4% to 15% by weight of cement. Fly ash is very useful in the preparation of blended cements. It is abundantly available as a waste by-product from various Thermal Power Stations. The project aims at finding the optimum replacement of cement by fly ash and condensed silica fume from which maximum benefits in various strengths and workability of mix can be obtained. Keywords— Pozzolonas, Triple Blending, Impact, Drop Hammer, Correlation. INTRODUCTION

Admixtures

Concrete Making

Admixture is defined as a material, other than cement, water and aggregates that is used as an ingredient of concrete and is added to the batch immediately before or during mixing. These days concrete is being used for wide varieties of purposes to make it suitable in different conditions. In such cases, admixture is used to modify the properties of ordinary concrete so as to make it suitable for any situation.

Cement concrete is one of the seemingly simple but actually complex materials. The properties of concrete mainly depend on the constituents used in concrete making. The main important materials used in making concrete are cement, sand, crushed stone and water. Eventhough the manufacturer guarantees the quality of cement, it is difficult to produce a fault proof concrete. It is because of the fact that the building material is concrete and not only cement. The properties of sand, crushed stone and water, if not used as specified, cause considerable trouble in concrete. In addition to these, workmanship, quality control and methods of placing also play leading role on the properties of concrete.

Pozzolonas are either naturally occurring or available as waste materials. In developing countries like India, pozzolonic materials are mainly available as industrial waste by-products. Fly ash, silica fume, stone dust, blast furnace slag, rice husk ash, etc., are some of the industrial wastes which possess pozzolonaic properties. The reactivity varies depending upon the type of pozzolona, its chemical composition and its fineness.

High Strength Concrete The primary difference between high strength concrete and normal strength concrete relates to the compressive strength that refers to the maximum resistance of concrete sample to applied pressure. Although there is no precise point of separation between high strength concrete and normal strength concrete, the American Concrete Institute (ACI) defines high strength concrete as concrete with a compressive strength greater than 40 MPa. Concrete of very high strength entered the field of construction of high rise buildings and long span bridges. In India, there are cases of using high strength concrete for prestressed concrete bridges.

Extensive research work has been carried on the use of pozzolonas in constructions materials. Out of the above pozzolona admixtures fly ash and condensed silica fume are used to derive certain desirable and enhanced properties compared to ordinary concrete. Several researchers have worked on the use of the above pozzolonic admixtures as replacement or addition to cement in preparing concrete mixes. The beneficial properties which result in concrete by the use of pozzolonas were highlighted by them.

28

Triple Blended High Strength Concrete Mixes-Studies on Compressive and Impact Strengths

Details of the Present Experimental Study

Mixing, Casting and Curing

In the present experimental investigation, OPC is blended with fly ash and CSF in various percentages as replacement. The triple blended concrete mixes of M60 and M80 grades are tested for compressive and impact strengths. A correlation between the two is attempted.

All the mixes were prepared by using a pan mixer. Required number of cube specimens were cast using the cube moulds of size 100mm x 100mm x 100mm. For impact test, cylinder specimens of size 152mm diameter and 63.5mm thickness were cast (Fig.1). Sufficient compaction was given by vibration. The specimens cast were allowed 24 hrs air dying after which demoulding was carried out and the specimens were transferred and immersed in water in a curing tank. After the age of 28 days, the specimens were taken out dried and tested. Required number of specimens were prepared for all combinations considered in the investigation. Mixing, casting and curing were carried out as per the standard specifications.

EXPERIMENTATION The following are the details of the experimental investigation carried out. Materials Basic Ingredients of Concrete Ordinary Portland Cement (OPC) 53 grade (M/s. Ultratech Ltd.), locally available river sand and crushed granite metal (20mm nominal size) are selected as the basic materials of concrete. All the materials were tested and found to satisfy the relevant I.S. specifications.

Testing Workability Test Workability of all the mixes of different combinations was determined using compacting factor apparatus. The workability of all the mixes was maintained at almost medium level (C.F=0.85 to 0.90) by adding the superplasticizer in required amongst not exceeding 2 percent.

Fly Ash and Condensed Silica Fume (CSF) The mineral admixture fly ash was obtained from Ramagundam Power Station of A.P. and CSF was obtained from M/s. V.B. Ferro Alloys Ltd., Rudraram near Hyderabad.

Compressive Strength Cube specimens were tested at the age of 28 days for compressive strength, following the standard specifications and using a standard compression testing machine. The compressive strength of the respective specimens was determined.

Superplasticizer Complast 430of M/s. Fosrock (India) Ltd., is employed as the chemical admixture to maintain the workability level. Water Potable water was used for concrete mixing.

Impact Strength by the Drop Hammer Test The impact strength of the specimens at the age of 28 days for different combinations was determined by conducting the drop hammer test (Fig.2) as per ACI 5442R-89 specifications.

High Strength Concrete Mixes In the present investigation high strength concrete mixes of M60 and M80 were designed by the D.O.E. method. The British code has adopted this method for concrete mix design. The proportions obtained are given in table-1.

Repeated impact, drop-weight test (Fig.2), yields the number of blows necessary to cause prescribed levels of distress in the test specimen. This number serves as a qualitative estimate of the energy absorbed by the specimen at the levels of distress specified. It can be adopted to show the relative impact resistance of different material thicknesses.

Table 1: Concrete Mix Proportions by Weight

Sl. No. 1. 2.

Mix Grade M60 M80

Fine Course Water/ Aggregate Aggregate Cement 1.00 1.07 1.75 0.33 1.00 0.98 1.60 0.38

OPC

In the case of high strength concrete mixes, specimens do not break even after giving 50 or 100 blows with drop hammer. It requires several blows (few hundreds) to break the specimens which is too laborious and time consuming. Hence, the cylinder specimens were given limited number of blows like 50 and 100 after which they were again tested for compression in the compression testing machine. This gives an idea about the influence of impact on the compressive strength of concrete and this results in a kind of rough correlation.

Triple Blended Cement Concrete Mixes Fly ash and CSF were simultaneously used as replacements to OPC. Four percentages of fly ash 0, 20, 30, 40 and four percentages of CSF 0, 5, 10 and 15 were tried as replacements to OPC in various combinations of triple blended concrete mixes. In all 16 combinations of triple blended concrete mixes are tried in the present investigation.

29

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

RESULTS AND DISCUSSION

strength but this does not come under triple blending. When both the admixtures are present it can be seen that 20% fly ash with 15% CSF gives the optimum and marginally higher compressive strength is generated. Even 30% fly ash and 10% to 15% CSF are good enough to give marginally higher compressive strengths. The optimum percentages of the mineral admixtures are 30% to 40% of fly ash and 10% to 15% of CSF for impact strength.

Tables and Graphs Cube compression results are shown in tables 2 and 3 for different combinations of M60 and M80 mixes at the age of 28 days. Compressive strength results of cylinder specimens after conducting the impact are shown in table.4 for typical M60 mix at the age of 28 days. Figs. 3 and 4 show the variation of compressive strength for various combinations of typical M60 mix after giving impact blows of 50 and 100 respectively.

Advantages of Triple Blended Concrete Mixes In the present experimental investigation, high strength concrete mixes like M60 and M80 have been studied with triple blending of cement using mineral admixtures CSF and fly ash. It has been discussed and stated that triple blending is contributing toward strength increase in compression as well as impact. Triple blending also helps in enhancing the durability properties which include acid resistance, water tightness etc. Economical concrete mixes can be produced because the mineral admixtures are available as industrial waste products.

The results are discussed herein. Influence of Flyash on the Strength Properties It is found that as fly ash% is increased the strength is getting decreased. Hence, it is clear that cement replacement by flyash should be limited to certain percentage which is not more than 40%. To compensate the loss of strength CSF is also employed in the triple blended mixes. However it can be stated that fly ash does not affect the impact strength.

Applications of Concrete Mixes with Triple Blending

Influence of CSF on the Strength Properties

Triple blended high concrete mixes could serve as high performance concrete in applications like rigid pavements heavy floors, bridge decks etc. Triple blended concrete mixes are very useful because of their higher compressive and impact strengths.

CSF contributes in increasing the strength of concrete upto an optimum percentage of replacement of 15%. This increase occurs under both compressive and impact strengths. In triple blending along with CSF other mineral admixture like fly ash is also used. At higher fly ash % the strength gets reduced. This is compensated by the presence of CSF to a certain extent.

Table 2: Cube Compressive Strength Results for M60 at 28 days

Correlation between Compression and Impact From the table.4 for M60 mix the strength of reference mix at 28 days is 63.21 N/mm2. With 15% of CSF and 0% fly ash the highest compressive strength reached is 66.24 N/mm2. This value becomes 51.65 N/mm2 and 47.80 N/mm2 after 50 and 100 blows respectively, correlating the compressive and impact strength, it can be seen that for the reference mix, there is a reduction of nearly 40% in compressive strength after 50 blows. After 100 blows this reduction is nearly 50%. For the mix with 5% CSF and 0% fly ash the reductions are 20% and 25% after 50 and 100 blows respectively. Other mixes, with 40% fly ash and 15% CSF the reduction in compressive strength is least. The reductions are 5% and 20% nearly after 50 and 100 blows respectively. It can be seen that the presence of mineral admixtures like fly ash and CSF even at higher percentages contribute towards more impact strength in the long run. Optimum Dosage of Mineral Admixtures in Triple Blending From the results of compressive strength, it can be seen that 15% CSF with 0% fly ash gives max. compressive

30

Mix Notation

% of fly ash

% of CSF

P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16

0 0 0 0 20 20 20 20 30 30 30 30 40 40 40 40

0 5 10 15 0 5 10 15 0 5 10 15 0 5 10 15

Avg. Compressive Strength N/mm2 63.21 63.86 64.93 66.24 61.80 63.45 64.12 65.68 60.81 62.65 63.94 64.53 54.13 57.31 58.24 58.61

% Increase in compressive strength over 0% 1.02 2.72 4.79 -2.23 0.37 1.43 3.90 -3.79 -0.88 1.15 2.08 -14.36 -9.33 -7.86 -7.27

Triple Blended High Strength Concrete Mixes-Studies on Compressive and Impact Strengths Table 3: Cube Compressive Strength Results for M80 at 28 days

Mix Notation

% of fly ash

% of CSF

M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M13 M14 M15 M16

0 0 0 0 20 20 20 20 30 30 30 30 40 40 40 40

0 5 10 15 0 5 10 15 0 5 10 15 0 5 10 15

Avg. Compressive Strength N/mm 71.06 71.72 73.07 75.90 64.64 66.71 67.02 68.14 58.54 59.65 61.66 62.50 53.21 54.40 55.16 56.40

% Increase in compressive strength over 0% 0.93 2.82 6.81 -9.03 -6.21 -5.68 -4.10 -17.61 -16.05 -13.22 -12.04 -25.11 -23.44 -22.37 -20.63

Fig. 1: Specimens for Impact Strength

Table 4: Results of Compressive Strength of Cylinder Specimens after Impact at the age of 28 days

Fig. 2: Impact Strength Test by Drop Hammer

Compressive % Increase in Strength after Impact Strength over Mix % of % of Impact with initial 0% Notation fly ash CSF 50 100 50 100 blows blows blows blows P1 0 0 37.28 34.0 P2 0 5 39.80 38.30 6.75 12.64 P3 0 10 47.42 40.22 27.19 18.29 P4 0 15 51.65 47.80 38.54 40.58 P5 20 0 49.50 48.75 32.77 43.38 P6 20 5 52.57 44.84 41.00 31.88 P7 20 10 54.01 49.21 44.87 44.73 P8 20 15 55.21 52.21 48.09 53.55 P9 30 0 48.65 38.65 30.49 13.65 P10 30 5 53.64 46.28 43.88 36.11 P11 30 10 53.82 46.55 44.36 36.91 P12 30 15 53.93 44.96 44.66 32.23 P13 40 0 51.85 44.25 39.08 30.14 P14 40 5 54.15 45.39 45.25 33.50 P15 40 10 54.39 50.59 45.89 48.79 P16 40 15 60.50 51.35 62.28 51.02

Fig. 3: Graph showing Impact-Cum-Compressive Strength with Initial 50 Blows for M60 Grade at 28 days

Fig. 4: Graph showing Impact-Cum-Compressive Strength with Initial 100 Blows for M60 Grade at 28 days

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

7. 30% to 40% of fly ash with 10% to 15% of CSF can be used to give optimum impact strength. 8. Triple blended concrete mixes can be advantageously used for higher compressive and impact strength. 9. Triple blended concrete mixes can be preferred for the construction of rigid pavements, runways, bridge decks, heavy floors etc. ACKNOWLEDGEMENTS The authors sincerely thank the authorities of Vasavi College of Engineering, Hyderabad, for extending the laboratory facilities in conducting the present experimental investigation.

Fig. 5: Graph showing Impact-cum-Compressive Strength with Initial 50 Blows for M80 Grade at 28 days

REFERENCES [1]

Krishna Raju. N11 – Design of concrete mix – CBS Publishers-1985.

[2]

Malhotra, V.M., 1980, “Strength and durability characteristics of concrete incorporating a pelletized blast furnace slag fly ash, silica fume, slag and other mineral by-products in concrete”, SP-79, V.2 American Concrete Institute, Detroit pp.891-922.

[3]

Meusel J.W., and Rose J.H., 1983, “Production of Granulated Blast Furnace Slag at Sparrows Point, and the workability and strength potential of concrete incorporating, the slag fly ash, silica fume and other mineral by-products in concrete”, SP-79, V.2.

CONCLUSIONS

[4]

Neville, A.M11 – Properties of Concrete English Language Book Society-1998.

Based on the experimental investigation carried out, the following conclusions are drawn:

[5]

Shetty, M.S., - Concrete Technology-S.Chand and Company Limited-2006.

1. Condensed silica fume (CSF) contribute towards strength increase of concrete upto an optimum of 15% replacement. This is true, in the cases of compressive and impact strengths.

[6]

IS 10262:2009-Indian Proportioning.

[7]

IS 516:1959-Methods of Test for Strength of Concrete.

[8]

IS 456:2000-Plane and Reinforced Concrete Indian Standard Specification.

[9]

ACI 544-2R-89-Measurement of Properties of Fibre Reinforced Concrete.

Fig. 6: Graph showing Impact-cum-Compressive Strength with Initial 100 Blows for M80 Grade at 28 days

2. As the percentage of fly ash is increased in the mix, strength gets reduced particularly after 20% and above.

Standard

Concrete

Mix

[10] IS 2386:1963-Indian Standard Methods for aggregates of Concrete.

3. In triple blending, when both CSF and fly ash are used as replacement to OPC, the combination of 20% fly ash with 10% or 15% CSF gives agreeable strengths which are marginally more that the reference mix.

[11] IS 383:1970-Indian Standard Specification on for coarse and fine aggregate for natural sources of concrete -2 revision bureau of Indian Standards NEW DELHI. [12] IS 7869 (Part 2) : Indian Standard specifications for Admixtures for concrete 1981.

4. The presence of both CSF and flyash contribute towards increase in the compressive strength after given certain number of blows of impact.

[13] IS 1344:1968 – Indian Standard specifications for Pozzolanas-Bureau of Indian Standards.

5. In the case of reference mix without CSF and fly ash, the compressive strength is reduced by 40% and nearly 50% after 50 and 100 blows respectively.

[14] IS 1344-1968, “Indian Standard specifications for pozzolonas-Bureau of Indian Standards, New Delhi, India. [15] IS 7869-Part II-1980, “Indian Standard Specifications for Admixtures in Concrete”, Bureau of Indian Standards, New Delhi, India.

6. The presence of CSF and fly ash contribute towards more impact strength.

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.33-40.

Study on Effect of MFRC for Flexural Strength and Ductility Urooj Masood1, B.L.P. Swami2 and A.K. Asthana3 1

Associate Professor, Civil Engineering, Deccan College of Engineering and Technology, Darussalam, Hyderabad. Professor, Coordinator, Research and Consultancy, Vasavi College of Engineering, Ibrahimbagh, Hyderabad. 3 Professor, Principal, Keshav Memorial College of Engineering and Technology, Narayanguda, Hyderabad. Email: [email protected], [email protected]

2

ABSTRACT The Effect of mixed Fibers is studied in MFRC. The investigation is conducted by using mixed fibers of AR-HD glass fiber and mild steel fiber with an aspect ratio (l/d) of 857 and 55 respectively. The total fiber percentages of 0.5, 0.75, 1.0 and 1.5 were taken with five varying mixed fiber percentage proportions of glass and steel fibers as 0-100, 25-75, 50-50, 75-25 and 100-0. The design mix of M25 concrete with W/C ratio of 0.5 is taken and the workability is considered between low to medium. At the age of 28 days the specimens were tested for flexure strength and ductility characteristics. It is found that the addition of mixed fiber in certain percentage to concrete is resulting in optimum strengths in flexure. The study of deflections has indicated that the presence of fibers not only has increased the flexural strength but also the deflections are controlled. The ultimate deflections recorded with various percentages are more compared to the reference specimens. The specimens with the fibers have more reserved strength even after the first crack showing the ductile behavior where as specimens without fiber have undergone a brittle failure at the instant of crack formation. The studies showed mixed fibers provide better properties in controlling cracks and higher flexure strengths than reference specimen without fiber. Keywords— Alkali Resistant, Glass Fiber, Steel Fiber, Micro Silica, Strength, Deflection, Cracking. results. The addition of steel fibers significantly improves strength properties like impact strength, toughness, tensile strength, flexural strength, fatigue strength and reduces spalling (1, 2, 3, 4 and 5). The glass fiber provides higher resistance to propagation and occurrences of early cracks sustaining higher stresses (6, 7, 8, 10 and 15).

INTRODUCTION The role of fibers are essentially to arrest any advancing cracks by applying punching forces at the rack tips, thus delaying their propagation across the matrix. The ultimate cracking strain of the composite is thus increased to many times greater than that of un-reinforced matrix. Admixtures like fly ash, silica fume, granulated blast furnace slag and metakaolin can be used for such purposes. However addition of fibers and mineral admixtures posses certain problems regarding mixing, as fibers tends to form balls and workability tends to decrease during mixing.

The present studies are aimed at investigating the mechanical properties of dual mild steel and Cem-Fil AR HD fiber concrete for different total fiber percentages with five varying mixing proportions in each total fiber percent. The study is expected to provide an optimized mixed fiber reinforced concrete for structural application. EXPERIMENTAL INVESTIGATION

Experimental studies have shown that fibers improve the mechanical properties of concrete such as flexural strength, compressive strength, tensile strength, creep behavior, impact resistance and toughness. Moreover, the addition of fibers makes the concrete more homogeneous, isotropic and a more ductile material (9, 10, 11, 12, 13 and 14). The concrete-reinforcing fibers include metallic and non metallic like steel, polypropylene and various other types. With time and stress the cracks are developed exposing internal microstructure to moisture and to various other harmful effects leading to deterioration of concrete and corrosion of reinforcement. The use of fibers in concrete leads to minimization of these cracks (16, 18). Majumdar et al. have studied the influence of glass fiber on cement matrix and have come out with encouraging

The details of materials used in the present experimental investigation are as follows. Cement OPC of 53 grade having specific gravity of 3.15. Coarse Aggregate Machine crushed well graded angular granite aggregate of nominal size 20 mm from local source are used. The specific gravity is 2.84. It is free from impurities such as dust, clay and organic matter.

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 1: Properties of Glass Fiber CEM – Fil ARC14 306 HD

Fibers AR- Glass

Density t/m3 2.6

Elastic modulus GPa 73

Tensile strength MPa 1700

Fine Aggregate

Micro Silica of M/s. Elcom Metallurgical Industries is used as partial replacement of OPC. Micro Silica is a reactive pozzolonic mineral admixture. Glass Fiber Cem – Fil ARC14 306 HD glass fiber is used. The properties are shown in Table 1. Steel Fiber Monofilament Steel fiber of 1 mm diameter & aspect ratio 55 is used. Water Locally available potable water is used.

The compressive strength of MFRC specimens with 100 percent steel fibers at 28 days age in total fiber percent of 1.5 and with no microsilica is found to be maximum and is 46.21 percent more over the strength of base reference concrete. It is observed that the compressive strength of the MFRC specimens with 1.5 percent total fibers and100 percent steel fibers and 5 percent microsilica added as partial replacement by weight of cement is 41.49 percent more over the strength of reference specimens with no fibers and is 46.93 percent more over the strength of base reference specimens without any fibers and without any microsilica.

Concrete Mix The M25 grade of concrete and quantities used per cubic meter are shown in Table 2. The water cement ratio has been fixed depending upon the compaction factor test, keeping medium workability. Table 2: Materials Required for 1cu.m. Of Concrete

M-25

Kg 400

Fine aggre gate Kg 640

Coarse aggregate

Water cement ratio

Kg 1200

0.5

No. of fibers million/kg 212

The Compressive Strength of MFRC specimens with no microsilica is found to be maximum in total fiber percentage of 1.5, when compared to specimens with other total fiber percentages of 0.5, 0.75 and 1.0. It is observed in the MFRC specimens that with increase in glass fiber percentage in a total fiber percent, the compressive strength is decreasing and it is found to be 59.15 N/mm2 at 1.5 percent total fiber with 100 glass fiber when compared to 66.85 N/mm2 in specimens with 100 percent steel fibers in the same total fiber percent of 1.5. There is an increase of 29.37 percent compressive strength in specimens at 1.5 total fiber percent with 100 percent glass fiber over the base reference specimens with no fibers. The same trend is observed in the MFRC specimens with 5 percent and 15 percent microsilica added as partial replacement by weight of cement.

Micro Silica

Cement

Length mm 12

age. At the age of 28days with 1.5 percentage fiber the compressive strength is 46.21 percent in excess over the strength of reference mix.

River sand locally available is used. The specific gravity is 2.47

Grade

Density micron 14

The compressive strength of the MFRC specimens with 15 percent microsilica added as partial replacement of cement by weight is 32.83 percent more over the reference specimens with 15 percent microsilica and no fibers. It is observed that the compressive strength of MFRC specimens with 15 percent microsilica and 1.5 percent total fiber content with 100 percent steel fiber is 51.36 percent more over the base reference specimens with no fiber and no microsilica.

Mixing – Casting – Testing As per I.S. specifications, the concrete is carefully mixed by uniformly sprinkling dual fiber in a pan mixer. The mix was cast in moulds. For each percentage of fiber sufficient number of cubes, cylinders and flexural beams were cast as per I.S. specifications for testing at the curing age of 28days. The tests were conducted for compression, flexure and deflection on the specimens using standard procedures.

The compressive strength of MFRC specimens with mixed fibers of 25 percent glass fiber and 75 percent steel fiber at 28 days age in total fiber percent of 1.5 and with no microsilica is found to be maximum and is 41.78 percent more over the strength of base reference concrete. It is observed that the compressive strength of the MFRC specimens with 5 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 100 percent steel fiber is 39.33 percent

RESULTS AND DISCUSSIONS Compressive Strength From Tables 3, 4, it is observed that with increase in fiber percentage, the compressive strength also increases with

34

Study on Effect of MFRC for Flexural Strength and Ductility

more over the strength of reference specimens with 5 percent microsilica and no fibers and is 44.69 percent more over the strength of base reference specimens without any fibers and without any microsilica.

specimens without any fibers and without any microsilica. The ultimate flexural strength is found to have an increase of 24.14 percent over the first crack strength. It is observed that the flexural strength of the MFRC specimens with 15 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 100 percent steel fiber is 70.48 percent more over the strength of reference specimens with no fibers and is 128.29 percent more over the strength of base reference specimens without any fibers and without any microsilica. Over the first crack the maximum ultimate flexural strength is found to have an increase of 13.29 percent over the first crack strength of the reference specimens and 47.39 percent more over the first crack strength of base reference specimens. It is observed that the percentage increase in the ultimate flexural strength over the first crack in the specimens with 100 percent steel fiber is maximum when compared to specimens with various mixed fiber proportions in all the total fiber percentages.

The compressive strength of the MFRC specimens with 15 percent microsilica added as partial replacement of cement by weight and 1.5 percent total fiber content with 100 percent steel fiber is 32.20 percent more over the reference specimens with 15 percent microsilica and no fibers. It is observed that the compressive strength of MFRC specimens with 15 percent microsilica is 50.65 percent more over the base reference specimens with no fiber and no microsilica. Flexural Strength From Table.5 with 1.5 percentage fiber the flexural strength is 77.7 percent in excess over the strength of reference mix. The variation of flexural strength at 28 days with various percentages of glass fiber of 0, 25, 50, 100 percentages by volume used as replacement for steel fiber in total fiber content of 0, 0.5, 0.75, 1.0 and 1.5 percentages were studied and results are presented in Table 5, 6. It is observed that as the percentage of total fiber content is increased, the flexural strength also increases and it is seen as maximum at mixed fiber proportion of 25 – 75 percentage in all the total fiber percentages. As the percentage replacement of steel fiber by glass fiber is increased and steel fiber percentage is decreased, the flexural strength goes on decreasing. The same trend is observed in all the total fiber percentages.

The flexural strength of MFRC specimens with mixed fibers of 25 percent glass fiber and 75 percent steel fiber at 28 days age in total fiber percent of 1.5 and with no microsilica is found to be maximum and is 77.75 percent more over the strength of base reference concrete and an increase in ultimate flexural strength of 24.69 percent in strength over the first crack. It is observed that the maximum flexural strength of the MFRC specimens with 5 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 25 percent glass fiber and 75 percent steel fiber is 91.08 percent more over the strength of reference specimens and 117.49 percent more over the strength of base reference specimens with no fibers and no microsilica. The ultimate flexural strength is found to have an increase of 23.86 percent over the first crack strength.

The flexural strength at first crack and ultimate failure of MFRC specimens is found to be maximum in total fiber percentage of 1.5 when compared to specimens with other total fiber percentages of 0.5, 0.75 and 1.0. It is observed in the MFRC specimens that the mixed percentage of fibers of 25 percent glass and 75 percent steel in a total fiber percent showed higher flexural strength when compared to various other mixed fiber proportions of glass fiber and steel fiber in a total fiber percent and the same is true in all the other total fiber percentages. The same trend is observed in the MFRC specimens with 5 percent and 15 percent microsilica added as partial replacement by weight of cement.

The maximum flexural strength of the MFRC specimens with 15 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 25 percent glass fiber and 75 percent steel fiber is 74.68 percent more over the strength of reference specimens and 133.91 percent more over the strength of base reference specimens with no fibers and no microsilica. Over the first crack the ultimate flexural strength is found to have an increase of 11.99 percent over the first crack strength of the reference specimens and 46.51 percent more over the first crack strength of base reference specimens.

The flexural strength of MFRC specimens with 100 percent steel fibers at 28 days age in total fiber percent of 1.5 is found to have an increase in ultimate strength of 72.14 percent over the strength of base reference concrete and an ultimate maximum increase of 25.91 percent in strength over the first crack. It is observed that the flexural strength of the MFRC specimens with 5 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 100 percent steel fiber is 84.44 percent more over the strength of reference specimens with no fibers and is 109.94 percent more over the strength of base reference

The flexural strength of MFRC specimens with 100 percent glass fibers at 28 days age in total fiber percent of 1.5 is found to have an increase in ultimate strength of 36.07 percent over the strength of base reference concrete and an ultimate maximum increase of 2.44 percent in strength over the first crack.

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

Variation of Deflections

with 5 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 100 percent steel fiber is 121.35 percent more over the deflection of reference specimens with no fibers and is 159.21 percent more over the deflection of base reference specimens without any fibers and without any microsilica.

Standard prisms of MFRC with various percentages of mixed fibers of glass and steel in total fiber percentages of 0.5, 0.75, 1.0 and 1.5 with 0, 5 and 15 percent microsilica added as partial replacement to cement has been tested for load deflection behaviour under two point loading as per the standard specifications. The procedure followed was discussed the results are presented in table.6. The variation of deflections are plotted in figs. 1 and 2. The deflections at ultimate load in MFRC specimens with no microsilica are found to be maximum in total fiber percent of 1.5 when compared to specimens with other total fiber percentages of 0.5, 0.75 and 1.0. It is observed that in the MFRC specimens with increase in glass fiber percentage in various mixed fiber percentages in a total fiber percent, the ultimate deflections are decreasing. The same trend is observed in the MFRC specimens with 5 percent and 15 percent microsilica added as partial replacement by weight of cement.

The deflection of the MFRC specimens with 15 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 100 percent steel fiber is 88.54 percent more over the reference specimens with no fibers. It is observed that the deflection of the MFRC specimens with 15 percent microsilica is 138.16 percent more over the base reference specimens with no fiber and no microsilica. The deflection of MFRC specimens at ultimate load with mixed fibers of 25 percent glass fiber and 75 percent steel fiber at 28 days age in total fiber percent of 1.5 and with no microsilica is found to be maximum and is 160.52 percent more over the deflection of base reference concrete prisms. It is observed that the deflections at ultimate load of the MFRC specimens with 5 percent microsilica added as partial replacement by weight of cement and 1.5 percent total fiber content with 25 percent glass fiber and 75 percent steel fiber is 100 percent more over the strength of reference specimens with 5 percent

The deflections in MFRC specimens at ultimate load with 100 percent steel fibers at 28 days age in total fiber percent of 1.5 and with no microsilica is found to be maximum and is 205.26 percent more over the deflection of base reference concrete prisms at ultimate load. It is observed that the deflections in the MFRC specimens

Table 3: Compressive strength of mixed fiber reinforced concrete cube at 28 days

Mixed Fiber (%)

S. No.

Total fiber (%)

Glass

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

0.0 0.5 0.5 0.5 0.5 0.5 0.75 0.75 0.75 0.75 0.75 1.0 1.0 1.0 1.0 1.0 1.5 1.5 1.5 1.5 1.5

0.0 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100

Steel

Ultimate Load (Pu) in KN

Compressive strength (fu) in N/mm2

0.0 100 75 50 25 0 100 75 50 25 0 100 75 50 25 0 100 75 50 25 0

457.2 599.0 580.2 557.3 532.5 519.7 617.8 604.2 583.6 542.5 530.1 639.8 621.4 603.0 587.7 564.9 668.5 641.2 634.6 604.3 587.5

45.72 59.90 58.02 55.73 53.25 51.97 61.78 60.42 58.36 54.25 53.01 63.98 62.14 60.03 58.77 56.49 66.85 64.12 63.46 60.43 58.75

36

Increase in compressive strength (%) ------31.01 26.90 21.89 16.47 13.67 35.13 32.15 27.65 18.66 15.94 39.94 35.91 31.89 28.54 23.56 46.21 40.24 38.80 32.17 28.49

Study on Effect of MFRC for Flexural Strength and Ductility Table 4: Compressive Strength Results of MFRC Specimens with Various Total Fiber Percentages and 15 Percent Microsilica at 28 days.

S.No.

Total fiber (%)

Total Micro silica (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

0.0 0.0 0.50 0.50 0.50 0.50 0.50 0.75 0.75 0.75 0.75 0.75 1.00 1.00 1.00 1.00 1.00 1.50 1.50 1.50 1.50 1.50

0.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0

Mixed Fiber (%) Glass

Steel

Compressive strength (N/mm2)

0.0 0.0 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100

0.0 0.0 100 75 50 25 0 100 75 50 25 0 100 75 50 25 0 100 75 50 25 0

46.30 52.76 65.91 64.73 62.57 60.15 58.19 67.94 66.26 64.83 62.82 59.42 69.22 68.86 66.99 64.14 61.34 70.08 69.75 67.73 64.39 62.71

Increase in Compressive Strength with 15 % Microsilica Reference (%) --------------24.92 22.69 18.59 14.00 10.29 28.77 25.59 22.88 19.07 12.62 31.19 30.51 26.97 21.57 16.26 32.83 32.20 28.37 22.04 18.86

Increase in Compressive Strength over the Base Reference (%) ---------13.95 42.35 39.80 35.14 29.91 25.68 46.73 43.11 40.02 35.68 28.33 49.50 48.72 44.68 38.53 32.48 51.36 50.65 46.28 39.07 35.44

flexural specimens tested have exhibited ductility characteristics. At the failure load a diagonal crack has appeared in between the loading points and the specimens have not failed suddenly. The failure is not brittle and is entirely different from that of plain concrete, where failure is brittle. The ductility characteristics exhibited by the specimens are due to the introduction of fiber in the mix. At the age of 28 days with 1.5 percentage fiber the deflection is 205.26 percent in excess over the deflection of reference mix.

microsilica and no fibers and is 134.21 percent more over the deflection of base reference specimens without any fibers and without any microsilica. The deflection of the MFRC specimens with 15 percent microsilica added as partial replacement of cement by weight and 1.5 percent total fiber content with 25 percent glass fiber and 75 percent steel fiber is 77.08 percent more over the reference specimens with 15 percent microsilica and no fibers. It is observed that the deflection of MFRC specimens with 15 percent microsilica is 123.68 percent more over the base reference prisms with no fiber and no microsilica. The deflection of MFRC specimens with 100 percent glass fibers at 28 days age in total fiber percent of 1.5 and with no microsilica is found to be maximum and is 84.21 percent more over the deflection of base reference prisms.

Cracking Characteristics Observation of specimens during Split tensile strength test shows a single crack occurring at failure along diameter of cross section without any appearance of longitudinal crack. It is observed that failure has taken place gradually with the formation of cracks. In the case of plain concrete specimens the failure is sudden and brittle. Hence it is established that the presence of fibers in the matrix has contributed towards arresting sudden crack formation.

Ductility Characteristics Beam specimens of M25 Mix with various percentages of fibers have been tested for flexural strength under two point loading as per the standard specifications. The

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 5: Ultimate Flexural Strength of MFRC Standard Prisms with and without 15 Percent Micro Silica at 28 days

Mixed Fiber (%) S. No.

Total Fiber (%)

Total Micro Silica (%)

Glass

Steel

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

0.0 0.0 0.50 0.50 0.50 0.50 0.50 0.75 0.75 0.75 0.75 0.75 1.00 1.00 1.00 1.00 1.00 1.50 1.50 1.50 1.50 1.50

0.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0

0.0 0.0 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100

0.0 0.0 100 75 50 25 0 100 75 50 25 0 100 75 50 25 0 100 75 50 25 0

Ultimate Flexural Strength (N/mm2)

11.58 15.50 20.33 20.50 18.17 16.83 16.33 22.33 22.42 20.17 18.33 17.17 24.08 24.17 21.67 20.25 19.25 26.42 27.08 24.33 23.17 20.50

4.63 6.20 8.13 8.20 7.27 6.73 6.53 8.93 8.97 8.07 7.33 6.87 9.63 9.67 8.67 8.10 7.70 10.57 10.83 9.73 9.27 8.20

24.00

glass fiber = 0%, Steel fiber = 0%

24.00

21.00

glass fiber = 0%, Steel fiber = 100%

21.00

18.00

18.00

glass fiber = 100%, Steel fiber = 0%

15.00

Load (KN)

Load (KN)

Ultimate Flexural Load (KN)

12.00 9.00 6.00

12.00

Increase in Ultimate Flexural Strength over the Base Reference (%) --------33.91 75.59 77.10 57.01 45.36 41.04 92.87 93.74 74.29 58.32 48.38 107.99 108.85 87.26 74.95 66.31 128.29 133.91 110.15 100.22 77.10

glass fiber = 0%, Steel fiber = 0% glass fiber = 25%, Steel fiber = 75%

9.00 6.00

3.00 0.00 0.00

15.00

Increase in Ultimate Flexural Strength over the Reference with 15 % Micro Silica (%) --------------31.13 32.25 17.26 8.54 5.32 44.03 44.67 30.16 18.23 10.81 55.32 55.96 39.84 30.65 24.19 70.48 74.68 56.94 49.52 32.26

3.00 3.00

6.00

9.00

12.00

0.00 0.00

15.00

Deflection (mm)

Fig. 1: Load Deflection curves of MFRC Standard Prisms at various Fiber Percentages in Total Fiber Percentage of 1.5

3.00 6.00 9.00 12.00 15.00 Deflection (mm)

Fig. 2: Load Deflection curves of MFRC Standard Prisms at various Mixed Fiber Percentages in Total Fiber Percentage of 1.5

38

Study on Effect of MFRC for Flexural Strength and Ductility Table 6: Ultimate Deflection values of Mixed Fiber Reinforced Concrete (on Standard Prisms)

Mixed Fiber (%) S. No.

Total Fiber (%)

Glass

Steel

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

0.5 0.5 0.5 0.5 0.5 0.75 0.75 0.75 0.75 0.75 1.0 1.0 1.0 1.0 1.0 1.5 1.5 1.5 1.5 1.5

0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100

100 75 50 25 0 100 75 50 25 0 100 75 50 25 0 100 75 50 25 0

0% Micro silica

5% Micro silica

15% Micro silica

117.11 107.89 75.00 59.21 52.63 139.47 127.63 106.58 94.73 63.15 184.21 155.26 148.68 130.26 73.68 205.26 160.52 151.32 146.05 84.21

78.65 73.03 42.69 29.21 16.85 96.63 78.65 52.81 35.96 19.10 113.48 93.26 87.64 61.79 28.09 121.35 100.00 78.65 65.17 35.96

47.92 38.54 20.83 12.50 2.08 66.67 57.29 26.04 22.92 5.21 81.25 69.79 51.04 36.46 14.58 88.54 77.08 54.17 44.79 16.67

Percent Increase for 5% Micro silica over the Base Reference 109.21 102.63 67.11 51.32 36.84 130.26 109.21 78.94 59.21 39.47 150.00 126.32 119.74 89.47 50.00 159.21 134.21 109.21 93.42 59.21

Percent Increase for 15% Micro silica over the Base Reference 86.84 75.00 52.63 42.10 28.94 110.53 98.68 59.21 55.26 32.89 128.94 114.47 90.79 72.36 44.74 138.16 123.68 94.73 82.89 47.37

microsilica in the same mix, the increase is 117.49% over the base reference concrete. With 15% microsilica, there is a further increase to 133.91%. Mixed fiber combination results in substantial increase in the flexural strength. Optimum percentage of microsilica used as replacement to cement contributes to further increase.

CONCLUSIONS Based on the present experimental investigation conducted and the analysis of test results, the following conclusions are drawn. 1. There is a maximum increase of 46.21% in the compressive strength of mixed fiber reinforced concrete at 28 days at 1.5% of total fiber content with 100% steel fiber over reference plain concrete. With 5% micro silica in the same mix, the increase is 46.93% over the reference concrete. With 15% micro silica, there is a further increase to 51.36%.

4. The Flexure strength of dual fiber concrete is also found to be maximum at 1.5 percent of fiber, and there is an increase of 77.75 percent for M25 grade mix at 28 days 5. The ultimate flexural strength at 1.5% total fibers and 15% microsilica in specimens with 100%steel fiber and in specimens with 100% glass fiber is found to have an increase of 47.39% and 28.46% over the first crack strength of base reference specimens.

2. The compressive strength of dual fiber concrete is maximum at 100 percent total fiber content of steel at 28 days compared to plain concrete. There is substantial increase in the compressive strength for mixed fiber combination when compare to plain concrete. As the percentage of steel fiber is reduced and glass fiber is increased, the compressive strength is getting reduced compared to that of 100 percent steel fiber in the matrix.

6. The maximum ultimate deflection capacity of MFRC standard prisms with no microsilica has been found to increase by 205.26% with 100% steel fibers in a total fiber percent of 1.5. With 5% microsilica, increase in deflection is 159.20%. With 15% microsilica this increase is 138.16%. The presence of microsilica is rendering the beam specimens more stiffer.

3. The flexural strength of MFRC standard prisms with mixed fibers of 25% glass fiber and 75% steel fiber in 1.5% total fiber content is higher and is 77.75% compared to reference plain concrete. With 5%

7. The flexural strength of dual fiber concrete is found to be maximum at 75 percent total steel fiber content in 39

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

the mixed fiber proportion at 28 days compared to plain concrete in all the total fiber percentages. As the percentage of steel fiber is reduced and glass fiber is increased, the flexural strength is getting reduced compared to that of mixed fiber percent of 25 – 75 in the matrix.

[3]

8. The ductility characteristics have improved with the addition of glass fibers. The failure is gradual compared to that of brittle failure of plain concrete. The ductility characteristics are improved by adding Steel fibers also.

[6]

[4] [5]

[7]

[8]

9. Cracks can be controlled by introducing glass fibers. Cracks have occurred and propagated gradually till the final failure. This phenomenon is true with all the percentages of glass fiber. Glass fiber also helps in controlling the shrinkage cracks. Compared glass fiber combining possessing produced.

[9]

[10]

to metallic fibers like steel, alkali resistant gives corrosion free concrete. By judiciously Glass fiber with Steel fiber, optimum FRC required strength and other properties can be

[11] [12] [13]

ACKNOWLEDGEMENT The authors wish to place on record the help provided by the managements and the academic teaching and non teaching faculties of Vasavi college of Engineering, Ibrahimbagh, and Deccan college of Engineering and Technology Darussalam, Hyderabad in the completion of this project.

[14]

[15]

[16]

REFERENCES [1] [2]

ACI 544.1R-96 reapproved 2009 Report on Fiber Reinforced Concrete ACI 544.2R-89 reapproved 2009 Measurement of Properties of Fiber Reinforced Concrete

40

ACI 544.4R-88 reapproved 2009 Design Considerations for Steel Fiber Reinforced Concrete ACI 544.3R-08 Guide for Specifying, Proportioning, and Production of Fiber-Reinforced Concrete ACI 544.5R-10 Report on the Physical Properties and Durability of Fiber-Reinforced Concrete ACI 549.3R-09 Report on Glass Fiber-Reinforced Concrete Premix D. D. Theodora kopoulos Creep Characteristics of Glass Reinforced Cement Under Flexural Loading Cement & Concrete Composites 17 (1995) 261-219 GRCA 2nd edition Specification for the manufacture, curing and testing of GRC products. 2006. Heurik Strang, Victor C Li. 2004. Classification of Fiber Reinforced Cementitious Materials for Structural Applications 6th Rilem symposium on FRC, 20–22 Sep. Varenna, Italy, P.P 197 – 218. Majumdar A. J., Laws V. 1991. Building Research Establishment book on Glass fibre reinforced cement 2nd ed. Oxford; Boston: BSP Professional. IS 456 : 2000 Plain and reinforced concrete - code of practice IS : 516 – 1959 Methods of tests for strength of concrete N. Banthia, N. Nandakumar Crack growth resistance of hybrid fiber reinforced cement composites Cement & Concrete Composites 25(2003)3–9 R.I. Gilbert Shrinkage, Cracking and Deflection the Serviceability of Concrete Structures Electronic Journal of Structural Engineering, 1 ( 2001) Saint Gobain Vetrotex, Cem – Fil. 2002. Why Alkaline Resistant Glass Fibers. In Technical data sheets. www.cem-fil.com Sivakumar. A and Santhanam Manu. 2007. Mechanical Properties of High Strength Concrete Reinforced with Metallic and Non-Metallic Fibers. Cement and Concrete Composites (29) pp. 603–608.

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.41-48.

Effect of Fly Ash Addition on Properties of Concrete with Portland Pozzolana Cement A. Chandrashekar1, P.D. Maneeth2, B.S. Mantesh3 and Nausha4 1 HOD & Professor, 2Assistant Professor, 3,4U.G Student Department of Civil Engineering, K.V.G College of Engineering. Kurungibhag, Sullia, Karnataka, India. Email: [email protected], [email protected]

ABSTRACT Fly ash is a waste material generated from thermal power plants which are responsible for 2/3rd of total electricity generation in India. Safe disposal of fly ash is a cause of concern for power industry. Waste utilization is one of the main methods employed in the case of fly ash disposal. However, it is in very small quantity compared to its production. The chemical composition of fly ash made it useful material in the production of cement and concrete. Portland pozzolana cement is one such cement produced using this waste material. In this study, the amount of fly ash which can be further added to the Portland pozzolana cement as an extra ingredient was investigated. The control mix of M30 was considered for the comparative study. PPC has been partially replaced by fly ash in the ratio 5%, 10%, 15%, 20% and 25% by weight of cement. Slump test and compaction factor were carried out to know the workability of concrete. Mechanical strength properties such as compressive, split tensile and flexural strength were evaluated at different ages and compared. The results are quite promising to use additional fly ash. Keywords— Pozzolana cement, fly ash, slump, mechanical strength, waste utilization. impurities are carried away by the flue gas in the form of ash. The molten ash is cooled rapidly and solidifies as spherical, glassy particles. Fly ash particles range in diameter from 30 min 1, there is less probability of failure (pf 0.5 implies that the original phenomenon value may be a member of the set.

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As the fuzzification values go below 0.5, it is less likely that the original phenomenon's value is a member of the set; the values may not be part of the set.

dissolved oxygen, pH, BOD and suspended solids. Finally, fuzzy inference systems similar to the one described here were applied by Jinturkar et al. (2010) to assess the quality of an Indian aquifer and by Lermontov et al. (2009) to express the water quality in a Brazilian watershed. This FQI is based on lake water parameters. Fuzzification consists of translating numerical data into the degree of membership (DOM) with respect to a set of predefined functions, here labeled low, medium, and high. The fuzzy inference consists of a set of logical rules (Ri : i ¼ 1; 2; ::: n) where Ri : If {DO is DOi and TSS is TSSi and BOD is BODi} Antecedents then {FQI is FQIi};

(1)

Consequent

Fig. 4: Fuzzy membership function diagram (Gaussian).

Universe of discourse (a range of all possible values considered as fuzzy system input) is taken as all possible valves of environmental parameters taken in to consideration and the fuzzy sets (µF(x) - a function from the reference set X to the unit interval) of corresponding parameters are recorded such that µ : X  [0,1].The centre of a fuzzy set F is taken as the point (or points) at which µF(u) achieves its maximum value. The fig: 5(D) is a risk map representing fuzzy classified pH data in which darker the shade, the basic the pH of water is, and the lighter the shade the more acidic the pH of water is (White colour means Acidic and black implies alkaline). FUZZY QUALITY INDEX (FQI) Synthetic environmental indicators based on fuzzy logic were preferred by Ganoulis (1994) for the ability to deal with information imprecision and the merit of reducing the data dimensionality. Later Chang et al. (2001) proposed a water quality index based on fuzzy clustering (Bezdek 1981) and a fuzzy similarity measure based on

in which the composition of the antecedents (Say Dissolved oxygen, Total suspended solids, Biochemical oxygen demand) implies the consequent, defined in an arbitrary range FQIi = Ii where i= [1; 2; 3; 4; 5] (Say) with 1 representing the worst quality and 5 the best. The inference systems is composed of a finite number of tabulated fuzzy rules, selected after testing many combinations and discarding the illogical ones. Finally, the FQI is obtained by weighted average defuzzification method. According to the weight values and the degree of membership for fuzzy output, the crisp value of output i.e., defuzzified output FQI is determined by the following formula ∑

(

)

∑ where each FQIi is weighted by the consequent DOM i.e., FQIi is the fuzzy output weighted value for output

Fig. 5: Image Showing (A)Sample collection points, (B)pH Analysis by GIS, (C)Reclassified Zones of pH, (D)Risk assessment map (Fuzzy classified pH data).

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Fuzzy Based Approach of Water Quality Assessment in Hussain Sagar Lake

singleton i; Vi resulting from the product composition of the antecedents in each instance of Equation (1), i.e.,

Based on the information obtained from the simulation, authorities and decision makers can design optimal strategy in which sampling stations, and experimental analysis costs can be reduced.

The three current quality values are fuzzified by comparing the current value to the three memberships (low; moderate; high) and the resulting degrees of membership enter the inference systems of Table 3. The subsequent defuzzification yields the FQI.

Future work will be aimed at extending the model validity by adding more quality variables, improving the rule base, expanding the paradigm of the scenarios, Extending the fuzzy logic model parameter rankings by sensitivity analysis and comparing with the Analytical Hierarchy process.

Table 3: Inference rules defining the FQI

Antecedents If {(DO is DOM) and (TSS is TSSL) and (BOD is BODL)} If {(DO is DOM) and (TSS is TSSM) and (BOD is BODL)} If {(DO is DOL) and (TSS is TSSM) and (BOD is BODL)} If {(DO is DOL) and (TSS is TSSH) and (BOD is BODL)} If {(DO is DOM) and (TSS is TSSH) and (BOD is BODL)} If {(DO is DOL) and (TSS is TSSM) and (BOD is BODM)} If {(DO is DOL) and (TSS is TSSH) and (BOD is BODM)} If {(DO is DOM) and (TSS is TSSM) and (BOD is BODM)} If {(DO is DOH) and (TSS is TSSM) and (BOD is BODM)} If {(DO is DOH) and (TSS is not TSSL) and (BOD is BODL)}

Consequent

REFERENCES

then I is I5

[1]

then I is I4 then I is I2

[2]

then I is I1 [3]

then I is I3 then I is I2

[4]

then I is I1

[5]

then I is I3 [6]

then I is I3 then I is I2

CONCLUSIONS

[7]

This paper has presented a preliminary study for Hussain sagar lake restoration. The exercise consisted of three parts: the synthesis of the input time-series by creating a multi layer geospatial database of hussain sagar lake in GIS environment, the structuring of the free surface water of lake in GIS model and the defining of a quality index based on fuzzy logic to describe the lake water quality. The hypothesis was that the multiple data layers could be combined using fuzzy logic knowledge based analysis to delineate the subwatersheds at high risk for pollution from 3 categories physical, chemical and Biological. The simulation show that the lake water is moderately polluted and can be indeed improved by changing the quality of the water received from the drainage channels (Nalas). The FQI proved adequate to describe the water quality and to compare several scenarios, showing that the mid-spring tomid-autumn period is the most critical and confirming, with its small variations, that the lake is robust enough to withstand significant load fluctuations.

[8] [9]

[10] [11] [12] [13]

[14]

205

Jinturkar, A. M., Deshmukh, S. S., Agarkar, S. V.&Chavhan, G. R. 2010 Determination of water quality index by fuzzy logic approach: a case of ground water in an Indian town. Water Science and Technology 61 (8), 1987–1994. Lermontov, A., Yokoyama, L., Lermontov, M. & Soares Machado, M. A. 2009 River quality analysis using fuzzy water quality index: Ribeira do Iguape river watershed, Brazil. Ecological Indicators 9 (6), 1188–1197. Chang, N. B., Chen, H.W.&Ning, S. K. 2001 Identification of river water quality using the fuzzy synthetic evaluation approach. Journal of Environmental Management 63 (3), 293–305. Ganoulis, J. 1994 Engineering Risk Analysis of Water Pollution. WILEY-VCH, Weinheim, pp. 306. Bezdek, J. C. 1981 Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York, pp. 256. A Geographic Information System-based Fuzzy Logic Approach to Modeling Non-Point Source Pollution Critical Areas in the Verde Watershed, Arizona by Dr.Stuart E. Marsh, Professor of Arid Lands Resource Sciences and Christian Will Black School of Natural Resources the University of Arizona, U.S.A. Ross T.J., Hassanein H., ALI A.N.,: Fuzzy logic with engineering applications: design and stability analysis. 3rd ed. Chichester (Royaume Uni): Wiley, 2010, xxvii, 275 p. ISBN 978-047-0748-510. P.Sudha Rani TH 614.7: S94E (2004), Environmental monitoring of Hussain sagar lake water, Hyd. Krishna Kumar TH 591.5: K92E (1979), An ecological analysis of integration of ciliate protozoa and water quality fluctuations in lake hussain sagar consequent influx of industrial effluent, OU, Hyd. Applying fuzzy logic to overlay rasters, esri – ArcGIS Resources (http://resources.arcgis.com). Executive Engineers of BPPA and APPCB, Hyd, A.P., India. Basic principles of Fuzzy logic, Vydáno dne 01. 08. 2012 (5814 přečtení). Kaehler S.D.,: Fuzzy Logic Tutorial. Seattle Robotics Society [online]. 1998. ed. [cit. 2012-08-22]. Avaible at: http://www.seattlerobotics.org/encoder/mar98/fuz/flindex. html. “Fuzzy Logic”. Stanford Encyclopedia of Philosophy. Stanford University. 2006-07-23. Retrieved 2008-09-30

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.206-209.

Automatic Cleaning of Drainage & Production of Biogas, Electricity, Biomanure P. Ramu1 and U. Ramesh2 1

Civil Engineering Department, 2Rajiv Gandhi University of Knowledge Technologies – IIIT Email: [email protected]

ABSTRACT In present era water sources are drastically decreasing, there is no abundant source to meet the present demand of water; So we should adopt a better result yielding procedures that reduce the cost of construction & maintenance. so the main aim is to construct a automatic drainage cleaning system this phenomena includes by finding out supply of water to a urban area and finding out the Runoff and by providing better elevation design to automatically clean the waste water Instead of solely depending upon fossil fuels to produce biogas, we can go for production of environmental friendly Biogas from the drainage waste, collected from the various sources of drainage water and solid waste (except plastic). In addition to above automatic cleaning drainage system where the total waste water flow is very high, by using Microbial Fuel Cells in Aerobic and Anaerobic biological system and can be produce the electricity. we can make use of Biomanure as fertilizers which has abundant essential nutrients like nitrogen, phosphorous, potassium. It will increase soil fertility so that high yielding of the crops can be possible and it can accommodate nation’s food scarcity. Our theoretical study gives the new proposal for cleaning drainage and various outputs from the resultants. Keywords— Drainage Cleaning, Ductility mechanism, Electricity, Microbial Fuel Cells, Biogas and Biomanure. DRAINAGE DESIGNING: (Refer Photograph 1)

Surface Run-Off Coefficient (C)

Catchment Areas (Assuming Area Data)

 Coefficient of Bituminous Road (C1) = 0.95

 Flexible Pavement Road and Shoulders

 Coefficient of Build up area (C2) = 0.8

 Length of the Area = 3km

 Coefficient of Grass (C3) = 0.1

 Width of the area = 10.5 m (2lanes+shoulders)

 Coefficient of Gravel surface = 0.35

 Area = Length* Width

Weighted value of Run-off coefficient

= 3*10.5

C = ((C1A1) + (C2A2) + (C3A3)) / (A1+A2+A3) 2

=. 0315 km

Area of Land on other side drains (Build up area) = 850 hectares = 8.5 km2 Area covered with build-up area another side

= 1000 hectares = 10 km2

Area covered with grass

= 80 hectares = 0.8 km2

Total Catchment area

= 19.3315 km2

C=((0.95*0.315)+(0.8*18.53) +(0.1*0.8))/(0.315+18.53+0.8) C = 0.773901204 The Run-off Coefficient C = 0.773901204 Peak Flow (Q) = 0.278*C*I*A Where Q = Quantity of Rain water surface run-off in m3/sec C = Surface Run-off Coefficient I = Maximum Rainfall Intensity in mm/hour A = Size of Surface Area to be drained in km2 C= 0.773901204 I = 1094 mm/hour 206

Automatic Cleaning of Drainage & Production of Biogas, Electricity, Biomanure

A = 19.3315 km2 Here taking data from Average Rainfall Intensity of Coastal Andhra If Telangana = 961mm; Rayalaseema = 680 mm

The rectangular shape requires less space but needs to be lined with rock or concrete to maintain its shape. This shape is often used in urban areas where there is limited space for the drainage. Trapezoid shaped side drain carries a high flow capacity and by carefully selecting the right gradients for its side slopes, will resist erosion.

Q = 0.278*0.773901204*1094*19.33151 = (4550.021184308) / (60*60) = 1.263894*1000 = 1263.894 m3/sec Quantity of Rain water Surface run-off Q = 1263.894 m3/Sec Drainage Design Q = A*V Where Q = Quantity of Rain water surface runoff in m3/sec

Fig. 3: Road side drainage

A = Cross section area in m2 V = Velocity of flow in m/sec Velocity of flow for lined Structure = 1.5 m/sec Fig. 4: Super passage truff drain

1) A = Q / V = 1263.894 / 1.5 = 842.596 m2 Consider the Trapezoidal Section

Calculation 842.596 = 0.5(42+2D) d 842.596 = 21d + d2 d2 + 21d – 842.596 = 0 d = 20.36 Formula: - x=-b± (root (b2-4ac))/2 So T = 21+ 2d T = 21+2*20.36 T = 61.730m Slope = 1:1 b = 21m

Fig. 1: Road side drain

My proposal is after designing the above we have to identify the Highest and Lowest Elevations of the area. Based on that providing above design values at highest elevation and increase the depth (2cm) every 20m reduced level up to lower elevation point. Here we are adopting Super passage truff model drainage to the road side drainage because of the total sewage going under trapezoidal section. If rain is falling then the availability of water in the road is go to plant by using rectangular drainage (above the trapezoidal). Construct one plant at lower elevation point why because the total waste collected by using mechanical device. After receiving the waste we have to produce Electricity and Biogas, after producing this some waste will remaining in plant that is called Bio manure.

Fig. 2: Diff cross sections of road

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

PROPOSED AUTOMATIC CLEANING OF MECHANICAL DEVICE Here we are applying Ductility Machine Mechanism for Cleaning Drainage. See below Ductility Machine diagram

Photo 2: Proposed Mechanism for Drainage cleaning

ELECTRICITY PRODUCTION FROM WASTE WATER Microbial Fuel Cell divides into 2 hands i.e. 1) Aerobic 2) Anaerobic cells Aerobic and Anaerobic chamber:-

Bio manure— Now a days, synthetic/artificial fertilizers have become an integrated part of agriculture. These artificial fertilizers increased the fertility and now able to create their own identity. These fertilizers are indirectly causing a great havoc. According to an economic survey of 2008-09, the usage has been increased from 05 kg/hectare in 1951-52 to 117.07 kg/hectare in 2007-08. There is a false assumption that, more the usage of fertilizer more is the yield. This excessive usage results in pollution of ground water, decrease in fertility of soil, having a lot of impact on humans due to accumulation of chemicals in food material, ground water pollution leads to health hazards, a better alternative has been suggesting by the scientists, to used natural fertilizers like dug, waste obtained from animal farming, discards from bio-gas plant, vermin compost instead of that use of these natural organic fertilizers helps in preserving the rhizosphere of the environment of all, the bio-gas manure has proven to be outstanding, it comprises of N, P, K nutrients in higher concentration. Also includes 144ppm Zn, 188ppm Mn, and 3550ppm Fe, 28ppm Cu. It increases the fertility of soil and helps in better yields of crop. 20% nitrogen is present in biogas manure in form of ammonia. High nutrients present in bio-gas manure, facilitate the required supply of air to roots of plants and sieves strength, there by implying better yield. It also doesn’t any sort of foul odor as a result; it doesn’t facilitate the growth of insects. Natural fertilizers have been classified into two categories i.e., 1) Bulky organic fertilizers— which includes farm hard manures, wastes from bio-gas plant, varmi compost, human wastes, compost, sludge etc.,

i) The bacteria on the anode decompose organic matter and free H+ ions and electrons ii) The electrons flow from the bacteria to the anode. Sometimes assisted by a mediator molecule. iii) Electrons flows up from the anode through a wire and onto the cathode while flowing through the wire an electrical current is generated that can be used to perform work. iv) H+ ions flow through the semi-permeable membrane to cathode this process is driven by the electrochemical gradient resulting from the high concentration of H+ ions near the anode v) The electrons from the cathode combine with dissolved O2 and the H+ ions to form pure H20 Biogas— sewage coming from the drainage, in this sewage containing raw water, mud, plastics, vegetable waste and industrial wastes etc., the electricity producing from raw water. So that the remaining wastes whatever coming from the drainage that contains Methane so we can produce Biogas.

2) Green manure crops— includes sesbeeniya, sunhemp, dhaincha etc. it means plants are grown in fields and their organic matter is mixed along with soil, before going for a new crop if a result the nutrients and organic matter is restored to the soil which helps in increase in fertility of soil. Varmi compost includes the usage of worm which feeds on organic matter and helps in decomposing them and providing nutrient value for the soil. Varmi compost constitutes N, P, K, 0.16% Zn, 0.03% Cu, 1.38% Fe. Varmi compost increases the water retaining capacity of soil and facilitates the air supply for plant. Bio-gas manure obtained contains 92-94% humidity. It strengthens the yielding capacity of soil. Bio-gas manure is especially useful for growth of gardening plants, aquatic form etc. excessive use of chemical fertilizers results in the extension of micro flora present in soil. As a result the ground water pollutes. Bio manure proved itself in mushroom culture and fish farming. Bio manure is of three types liquid, semi dry and dry. Use of bio manure in fish ponds helps in healthy growth of fishes. Increases the immunity towards bacterial diseases. From 30-40% to 95% bio manure usage in mushroom culture gave good results. It makes the growth of mushrooms 3-4 days faster than normal. It

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Automatic Cleaning of Drainage & Production of Biogas, Electricity, Biomanure

increases the yield by 19-26% than normal. It can also be used in horticulture, kitchen gardens and in growth of fruit plants.

REFERENCES [1] [2] [3]

Photo 1: Prototype model

209

Design of Road side Drainage Project Report by Ordinary Diploma in Transportation Engineering Microbial Fuel Cells: Generating Power from Waste by Justin Mercer Biomanure from Vijeta competitions magazine (September 1-15, 2011)

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.210-213.

Pollution Impact Assessment in Hussain Sagar Lake P. Raja Sekhar1, G. Rakesh Kumar2 and G. Shiva Kumar3 1 Associate Professor, 2Student, 3Student Department of Civil Engineering, University college of Engineering (Autonomous), Osmania University, Hyderbad.

ABSTRACT The Numerical Model include water quality modelling by use of geostatistical modelling techniques to understand the spatial scales of dynamics in a watershed. This model is “a GIS-based watershed load model” and is basically a mass transport model (Transport and fate model) [which uses results of hydrodymanic circulation model] allows one to simulate parameters governing water quality like nitrogen, phosphorus loads discharged to the lake from the surrounding watershed or from influent primary stream system (Nalas). Results from this simulation are expected to yield a satisfactory correspondence between simulated and measured water parameters, enables watershed managers to prioritize effective management alternatives for protecting the water quality and in determining water quality parameters at any anonymous point on the surface. Applicability of this model is illustrated through a case study for The Hussain sagar lake, Hyderabad. Keywords— Numerical Model, ARCGIS Mapping, Water Characteristics, Data Sampling. INTRODUCTION The development of water quality models has reached an extremely important stage. Clean water is becoming more and more precious, and although it is known that in absolute terms there is no 'clean water', in the management of water quality, we are trying to reduce the level of water pollution at the lowest possible cost. To achieve this goal, We perform a lot of numerical simulations to find out the best trade-off management solution. The final goal of using water quality management models is to simulate the consequences of different measures that can be taken to improve the water quality, and then to determine the measure which is optimal in both economical and environmental sense. Another advantage of water quality models is that we can simulate different, even not quite well known, processes and the response of a physical system to certain forcing. By comparing the results of such simulations with field measurements and observations we can better understand physical, biological and chemical processes and find more accurate mathematical descriptions of these processes. long-term continuous monitoring is not currently being conducted due to high costs. Therefore, there is a need for an alternate tool such as a basin-scale hydrologic/water quality model that is capable of predicting the effects of land management with reasonable level of accuracy. It is very important that the right choice and use of numerical models can reduce to a minimum the number of necessary usually very expensive - field measurements. The Numerical water quality model is a complete

integrated model for the simulation of water quality processes and transport, dispersion and the growth or decay processes of the relevant quantity (i.e. of a contaminant), through interaction with the biochemical processes. The expression quantity or contaminant will be used for all the quantities whose mass transport is of interest. Water Quality models can be zero-dimensional (usually called compartment models), where complete mixing of all quantities inside the 'compartment' is assumed; onedimensional, where subsequent connection of compartments is made (typically along a river reach); or two- or three-dimensional (2D, 3D) models. As the transport and dispersion of water parameters are considered on lake surface only 2D model will be discussed in this paper. GEOGRAPHIC INFORMATION SYSTEM GIS proving to be an effective tool for numerical models offers distributed parameter and continuous time simulation with flexible watershed configuration, interbasin water transfer, and lake water quality simulation capabilities. It has been proven to be an excellent tool to aggregate and organize input data for distributed parameter hydrologic/water quality models. A geographic information system (GIS) is a computerized database management system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data and display of spatial (e.g. locationally defined) data. It digitally creates and “manipulates”

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spatial areas that may be jurisdictional, purpose, or application-oriented. A GIS can be divided into five components: People, Data, Hardware, Software, and Procedures. All of these components need to be in balance for the system to be successful. No one part can run without the other. There are several things to consider before acquiring geographic data. It is crucial to check the quality of the data before obtaining it. Errors in the data set can add many unpleasant and costly hours to implementing a GIS and the results and conclusions of the GIS analysis most likely will be wrong. Spatial modeling represents the structure and distribution of features in geographical space. In order to model spatial processes, the interaction between these features must be considered. There are several types of spatial data models including: vector, raster, surface, and network (Burrough, 1998). The vector data model is a method of storing and representing data on an X,Y Cartesian plane. A coordinate and an equation defining the curvature of each feature is stored for both the beginning and the end point of each feature. The building block of the vector structure is the point; lines and areas are composed of a series of points in a specific order that gives the object direction (Clarke, 2001). The raster data model uses a grid composed of rows and columns to display map entities. Each cell in the grid is equivalent to one map unit or one pixel. Spatial resolution determines the precision of spatial representation by raster data. The smaller the size of the pixel implies the higher the resolution and the better the precision of spatial representation (Lo, 2002). An entity code is assigned to each cell that is connected to a separate attribute table, which provides information to the user as to what entity is present in what cell. In this model, instead of dividing the entire area into cells of equal size, only areas with specific details are broken down into smaller cells.

Fig. 1: Illustrative Mapping of a lake and its influent stream by vector and raster data models of GIS

STUDY AREA Hussain sagar lake was built in1562 A.D across a tributary of the Musi river and joins the twin cities of Hyderabad and secunderabad and adds historical aesthetic dimension to twin cities. The lake was utilized for irrigation and drinking water needs up to 1930. Hussain sagar has become the main sewage collection zone of the twin cities. As a result of heavy anthropogenic pressures such as unplanned urbanization, the entire ecosystem of Lake has changed. The water quality has deteriorated considerably and the lake has become shallow due to siltation and accumulation of plant debris. Hussain sagar Lake Characteristics:  Coordinates: 17.45ON - 78.5O E.  Total catchment area = 240 Sq. km.  Maximum water spread area of the lake = 5.7 Sq. km.  Present Water spread area @ FTL = 4.81 Sq. km.  Shore line length = 14 km.  Volume of the Lake at spill level = 27.18 Mcum.  Maximum depth of the lake is 9.75 m.  Average depth at full capacity = 5.02 m.  Full Tank Level (FTL) = 513.43 m (above MSL).  There are about 80 lakes in the catchment area of Hussainsagar Lake. SOURCES OF POLLUTION 1. Inlets and Types of pollution sources:

External Point sources include Raw sewage through nalas viz. Balkapur, Banjara, Kukatpally & Picket Nalas, Industrial effluents through Kukatpally Nala, Solid Waste Dumping in Nalas – Leading into Lake. External Non point sources include Slums, Dried Flower and Garlands – Puja material, Commercial Establishments, Immersion of Ganesh and Durga Idols, Visitors, Tourists etc. Internal sources include Nutrient rich sediments in the lake bed and Floating material on Lake Surface, Dissolved chemical solvents present in the deeper layers of lake which do not have favorable conditions to escape through outlet. 2. Outlets of Hussain sagar lake are 1)Surplus outlet opp. To Marriot, 2)Surplus outlet at Liberty.

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and adjacent land use. The most critical time period in a lake is typically during the growing season.

Fig. 2: Image showing inlets and outlets of Hussain sagar lake.

DATA SAMPLING A total of nine samples are collected at about the same time of day (at 9:30am) during each time of sampling and Sampling intervals is taken as 2 weeks. The location of the sampling points is fixed based on the location, Periodical change in water level and development of pressure around the point in the lake. During sample collection things recorded are the presence of storm water runoff pipes or culverts, types of shoreline vegetation (lawns, native vegetation, or agricultural land), Range of temperature change, Probability of shadow formation on the water surface due to adjacent structures

Fig. 3: Image showing all the nine data collection points.

Characterization of wastes is essential for an effective and economical waste management programme. It helps in the choice of treatment methods deciding the extent of treatment, assessing the beneficial uses of wastes and utilizing the waste purification capacity of natural bodies of water in a planned and controlled manner.

Table 1: Lake water characteristics sampled on 22/07/13.

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Domestic sewage comprises spent water from kitchen, bathroom, lavatory, etc and the factors which contribute to variations in characteristics of the domestic sewage are daily per capita use of water, quality of water supply and the type, condition and extent of sewerage- system, and habits of the people. Municipal sewage, which contains both domestic and industrial wastewater, may differ from place to place depending upon the type of industries and industrial establishment. ANALYSIS BY GIS - EXPERIMENTATION

Fig. 5: Datasets Included

Layers along with their properties, Datasets are included into the software and the results obtained are in the form of a graph for the water parameters.

From the point samples (measurements), you will produce two continuous surfaces (maps) predicting the values of lake parameters or concentrations for every location within the boundary of lake. The first map that is created will simply use all the default options to introduce you to the process of creating a surface from the sample points. The second map that produce will allow you to incorporate more of the spatial relationships that are discovered among the points. When creating this second map, the exploratory spatial data analysis (ESDA) tools are used to examine sample point data. Some of the geostatistical options that you can use to create a surface, such as removing trends and modeling spatial autocorrelation can also be done. By using the ESDA tools and working with the geostatistical parameters, one can able to create a more accurate surface.

Fig. 8: Output obtained

REFERENCES [1] [2]

[3] [4] [5] Fig. 4: Representation of experimentation procedure

The ca_lake.gdb geodatabase is to be opened which contain two datasets as

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P.Sudha Rani TH 614.7: S94E (2004), Environmental monitoring of Hussain sagar lake water, Hyd. Krishna Kumar TH 591.5: K92E (1979), An ecological analysis of integration of ciliate protozoa and water quality fluctuations in lake hussain sagar consequent influx of industrial effluent, OU, Hyd. Executive Engineers of BPPA and APPCB, Hyd, A.P., India. Peter A. Burrough, Prof. of physical geography, Principles of Geographical Information systems(1998). He, C. 2003. Integration of geographic information systems and simulation model for watershed management. Environmental Modelling & Software 18: 809-813.

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.214-216.

Analysis of Water and Assessment of its Quality for Drinking around Rajiv Gandhi International Air Port — A Case Study M. Rajasekhar1 and N. Venkat Rao2 1 Assistant Professor, 2Associate Professor Department of Civil Engineering, Vardhaman College of Engineering, Shamshabad

ABSTRACT Water is a vital natural resource in almost all activities in nature. Quality of water is considered to be important criteria for various purposes like drinking, irrigation, agriculture industrial use etc. For the safety of public health, economy and protection of various industrial processes, the water which we use should be thoroughly checked, analyzed and to be treated properly before use or distribution. The present study focused on the significance of water quality for drinking purpose. Samples have been collected near Rajiv Gandhi International Air port, Shamshabad, to check its quality in terms of essential water quality parameters like pH, Chlorides, Fluorides and dissolved solids. The paper also tries to compare the results obtained to the international water quality standards of potable water. Keywords— Water quality, Turbidity, Total Solids, Hydro geology, Potable water QUALITY OF WATER Absolutely pure water is never found in nature. Absolutely pure water is that water which contains only two parts of hydrogen and one part of Oxygen by volume and nothing else. But the water found in nature contains a number of impurities in varying amounts. The rain water which is originally pure also absorbs various gases, dust and other impurities in varying amounts. Impurities in Water and their Affect Impurities in water can be classified as follows: 1. Suspended impurities

Colloidal impurities— Very fine particles of size 1 to 500 nm of clay, micro organisms, decomposed organic matter, phosphates, fluorides and certain toxicants remain suspended in water without settling are called colloids. These are two types hydrophobic and hydrophilic, hydrophilic or water loving particles are removed by gravity but hydrophobic or water hating particles possessing no affinity for water are dependent on electrical charges for their stability in suspension. The electric charge is due to the presence of absorbed ions in the surface of the solid. These colloidal impurities are generally associated with organic matter containing bacteria and are the chief source of epidemics. METHODOLOGY

2. Dissolved impurities 3. Colloidal impurities Suspended impurities— These are solid particles suspended in water include clay, algae, fungi, organic and inorganic matter. The particles whose density is more than the water may settle down due to gravity and the particles having less density remains in continuous motion in water. Suspended impurities are macroscopic and they cause turbidity to the water. Turbidity can be identified by measuring suspended impurities in water. Dissolved impurities— water when it moves over the surface of the earth solids, liquids and gases are dissolved in natural waters. These dissolved impurities may contain organic, inorganic matter and gases etc. Carbonates and bicarbonates of calcium and magnesium cause hardness and alkalinity to the water.

The analysis of water is undertaken in order to establish the quality of water. This involves tests for determining the physical, chemical and bacteriological impurities present in the water sample. A brief description of these tests is given as follows. pH— Hydrogen ion concentration is a measure of the acidity or alkalinity of a substance. pH is determined by measurement of the electromotive force of a cell comprising an indicator immersed in the test solution and reference electrode is usually achieved by means of liquid junction, which forms a part of the reference electrode. The electro motive force of this cell is measured with pH meter. For public water supplies, pH value should be kept as close to 7 as possible. The lower value may cause tuberculation and corrosion, where as high values may

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produce incrustation, sedimentation, difficulty in chlorination and other bad effects on the human using the water.

divalent state and liberates iodine from KI equivalent to the original DO content. The liberated iodine is titrated against Na2 S2 O3 using starch as an indicator.

Total Dissolved Solids— The filterable solids can be determined either from the difference of the total solids and the total suspended solids or by using the filtrate. In water samples it can also be estimated from conductivity measurement.

Chlorides— the presence of chlorides in natural waters can be attributed to dissolution of salt deposits, discharges of effluents from chemical industries, oil well operations, sewage discharges, irrigation drainage, contamination form refuge leachates and sea water intrusion in coastal areas.

Turbidity— turbidity is a measure of the resistance of water to the passage of light through it. It is caused in the water due to the presence of suspended and colloidal matter. The degree and the intensity of turbidity is depending on the soil over which the water has passed. Turbidity is measured by shining light through a sample and measuring the degree of light penetration as measured by light detector placed in line to the original light path. This measuring technique is known as turbidimetry. Hardness— hardness is the traditional measure of the capacity of water to react with soap. In alkaline condition, EDTA reacts with Ca and Mg to form a soluble chelated complex. Ca and Mg ions develop wine red color with EBT under alkaline condition. When EDTA is added as a titrant Ca and Mg divalent ions get complexed resulting in a sharp change from wine red to blue which indicates end point of the titration. Table 1: Classification of water based on Hardness

Total Hardness as CaCo3 300

Chloride is determined in natural or slightly alkaline solution by titration with standard silver nitrate using potassium chromate as an indicator. Silver chloride is quantitatively precipitated before red silver chromate is formed. Fluorides— fluoride ions have dual significance in water supplies. High concentration of F- causes dental fluorisis. At the same time a concentration less than 0.8 mg/l results in dental caries. Hence it is essential to maintain the Fconcentration between 0.8 to 1.0 mg/l in drinking water. Under acid condition fluorides react with Zirconium SPANDS solution and the lake gets bleached due to formation ZrF6. Since bleaching is a function of fluoride ions, it is directly proportional to the concentration of fluoride. It obeys beers law in a reverse manner. The analysis of water is done as per the procedures mentioned above and assessed with WHO international standards.

Class of water Soft Moderately hard Hard Very hard

Table 2: International Standards (World Health Organization)

Parameters pH TDS (mg/l) TH as CaCo3 Cl (mg/l) So4 (mg/l) F (mg/l) DO ppm

Sulphates— sulphate ions usually occur in natural waters. Many sulphate compounds are readily soluble in water. Most of them are originate form sulphite ores, the solution of gypsum, the presence of shales, particularly those rich in organic compounds and the existence of industrial wastes. Sulfate ions are precipitated as BaSo4 in acidic media (HCL) with Barium chloride. The absorption of light by this precipitated suspension is measured by spectrophotometer at 420 nm or scattering of light.

Most desirable limits 7 - 8.5 500 100 200 200 0.8-1.0 -

Maximum allowable limits 9.2 1500 500 600 400 1.5 5 to 6 ppm

RESULTS AND DISCUSSION

Dissolved Oxygen— Oxygen dissolved in water, often referred to as DO is a very important parameter of water quality and is an index of physical and biological process going on in water. Oxygen present in sample rapidly oxidizes the dispersed divalent manganese hydroxide to its higher valency which precipitates as a brown hydrated oxide after addition of NAOH and KI. Upon acidification, manganese reverts to 215

Table 3: Experimental Values

Parameters pH TDS (mg/l) TH as CaCo3 Cl (mg/l) So4 (mg/l) F (mg/l) DO ppm

Experimental values 6.8 730 120 150 180 1.1 7

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overall quality of the water may be declared good and potable.

Table 4: Comparison of experimental results with standard desirable values.

Parameters pH TDS (mg/l) TH as CaCo3 Cl (mg/l) So4 (mg/l) F (mg/l) DO ppm

Most desirable limits 7 - 8.5 500 100 200 200 0.8-1.0 6

800 700 600 500 400 300 200 100 0

Experimental values 6.8 730 120 150 180 1.1 7

REFERENCES [1]

pH TDS (mg/l) TH as CaCo3 Cl (mg/l) So4 (mg/l) F (mg/l) Most Desirable Experimental limits values

DO ppm

Fig. 1: Comparison of experimental values with the standard values

Ground water samples were collected at various places of study area by grab sampling method. The results obtained in the experiment are tabulated below. CONCLUSION The results obtained for pH, Total Dissolved Solids, Total Hardness, Chlorides, Sulfates, Fluorides and Dissolved Oxygen are nearer to the permissible limits. But the quantity of fluorides obtained in the experiment is 1.1 mg/l, which is little bit close to the higher end. Hence

KN Duggal (2009), Elements of Environmental Engineering, S.Chand Publications. [2] National Environmental Engineering Research Institute, manual. [3] GS Birdie (2012), Water Supply and Sanitary Engineering, Dhanpat Rai Publications, New Delhi. [4] R. A. Freeze and J. A. Cherry, “Groundwater,” PrenticeHall, Englewood Cliffs, NJ, USA, 1979. [5] B. K. Kortatsi, “Hydrochemical framework of groundwater in the Ankobra Basin, Ghana,” Aquatic Geochemistry, Vol. 13, No. 1, pp. 41–74, 2007. [6] Z. Barkic, et al., “Hydrogeology and hydrogeochemistry in the alluvial aquifer of the Zagreb area (Croatia),” Materials and Geoenvironment, Vol. 50, No. 1, pp. 75–78. 2003. [7] Elkrai1, O. Kheir, L. Shu, and H. Zhenchun, “Hydrogeology of the northern Gezira area, central Sudan,” Journal of Spatial Hydrology, Vol. 4, No. 2, pp. 11, 2004. [8] N. Aghazadeh and A. A. Mogadam, “Evaluation effect of geological formation on groundwater quality in the Harzandat plain aquifer,” Symposium of Geosciences of Iran, Vol. 22, pp. 392–395, 2004. [9] M. T. Hossien, “Hydrochemical evaluation of groundwater in the Blue Nile Basin, eastern Sudan, using conventional and multivariate techniques,” Hydrogeology Journal, Vol. 12, pp. 144–158, 2004. [10] M. A. Schiavo, S. Havser, G. Gusimano, and L. Gatto, “Geochemical characterization of groundwater and submarine discharge in the south-eastern Sicily,” Continental Shelf Research, Vol. 26, No. 7, pp. 826–834, 2006. [11] T. Subramani, L. Elango, and S. R. Damodarasamy, “Groundwater quality and its suitability for drinking and agricultural use in Chithar River Basin, Tamil Nadu, India,” Environmental Geology, Vol. 47, pp. 1099–1110, 2005.

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Hydrogeochemistry of Ground Water in Jeedimetla Industrial Area, Greater Hyderabad, Andhra Pradesh G. Sharavan Kumar1, M. Anji Reddy2 and P. Madhusudhana Reddy3 1

Department of Civil Engineering, Vasavi College of Engineering, Hyderabad 2 Environmental Science & Technology, IST, JNTU, Hyderabad 3 Department of Geology, Dr. B.R. Ambedkar Open University, Hyderabad

ABSTRACT The qualitative investigations are carried out with the ground water samples collected from Jeedimetla Industrial area of Hyderabad city. The study area being an industrial area, untreated effluents are discharging in open areas. Fifty Seven ground water samples were collected from bore wells of the study area and analyzed for pH, total dissolved solids, electrical conductivity, total hardness, chloride, sulphate, bicarbonate, fluoride, potassium, sodium, calcium, magnesium and nitrates as N. The controlling factors on the ground water chemistry and criteria for water uses as discussed. The results showed that the concentrations are more than the permissible limits for drinking purposes and industrial use. The pollution of ground water may be due to large scale discharge of untreated industrial effluents. INTRODUCTION The evaluation of ground water quality is as important as quantity, since the usability of water is determined by it’s chemical characteristics. The quality of ground water depends upon the nature of rock formation, recharge and discharge conditions in the area. About one – third of solar flux absorbed by the earth’s crust is used to drive the hydrological cycle. Precipitation provides us with water supply and reserves of fresh water. Water due to precipitation reaching the ground water reservoir has to pass through, soil and weathered / fractured rock. In this process it comes in contact with several organic and inorganic substances. During its slow movement through the different layers below the ground, the percolating water reacts with number of minerals, organic and inorganic, and carries them along with it in dissolved state (Govardhan & Sudarshan, 2003). Dissolved minerals determine the usefulness of the ground water for various purposes. Presence of some substances beyond certain limits may make it unsuitable for irrigation, domestic or industrial uses. Corrosion or incrustation of tube well screens is another hazard related to ground water quality. Before using the ground water for any of the purposes, it is essential to find out possible hazardous substances, it may contain. Water quality studies bring out the concentrations of hazardous elements. Some organic components are known to be either toxic, or carcinogenic (cancer producing) or to produce odours and tastes. Chemical substances can be found either in suspension or solution. Ground water gets rid of suspended particles through natural filtration mechanism during the process of

percolation. Substances carried in the solution determine the suitability of water for various purposes. The study area is located 20 km north of Hyderabad city and form part of the survey of India topo sheets 56 K/6 and 56 K/7 and lies within latitudes 17027’ to 17033’ N and longitudes 78025’ to 278029’ E. In the study area many industries like pharmaceuticals, plastic, paints, polymers, chemical manufacturing units etc are discharging effluents either treated/ untreated in open areas causing ground water pollution. With the growing population of Qutbullapur revenue mandal together with considerable floating population from Hyderabad city and surrounding areas, the water demands have increased drastically. Small residential colonies have come into existence all around the industrial area. Thus, the ground water plays a vital role in water supply for domestic and drinking water needs of the residents. The ground water abstraction is taking place by means of dug wells and bore wells. Some areas are having piped water supply schemes. The climate is of humidity with monthly mean temperature ranges from 140C to 400C. The average annual rainfall of the area is 1033.6 millimeters (Handbook of Statistics, Ranga Reddy District, Hyderabad) and most of the rain receives from southwest mansoon, during the months of June to September. METHODOLOGY Geochemical studies have been carried out on 57 ground water samples (Fig. 1) collected from bore wells during 2005 with necessary precautions (Brown et al., 1974). The samples were collected in clean two litre polythene bottles and analyzed for chemical parameters such as pH, TDS, Ec, TH, Ca, Mg, Na, K, HCO3, Cl, F, NO3 and N

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and SO4 as per standard methods (APHA, 1985). pH and Ec are determined by Elico pH meter and Ec meter respectively. All the elements except Na and K are determined by Titration method. Na and K are determined with flame photometer. HYDROGEOLOGY The study area is underlain by crystalline formations like granites and granite gneisses of Archean Age. Granite is of both pink and grey variety and occurs as outcrops, boulders and as mounds. The depth of weathering ranges from less than a meter to 16.0 m bgl. These rocks are generally traversed by quartz veins. Three sets of joints are observed with N-S, NE-SW and NW-SE direction. Three major lineaments are present striking NNW-SSE, NW-SE and NE-SW direction. Ground water occurs under unconfined conditions in weathered and fractured zones and is being tapped predominantly by borewells. The hard crystalline formations lack primary porosity.

The occurrence and movement of ground water is usually limited to secondary porosity developed through weathering and fracturing. The aquifers are anisotropic and non-homogeneous, as such hydrogeological condictions vary widely. The depth of water varies from 4.7 to 20 m bgl. The yields of bore wells vary widely depending upon the thickness of weathered and fractured zone encountered. The total depth of bore wells ranges from 28 to 98m. The bore wells were constructed for domestic, irrigation, industrial and other purposes. Obviously the borewells drilled for domestic and drinking purposes in houses without any technical guidance. As such, in a number of wells, discharge is less and even become dry during the summer season. High yields are observed in the bore wells in some areas. HYDROGEOCHEMISTRY The chemical composition of ground water of the study area during Pre-Monsoon and Post-Monsoon respectively are shown in Table 1 and Table 2. Hydrochemical facies in the bore well zone is Na – HCO3. Generally the chemical constituents of ground water are controlled by precipitation, lithology, contact –time and prevailing physical conditions. However, the water composition may also change due to the interference of human activity. Quartz, K- feldspar and plagioclase feldspar occurs as essential minerals where as biotite, hornblende, muscovite and magnetite, occur as accessory minerals. The above minerals contribute large amounts of cations such as Ca, Mg, Na and K, HCO3 and total hardness. However, K which is derived from the rocks does not go into the ground waters because it is retained or fixed on the surface of the clay minerals by adsorption phenomenon. Exchange of Na for Ca is a natural process, especially where the clay minerals are present. Mg rich minerals are significantly present in the study area. Therefore the order of abundancy of cations is Na>Ca>Mg>k. Since the weathered zone in the study area has low permeability, it supports high concentrations of Cl along with Na. The main contribution of SO4 in ground waters in the study area comes mainly from industries. MAJOR IONS CONCENTRATION The pH of water is a very important indication of its quality and provides important information regarding types of geochemical equilibrium or solubility calculation (Hem, 1985)4. The pH of the ground water of the area during Pre-Monsoon is varying between 6.51 to 7.83 and the average pH value is 7.26. During Post-Monsoon the pH value is ranging between 7.42 to 8.9 and the average value is 8.25. The limit of pH value for drinking water is specified as 7 to 8.5 (WHO, 1983). It is observed that the ground water is alkaline in nature.

Fig. 1: Location map of the Study Area

Total dissolved solids of the ground water of the area during Pre-Monsoon vary from 192 to 4800 mg/l and 218

Hydrogeochemistry of Ground Water in Jeedimetla Industrial Area, Greater Hyderabad, Andhra Pradesh

average value is 1240 mg/l. During Post-Monsoon TDS value is ranging between 240 to 6000 mg/l and the average value is 1520 mg/l. The acceptable limit of TDS in drinking water is 500 mg/l (WHO, 1983). 90% of the samples show values above the limit. The principal ions contributing to TDS are bicarbonate, chloride, sulphate, nitrate, potassium, calcium and magnesium (EPA, 1976). The salt concentration of water is generally measured with the help of Electrical Conductivlity. The conductivity measurements provide an indication of ionic concentration. It depends upon temperature, concentration and types of ions present (Hem, 1991). The electrical conductivity of the ground water in this study during PreMonsoon vary between 368 to 8080 and during PostMonsoon it varys from 460 to 10100 conductivity in drinking water is prescribed as 1500 micro Siemens/cm (WHO, 1983). Nearly 68% of the samples of the study area exceed the limit. Chloride concentration in the ground water of the area during Pre-Monsoon is ranging from 26 to 1811 mg/l. Average concentration of Cl in drinking water is 294 mg/l. During Post-Monsoon the value range from 37 to 2587 mg/l and the average value is 414 mg/l. The standard of Cl in drinking water is 200 mg/l (WHO, 1983). It is observed that nearly 42% of ground water of the area exceeds the desirable limits. The source of Cl in ground water is due to weathering of phosphate mineral apatite and alos due to industrial effluents (Karanth, 1987). Bicarbonates in the ground water during Pre-Monsoon vary between 24 to 1140 mg/l and the average value is 264 mg/l. During Post-Monsoon the value range from 37 to 1109 mg/l and average value is 376 mg/l. Sulphate concentration in the ground water during PreMonsoon is varying from 60 to 640 mg/l and average concentration is 152 mg/l. During Post-Monsoon the value varys from 51 to 677 mg/l and average concentration is 177 mg/l. The acceptable limit in drinking water is 200 mg/l (WHO, 1983). 17% of the ground water exceeds the limit. The excess of SO2-4 concentration may be due to sulphate soil conditioners apart from industrial effluents. Flouride concentration in the ground water of the area during Pre-Monsoon varies from 0.34 to 5.82 mg/l and average fluoride concerntraion is 2.14 mg/l. During PostMonsoon the value varies from 0.35 to 6 mg/l and average value is 2.22 mg/l. The acceptable limit of content in drinking water is 1 mg/l (WHO, 1983). It is observed that 70% of the ground water exceeds the permissible limit (1.5 mg/l). Concentration of F in ground water may be due to presence of fluoride bearing minerals like apatite from the granites of the study area. Ingestion

of water with high fluoride concentration above 1.5 mg/l results in dental flourosis. Calcium concentration of the ground water during PreMonsoon is varying between 23 to 1134 mg/l and during Post-Monsoon is between 20 to 986 mg/l. The limit of calcium for drinking water is specified as 75 mg/l (ISI, 1993). It is observed that nearly 53% of the ground water exceeds the permissible limit. The concentration of calcium is due to weathering of silicate minerals like feldspars, amphiboles and pyroxenes (Karanth, 1987). The concentration of calcium is due to plagioclase feldspars present in the granites of the study area. Hardness is an important criterion for determining the usability of water for drinking and may industrial supplies. TH of ground water during Pre-Monsoon in the area ranges from 130 to 3469 mg/l and during PostMonsoon it varies from 148 to 3942 mg/l. The limit of TH for drinking water is specified as 300 mg/l (ISI 1993). Nearly 68% of the ground water exceeds the permissible limit. The hardness of water is due to the presence alkaline earths such as calcium and magnesium. Sodium concentration during Pre-Monsoon is varying between 12 to 655 mg/l and during Post-Monsoon it varies from 14 to 744 mg/l. Sodium concentration in the ground water is due to chemical weathering of plagioclase feldspars present in the granites of the area. The natural sources of anthropogenic activities, industrial effluents and sewage water have contributed to sodium concentration in ground water. Potassium in the ground water during Pre-Monsoon varies from 1 to 24 mg/l and average value is 5.11 mg/l. During Post-Monsoon the value varies from 1 to 27 mg/l and average value is 5.79 mg/l. The principal source of potassium in ground water is due to weathering of orthoclase feldspars. Nitrate as N in the ground water during Pre-Monsoon is varying from 0.94 to 115.19 mg/l and average value of NO3 as N is 21.43 mg/l. During Post-Monsoon the value range from 0.99 to 121.25 mg/l and the average value is 22.56 mg/l. The acceptable limit of drinking purposes is 10.12 mg/l. Nearly 55% of the ground water samples exceeds the acceptable limit. Magnesium in the ground water during Pre-Monsoon varies from 5 to 527 mg/l and average value is 87 mg/l. During Post-Monsoon the value range from 6 to 659 mg/l and the average value is 108.59 mg/l. The acceptable limit of Mg2+ in drinking water is 30 mg/l (WHO, 1983). Except well No.’s 1 and 8 (Papaiah yadav nagar and Ramy reddy nagar), all the well samples in the study area shows presence of Mg2+ in excess amounts.

219

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 1: Results of the Chemical Analysis of Groundwater: Major ion Concentration Jeedimetla Industrial Area, Greater Hyderabad PRE-MONSOON, 2005. All values in mg/l except pH & EC

Well No G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 G12 G13 G14 G15 G16 G17 G18 G19 G20 G21 G22 G23 G24 G25 G26 G27 G28 G29 G30 G31 G32 G33 G34 G35 G36 G37 G38 G39 G40 G41 G42

pH EC at 300C (µs/cm) 7.52 368 7.39 1600 7.35 1920 7.3 2000 7.27 2720 7.35 1120 7.13 1440 7.37 1120 7.04 1440 7.22 1520 7.48 2080 7.18 3040 6.81 2000 7.48 1520 7.22 4000 7.22 2080 7.39 800 7.45 960 6.86 2880 7.3 560 7.3 2720 7.32 2400 7.31 1040 7.3 2000 7.13 2480 7 3650 7.02 3680 7.08 2400 7.19 1760 7.22 1680 7.13 1440 7.57 1120 6.95 2080 7.48 880 7.22 2080 6.91 8080 7.3 1200 7.25 1120 7.44 960 7.66 1600 7.31 1760 7.06 1600

TDS

CL-

SO42–

192 880 1200 1264 1680 712 840 616 880 888 1280 1840 1200 910 2480 1360 384 592 1808 328 1680 1520 592 1272 1480 2340 2320 1488 1168 1008 880 680 1256 568 1344 4800 744 632 544 1000 1040 968

26 190 172 405 233 130 146 130 146 155 397 501 379 104 1018 440 128 104 440 86 172 52 78 311 259 60 906 509 310 207 190 138 293 104 311 1811 138 120 104 172 259 224

71 171 87 277 112 76 81 90 281 79 128 216 311 60 87 117 92 83 517 95 153 114 89 137 126 160 164 176 143 143 137 111 151 98 128 269 139 133 93 138 113 86

NO3– as N 1.07 6.12 27.86 13.2 22.28 13.58 0.95 4.28 4.59 55.01 15.91 55.01 9.58 7.32 13.35 68.64 4.14 28.91 32.94 3.63 115.19 18.53 1.22 6.77 13.18 12.79 12.7 12.51 13.27 13.64 1 43.57 29.55 13.45 69.61 27.99 37.13 9.94 12.87 13.02 10.44 10.4

220

HCO3–

F–

K+

Na+

Ca2+ Mg2+

24 200 456 32 1140 200 289 168 144 184 208 304 88 265 296 56 64 152 208 40 665 40 232 289 745 200 289 208 296 265 224 80 248 128 208 632 112 128 112 272 241 241

0.82 3.3 1.07 1.94 2.47 1.36 2.62 3.73 2.04 1.79 0.58 1.31 1.07 5.24 1.79 2.91 1.94 1.31 1.16 2.09 1.46 3.69 2.09 2.91 1.16 1.12 2.38 2.04 2.23 1.36 2.72 2.57 1.94 1.84 3.15 1.46 0.82 1.36 1.07 3.88 0.53 1.31

5 4 4 4 4 6 4 2 4 4 8 4 6 4 6 4 4 9 8 10 5 4 6 6 4 4 5 5 5 14 4 2 2 2 2 4 1 2 2 4 4 4

13 293 355 146 464 117 197 184 12 91 47 457 173 163 398 104 56 120 466 48 553 52 163 293 466 407 585 352 233 202 167 106 202 56 318 458 55 84 48 281 117 144

23 35 114 159 114 124 35 68 102 182 261 114 182 35 374 215 23 35 102 35 23 23 23 68 91 193 170 141 156 139 91 114 182 114 91 1134 159 114 91 68 114 136

18 34 34 110 72 34 57 5 124 67 129 115 101 52 173 129 48 62 124 34 86 38 38 96 52 86 144 96 82 48 57 38 77 38 77 288 57 38 48 38 106 67

TH as CaCO3 130 216 369 942 542 391 326 151 759 607 1084 737 803 304 720 997 260 347 759 216 434 216 216 564 412 759 976 650 607 477 434 391 911 391 520 3469 564 391 391 304 693 564

Hydrogeochemistry of Ground Water in Jeedimetla Industrial Area, Greater Hyderabad, Andhra Pradesh

G43 G44 G45 G46 G47 G48 G49 G50 G51 G52 G53 G54 G55 G56 G57

7.13 7.04 7.3 7.13 6.51 7.66 7.57 7.32 7.74 7.13 7.83 7.44 7.37 6.95 7.3

5200 3280 3280 1440 1400 1920 2040 800 1280 3300 1360 1600 1120 2080 2480

3200 1920 2024 936 888 1200 1288 512 760 2000 784 960 624 1376 1520

690 517 603 190 172 259 276 104 155 510 104 328 104 276 397

640 178 129 77 97 110 159 66 91 153 76 102 86 128 501

34.17 6.33 2.16 52.67 53.09 59.03 7.44 5.85 5.24 53.23 0.94 13.1 2.91 23.97 14.21

1120 441 456 176 152 192 320 144 168 289 272 160 200 424 160

1.65 0.34 4.66 2.52 3.15 2.72 2.09 0.82 1.65 2.67 5.82 2.33 2.67 2.67 2.38

10 24 4 2 4 2 2 13 4 4 2 8 4 4 9

158 55 655 190 71 143 261 75 59 168 127 163 137 269 331

114 431 91 136 68 159 204 91 114 170 56 91 45 238 79

527 173 57 38 115 106 48 29 77 149 72 96 38 57 149

3010 1604 434 434 650 781 607 304 672 997 434 607 260 715 781

Fig. 2 Table 2: Results of the Chemical Analysis of Groundwater: Major ion Concentration Jeedimetla Industrial Area, Greater Hyderabad POST-MONSOON - November, 2005. All values in mg/l except pH & EC

Well No G1 G2 G3 G4 G5 G6 G7 G8 G9

pH EC at 300C (µs/cm) 8.54 460 8.4 2000 8.35 2400 8.3 2500 8.26 3400 8.35 1400 8.1 1800 8.37 1400 8 1800

TDS

CL-

SO42–

240 1100 1500 1580 2100 890 1050 770 1100

37 271 246 579 333 185 209 185 209

84 203 104 330 133 90 97 84 335

NO3– as N 1.13 6.44 29.33 13.89 23.45 14.29 1 4.51 4.83

221

HCO3–

F–

K+

Na+

37 308 702 49 1047 308 444 259 222

0.85 3.4 1.1 2 2.55 1.4 2.7 3.85 2.1

6 5 4 5 4 7 4 2 4

15 333 403 166 527 133 224 209 14

Ca2+ Mg2+ 20 30 99 138 99 108 30 59 89

23 42 42 138 90 42 71 6 155

TH as CaCO3 148 246 419 912 616 444 370 172 862

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

G10 G11 G12 G13 G14 G15 G16 G17 G18 G19 G20 G21 G22 G23 G24 G25 G26 G27 G28 G29 G30 G31 G32 G33 G34 G35 G36 G37 G38 G39 G40 G41 G42 G43 G44 G45 G46 G47 G48 G49 G50 G51 G52 G53 G54 G55 G56 G57

8.2 8.5 8.16 7.74 8.5 8.2 8.2 8.4 8.47 7.8 8.3 8.3 8.32 8.31 8.3 8.1 7.96 7.98 8.05 8.17 8.2 8.1 8.6 7.9 8.5 8.2 7.85 8.3 8.24 8.45 8.7 8.31 8.02 8.1 8 8.3 8.1 7.4 8.7 8.6 8.32 8.8 8.1 8.9 8.46 8.38 7.9 8.3

1900 2600 3800 2500 1400 5000 2600 1000 1200 3600 700 3400 3000 1300 2500 3100 3500 4600 3000 2200 2100 1800 1400 2600 1100 2600 10100 1500 1400 1200 2000 2200 2000 6500 4100 4100 1800 1750 2400 2550 1000 1600 3200 1700 2000 1400 2600 3100

1110 1600 2300 1500 810 3100 1700 480 740 2260 410 2100 1900 740 1590 1850 2140 2900 1860 1460 1260 1100 850 1570 710 1680 6000 930 790 680 1250 1300 1210 4000 2400 2530 1170 1110 1500 1610 640 950 1900 980 1200 780 1720 1900

222 567 715 542 148 1454 628 123 148 628 123 246 74 111 444 370 86 1294 727 407 296 271 197 419 148 444 2587 197 172 148 246 370 320 986 739 862 271 246 370 394 148 222 493 148 468 148 394 567

94 152 257 370 51 103 139 110 99 616 113 182 136 106 163 150 191 195 209 170 170 163 132 180 117 152 320 166 158 111 164 134 102 627 212 154 92 115 131 189 79 108 182 90 121 102 152 596

57.9 16.75 57.9 10.08 7.7 14.05 72.25 4.36 30.43 34.67 3.82 121.25 19.5 1.28 7.13 13.87 13.46 13.37 13.17 13.97 14.36 1.05 45.86 31.1 14.16 73.27 29.46 39.08 10.46 13.55 13.7 10.99 10.95 35.97 6.66 2.27 55.44 55.88 62.14 7.83 6.16 5.52 56.03 0.99 13.79 3.06 25.23 14.96 222

283 320 468 136 407 456 86 99 234 320 62 1023 62 357 444 715 308 444 320 456 407 345 123 382 197 320 973 172 197 172 419 370 370 1109 678 702 271 234 296 493 222 259 444 419 246 308 653 246

1.85 0.6 1.35 1.1 5.4 1.85 3 2 1.35 1.2 2.15 1.5 3.8 2.15 3 1.2 1.15 2.45 2.1 2.3 1.4 2.8 2.65 2 1.9 3.25 1.5 0.85 1.4 1.l 4 0.55 1.35 1.7 0.35 4.8 2.6 3.25 2.8 2.15 0.85 1.7 2.75 6 2.4 2.75 2.75 2.45

4 9 5 7 5 7 5 5 10 9 11 6 5 7 7 5 5 6 6 6 16 5 2 2 2 2 5 1 2 2 5 5 5 11 27 4 2 4 2 2 15 4 5 2 9 4 4 10

103 53 519 197 185 452 118 64 136 530 55 628 59 185 333 530 462 665 400 265 229 190 121 230 64 361 521 62 95 55 319 133 164 180 62 744 216 81 163 297 85 67 191 144 185 156 306 376

158 227 99 158 30 325 187 20 30 89 30 20 20 20 59 79 168 148 123 136 121 79 99 158 99 79 986 138 99 79 59 99 118 99 375 79 118 59 138 177 79 99 148 49 79 39 207 69

84 161 144 126 65 216 161 60 78 155 42 108 48 48 120 65 108 180 120 102 60 71 48 96 48 96 360 71 48 60 48 132 84 659 216 71 48 144 132 60 36 96 186 90 120 48 71 186

690 1232 838 912 345 1700 1133 296 394 862 246 493 246 246 641 468 862 1109 739 690 542 493 444 1035 444 591 3942 641 444 444 345 788 641 2957 1823 493 493 739 887 690 345 764 1133 493 690 296 813 887

Hydrogeochemistry of Ground Water in Jeedimetla Industrial Area, Greater Hyderabad, Andhra Pradesh

Fig. 3

GIBB’S DIAGRAM The mechanism controlling the chemical relationships of ground waters based on aquifer lithology has been studied following Gibbs (1970). Three kinds of fields are recognized in the Gibb’s diagram namely atmospheric precipitation, evaporation-crystallization dominance and rock water dominance. Figure 2 and 3 presents Gibb’s plot of ground water quality data for Pre-Monsoon and Post-Monsoon of Jeedimetla Industrial area. The plots drawn with ratios of Na+K / Na+K+Ca for cation and Cl/Cl+HCO3 for anion of the water samples data plotted against relative values of total dissolved solids indicate that many wells are controlled by rock dominance category reflects the influence of the chemistry of aquifer lithology. CRITERIA FOR WATER USE

water samples are exceeding the upper limit of 500 mg/l. Hence the water causes incrustation and corrosion. CONCLUSIONS 1. The gensis of the ground water quality is mainly due to the lithology and some of the samples were influenced by the industrial activity. 2. The hydrochemistry of the samples shows that remarkable number of samples are not suitable either for driking or for industrial purposes. 3. Fluride concentrations are also showing excess levels in some samples. 4. As the quality of water are deteorating with the industrial effluents proper environmental legislations are required to be implemented in the study area. REFERENCES

For Drinking Purposes For drinking purposes, the concentration of TDS, TH, Ca, Mg, Nitrate as Na and Cl in most of the water samples are found to be greater than the desirable limits (mg/l) allowed (500,300,75,30,10 and 250 for TDS, TH, Ca, Mg, Nitrate as N and Cl respectively as per WHO, 1983 and ISI, 1993). Generally it causes distaste ness and gastrointestinal irritation. For Industrial Purposes Corrosion and incrustation are the two important chemical properties which disallow the utilization of water for industrial purposes (Johnson, 1983). The chemical constituents in the study are showed that most of the ground water samples are exceeding the upper limts (TDS 1000, HCO3 400 and TH 300) (mg/l). In case of Cl, 9

[1]

APHA. 1985. Standard method for the examination of water and wastewater, American Public health Association, American Water Works Association, Water Pollution Control Federation. Washington, D.C. 16th Edition.

[2]

Gibbs. R.J. 1970. Mechanisms controlling world water chemistry. Science. 170 : 1088 – 1090.

[3]

Brown.E, Skougstad.M.W and Fishman.M.J.1974. Methods for collections and analysis of water samples for dissolved minerals and gases. U.S. Dept. Of Interior. Book no.5.1 pp 160.

[4]

WHO 1983. Guidelines to drinking water quality World Health Organization, Geneva.

[5]

EPA. 1976. Quality criteria for water. Environmental protection Agency, Washington D.C. USA.

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development [6]

[7]

[8]

[9]

Hand book of Statistics, 2005-2006, Compiled and published by Chief Planning Officer, Ranga Reddy District, Hyderabad Hem J.D. 1985. Study and interpretation of chemical characteristics of natural water. 3rd edition. US Geological Survey Water supply. Paper 2254. pp117-120. Hem. J.D. 1991. Study and interpretation of the chemical characteristics of natural water. Scientific Publishers, Jodhpur. Govardhan Das.S.V and Sudarashan.V, 2003. Major ion

Geochemistry of fluoride rich ground water, Markapur area, prakasam district, A.P, India. Environmental Geochemistry vol.6, No. 1 & 2 : pp13-20. [10] ISI. 1993. Indian standards specification for drinking water. Indian standard institute New Delhi. [11] Karanth. K.R. 1987. Ground water Assessment, Development and Management. Tata Mc Graw Hill publishing Company Limited. New Delhi. [12] Johnson. E.E. 1983. Groundwater and wells. Jain Brothers, Udaipur (1st edn). 440 pp

224

Foundation Techniques

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.227-229.

Performance of Geotextile Reinforced Slopes of Zoned Earth Dam Sanjay W. Thakare1 and Rani B. Wath2 1 Associate Professor, Department of Civil Engg., Govt. College of Engineering, Amravati. M. Tech. (Civil- Geotech) Scholar, Department of Civil Engg., Govt. College of Engineering, Amravati (M.S)

2

ABSTRACT Earthen dam is a very huge structure built to impound water and therefore the stability of dam is of almost importance. The design of earth dams involves many considerations that must be examined before initiating detailed stability analyses. Such as geological and subsurface explorations, the earth and materials available for construction should be carefully studied. For achieving greater stability geotextile is used as reinforcement in earthen dam. This paper focuses on use of geotextile as reinforcement in earthen dam, geotextile as reinforcement is used to improve the mechanical properties of an earth structure by interacting with soil through interface shear. INTRODUCTION Dams are manmade structure build to impound water. They are build for many purposes such as irrigation, flood control, hydroelectric power generation, power generation etc. Dams may also be multifunctional surviving two or more purposes. Among the different types of dams embankment dams are most common type of dam build across the world since they are generally build of locally available earth or soil with minimum of processing. Embankment dams may be earth fill or rock fill dams, depending on primary material used in their construction. Earthen dam have been build since early times. However, early earth dams were of low heights as these were designed by empirical methods and their construction was based on experience. Developments of geotechnical engineering and new construction techniques have been helpful in creating confidence among the engineers to build dams of very large heights. Tehri dam in India is 216 m high. Earthen dams can be constructed on almost all types of foundation provided suitable measures are taken. Earthen dams more suitable than gravity dam if strong foundation at reasonable depth is not available at the site. Earthen dams are usually cheaper than gravity dam if the soil in abundant quantity is available near the construction site. Modern developments in earth moving equipments have resulted in decrease cost for earthen dams. Earthen dams are mostly rolled filled dams which consist of an embankment constructed in successive mechanically compacted layers of soils. The suitable material is transported from borrow pits to the construction site by earth moving machinery which is then spread by bulldozers to from layers of limited thickness. These layers are then thoroughly compacted at suitable water content by means of suitable rollers.

Generally a preliminary section of earth dam is selected and checked it whether it satisfied all design criteria. If does not satisfy the safety criteria, it is not modified & check again. A preliminary section of dam is selected considering various factors such as foundation condition, availability of materials, physical properties of materials, safety factors with respect to stability, method of construction etc. In the preliminary section the various parameters are decided which includes crest width, free board, upstream (U/S) & downstream (D/S) slopes, cutoff trench, d/s drainage system, central impervious core, provision of riprap etc. Various methods are available for checking the stability of slopes of earthen dam such as friction circle method, Swedish slip circle method, Janbu method, Spancer method etc. Swedish slip circle method is most commonly used method for checking stability of slopes because of its simplicity. Nowadays computer based software are also available for stability analysis of slopes such as Geostudio 2004, SAS-MCT 4.0, STABL5M, and UTEXAS3. This software’s are widely used nowadays because of simple graphical user interface because of simple graphical user interface, accuracy & speed. Also the stability problems can be analyzed using various input parameters & methods by using this software’s. The software’s gives results of analysis in the graphical form at which gives a better idea of the solution and failure mechanism if any. Using these software’s one can also analyze earth dam for slope stability, seepage analysis, seismic analysis with different conditions such as full reservoir, sudden drawdown etc. Need The conventional method of constructing embankment to a stable slope for given height or adding berms can involve considerable expenses in materials, plants,

227

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 1: Details of Parameters Study

Sr. No.

Slope

01

Downstream Slope

02

Upstream Slope

Condition Empty reservoir with and without earthquake Steady seepage with and without earthquake Empty reservoir with and without earthquake Full reservoir with and without earthquake Sudden drawdown with and without earthquake

construction time & extension to base area of embankment. While for the low heights of dams, this may not be of much concern, but for high dams there may be considerable increase in cost of dam and also the time of construction due to much flatter slope of embankment. In some cases, if the suitable construction material is not available nearby the site then there will be an additional increase in the cost due to transportation of suitable material from quarries located at greater distance. One of the solutions to this issue is to make the embankment slopes much steeper than obtained by the conventional design procedure. The slopes of embankment dam can be made steeper by following methods. i) By strengthening the slopes by providing the reinforcement in the form of anchoring and nailing. ii) By strengthening the slopes by providing the planer reinforcement such as geotextile, geogrid and metal grid. One of the primary requirements for the embankment slope is the stability of slope. Thus it is necessary that when slopes are made steeper by reinforcing them by any method, the slope should remain stable thus it becomes necessary for a civil engineer to analyse the various forces induced due to provision of reinforcement & take into account these forces in the stability analysis of slopes. The effect of provision of reinforcement in the form of anchoring & nailing for strengthening the slopes of embankment dam has been studied by few researchers & its effect on stability of slopes & economy achieved has been investigated however strengthening of slopesof embankment dam by providing horizontal layers of planer reinforcement such as geotextile and geogrid has not been investigated yet. Theme The software OASYS will be used to evaluate factor of safety for upstream and downstream slope for various conditions and will be compared with Existing design results. The various conditions of the study as shown in table no.1. LITERATURE REVIEW Ya-lin Zhu et.al. (2009)10 conducted a research to study the antiseismic measure of geogrid in high rockfill dam

Remark Changing length and spacing of geotextile layers

using elastoplastic analysis method. By studying the dynamic response of high earth rockfill dam in area of high seismicity, the concern aspects are installing geogrids in dam slope responding during strongly earthquake. Tension, permanent deformation & acceleration response are taken into account during earthquake & used as criteria evaluate the antiseismic measurement. High rockfill dam used in their study 200 m height, 916 m in length & 1:1.8 slope with u/s & d/s & completely symmetric core wall. The analysis was carried out using total stress method neglecting water load & water seepage on u/s. The uniaxial geogrid was used in construction of high earth rockfill dam & it was modeled as cable element. After analysis concluded that the level of shear strain can be reduced significantly, collapse of elements at the top of slope can be effectively controlled, horizontal permanent displacement 9near the top of the dam & downstream slope can be greatly reduced, stability of casing material can be improved at top of the dam. Srivastava Amit et.al (2011) et.al.presented a case study where the soil reinforcement technique has been used to reconstruct and stabilize the upstream slope of water impounding reservoir in Karnataka which was failed by sliding under sudden drawdown condition during rainy season. Using finite element method of analysis in the plaxis 2D software, it was demonstrated that the provision of reinforcement provides higher stability to the structure. The reinforcement used in their study was in the form of 24 mm diameter torque steel rods & length of bars varying from 5 m to 25 m. the bars were provided horizontally at spacing of 1 m & the vertical spacing between layers of reinforcement was 1.5. Tensile force mobilized in the reinforcement interacts via friction between soil & reinforcement & reducing driving forces as well as increases resisting forces. This results in improved factor of safety of section. S.P.Tatewar & L.Pawade (2012)2 studied the analysis & design of existing earth dam section of Bhimadi minor irrigation dam situated near Warud in Amravati district. Existing dam section was stable in all respect however the study was conducted to investigate the effect of various parameters such as change in berm width, strengthening the d/s & u/s slope by anchoring & nailing under different condition of stability. The slopes of dam section provided with reinforcement were changed & its effect on stability was evaluated. Also parameter of reinforcement such as length & spacing were changed to study its effect on

228

Performance of Geotextile Reinforced Slopes of Zoned Earth Dam

stability. The stability analysis was carried using Geo5 software. The models of original dam section as well as dam section with reinforced slope were developed in Geo5 software & stability analysis was carried out. Based on the study, it was concluded that, the factor of safety of stability of slopes is increased with anchoring and nailing. However, the improvement in factor of safety is continued up to certain limit. Also cost saving of 3% to 15% may be achieved using the anchoring & nailing to the slopes.

seepage condition, for upstream slope during sudden drawdown condition. The geotextile may increase the factor of safety for both slopes during construction. The geotextile may increases the factor of safety for downstream slope and upstream slope with earthquake effect.

[1]

A.B. Tewary,(1989) “Geotextiles in Earthen Dams”, International Workshops on Geotextiles, 29-39.

METHODOLOGY

[2]

i. Data of existing dam to be collected from Irrigation department.

Dr.S.P.Tatewar and Laxman N.Pawade (2012) “Stability Analysis of Bhimdi Earth Dam”,International Journal of Engineering Innovation & Research (IJEIR)” published in ISSN: 2277-5668. Volume No-1, Issue -6, and Nov- Dec. 2012.

[3]

ii. Modeling of existing earthen dam section without reinforcement in Oasys software.

Dr. G. Venkatappa Rao, “Geosynthetics” (1990), Tata McGraw Hill,New Delhi.

[4]

Engineer Manual, “Earth and rock-fill dams - general design and Construction considerations”, 1110-2-2300 (1994) pp.1- 78.

[5]

Ennio M. Palmeira, “Advances in Geosynthetics Materials and Applications for Soil Reinforcement and Environmental Protection Works”, Electronic journal of geotechnical engg.

v. Slope stability analysis of existing section with reinforcement.

[6]

Sanjay Kumar application”.

vi. Slope stability analysis of existing section with reinforcement for earthquake effect.

[7]

H. Hasani,J. Mamizadeh and H. Karimi, “Stability of Slope and Seepage Analysis in Earth Fills Dams Using Numerical Models (Case Study: Ilam DAM-Iran)”, World Applied Sciences Journal 21 (9), pp. 1398-1402, 2013.

The analysis to be carried out to calculate slope stability of zoned earthen dam without reinforcement. And when Geotextile is to be used as reinforcement in zoned earth dam to calculate slope stability of zoned earthen dam with reinforcement also calculates slope stability of zoned earthen dam with reinforcement for earthquake effect. Effect of reinforcement on slope stability of zoned earthen dam during construction.

[8]

Hamed Niroumand, “The Role of Geosynthetics in Slope Stability”, Electronic journal of geotechnical engg vol. 17(2012) pp. 2739-2748.

[9]

Sivakumar Babu G. L. and Amit Srivastava (2011) “Remediation of Upstream Slope of An Impounding Reservoir Using Soil Reinforcing Technique”, Proceedings of Indian Geotechnical Conference December-2011, Kochi (Paper No. J-307), pp. 589-592.

EXPECTED RESULTS

[10] Ya-lin Zhu, Xian-jing kong “The Anti-seismic Effect of Geogrid Reinforced on High Earth-rockfill Dams”, Electronic journal of geotechnical engg.Vol.14(2009) pp. 1-13.

REFERENCES

The method to be carried out consists of following steps for slope stability analysis of zoned earth dam.

iii. Slope stability analysis of existing section without reinforcement. iv. Modeling of existing earthen dam section with reinforcement in Oasys software.

OBJECTIVES

By using geotextile as reinforcement may increase the factor of safety for downstream slope during steady

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“Geosynthetic

and

their

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A Study on the Geotechnical Properties of Tannery Effluent on Black Cotton Soil K.V.N. Laxma Naik1, S. Bali Reddy2 and A.V. Narashima Rao3 1 Assistant Professor, P.V.P.S.T., Vijayawada, India. Research Scholar, Indian Institute of Technology Guwahati, India. 3 Formerly Professor, Department of Civil Engineering, S.V.University, Tirupathi. Email: [email protected], [email protected] 2

ABSTRACT Ground Pollution is perpetuated by humans due to many reasons. Industrial activity is necessary for the socioeconomic progress of a country, but at the same time, it generates large amount of solid and liquid wastes. Among various means available, disposal through land is simple and widely used. All types of pollution have either direct or indirect effect on soil properties. Behaviour of any contaminant in soil depends upon the Physical and Chemical properties of the contaminant as well as its interactivity with that of soil. The effect of tannery effluent on compaction, Plasticity, Swelling, Strength Characteristics and California Bearing Values of Black Cotton Soil has been presented in this paper. The soil used in this investigation falls under “SC” group as per I.S. Classification and its Differential Free Swell Index is 80% indicating very high degree of expansiveness. The tannery effluent used in this investigation is a colourless liquid and soluble in water. It has a sour taste and a pungent smell. INTRODUCTION The index and engineering properties of the ground gets modified in the vicinity of the industrial plants mainly as a result of contamination by the industrial wastes disposed. The major sources of surface and subsurface contamination are the disposal of industrial wastes and accidental spillage of chemicals during the course of industrial operations. The leakages of industrial effluent into subsoil directly affect the use and stability of the supported structure. Extensive damage to the floors, pavements and foundations of a light industrial building in Kerala State was reported by Sridharan et al. (1981). Joshi et al. (1994) reported that severe damage occurred to the interconnecting pipe of a phosphoric acid storage tank in particular and also to the adjacent buildings due to differential movements between pump and acid tank foundations of fertilizer plant in Calgary, Canada. A similar case of accidental spillage of highly concentrated caustic soda solution as a result of spillage from cracked drains in an industrial establishment in Tema, Ghana caused considerable structural damage to a light industrial building in the factory, in addition to localized subsidence of the affected area [Kumaplay & Ishola (1985)]. Therefore, it is better to start ground monitoring from the beginning of a project instead of waiting for complete failure of the ground to support human activities and then start the remedial actions.

Black cotton soils have high shrinkage and swelling characteristics. In general, these soils are very much sensitive to changes in environment. The environment includes the stress system, the chemistry of pore water in the system, the seasonal variations in ground water table and temperature variations. Hence, an attempt is made in this investigation to study the effect of Tannery effluent on the Geotechnical Properties of a black cotton soil. MATERIALS USED The soil used for this investigation is obtained from near Tirupati (India). The soil is classified as ‘SC’ as per I.S. Classification indicating that it is clayey sand. It is highly expansive as the Free Swell Index is 254.5 %. The properties of the soil are given in Table- 1. Tannery effluent is a colourless liquid and soluble in water in proportions. It has sour taste and pungent smell. The chemical properties of the effluent are shown in Table 2. PROCEDURE FOR CONTAMINATION The soil from the site is dried and the pebbles and vegetative matter present, if any, are removed by hand. It is further dried and pulverized and sieved through a sieve of 4.75 mm to eliminate gravel fraction, if any. This dried and sieved soil is stored in air – tight containers for use for contamination. The soil sample kept for contamination

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WATER CONTENT (%)

is mixed with different percentages of tannery effluent, from 0 to 100 per cent, in increments of 20 percent. The contaminated soil prepared thus is stored for a day in air tight containers for uniform distribution of tannery effluent. Table 1: Properties of Soil

S.No (a) (b) (c)

1

(a)

2

(b) 3

Property Value Atterberg Limits Liquid Limits 77% Plastic limit 29.2% Plasticity Index 47.8% Compaction Characteristics Maximum dry Unit Weight 18.48kN/m3 Optimum Moisture 13% Content Specific Gravity 2.65

90

LIQUID LIMIT

80

PLASTICITY INDEX

PLASTIC LIMIT

70 60 50 40 30 20 10 0 0

20 40 60 80 TANNERY EFFLUENT (%)

100

Fig. 1: Variation of LL, PL and PI with per cent Tannery Effluent 300

Table 2: Chemical composition of tannery effluent

Parameter Color pH Chromium chloride Sulphite Total Hardness BOD COD Suspended Solids

250

Value Dark color liquid 3.15 250 mg/l 496.3 mg/l 152.8 mg/l 520 mg/l 120 mg/lit 450 mg/lit 1200 mg/lit

200 DFSI(%)

S.No. 1. 2. 3. 4. 5. 6. 7. 8. 9.

150 100 50 0 0

TESTS CONDUCTED The following tests are conducted in the presented investigation: 1. Liquid limit tests 2. Plastic limit tests 3. Differential Free Swell Index Tests 4. Compaction Tests and 5. Unconfined Compression Test RESULTS AND DISCUSSION The effect of tannery effluent in varying proportion with soil has been studied and the variation in Liquid Limit (LL), Plastic Limit (PL) and Plasticity Index (PI) for various mixes is presented in Fig. 1. It is found that as the percentage of tannery effluent increases the LL, PL, and PI of soil mix is decreased marginally.

20 40 60 80 TANNERY EFFLUENT (%)

100

Fig. 2: Variation of DFSI with the percent Tannery Effluent (%)

The Optimum Pore- fluid Content (OPC) and Maximum Dry Unit Weight (MDU) for soil may vary with various proportions of tannery effluent. The results of the Standard Proctor’s Compaction tests for soil conducted at different percentages of tannery effluent are reported in Fig. 3. The bottom most curve corresponds to 0 % of tannery effluent followed by 20%, 40%, 60%, 80% and 100% respectively. From these curves, it is seen that the peak points are shifted towards right with per cent increase in effluent. The relationship between optimum pore fluid content and different percentages of tannery effluent is shown in Fig.4.It is found that the Optimum Pore fluid Content(OPC) increases with per cent increase of tannery effluent. The per cent decrease in OPC for 100% of tannery effluent is about 10.4%.

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22 DRY UNIT WEIGHT (kN/m3)

Undrained Cohesion with respect to different percentages of tannery effluent for various curing periods is shown in

0% EFFLUENT 20% EFFLUENT 40% EFFLUENT 60% EFFLUENT 80% EFFLUENT 100% EFFLUENT ZERO AIR VOID LINE

21 20

Fig.3.From the figure, it is observed that the strength of the soil decreases with increase in percentage of tannery effluent irrespective of curing period. The variation in Undrained Cohesion with respect to different curing periods for various percentages of tannery effluent is shown in Fig.4.From the figure it is observed that the strength of the soil decreases with increase in curing period irrespective of per cent tannery effluent. The maximum reduction in Undrained Cohesion occurs on the soil samples treated with 100% tannery effluent and cured for 15 days.

19 18 17 16 15 4

8

12

16

20

PORE FLUID CONTENT (%)

Fig. 3: Compaction Curves for different Percentages of Effluent

OPTIMUM PORE FLUID CONTENT(%)

12.6 12.4 12.2 12 11.8 11.6

Fig. 5: Variation of Undrained Cohesion with Per cent Tannery Effluent for Different curing periods

11.4 11.2 11 0

20

40

60

80

100

TANNERY EFFLUENT (%)

Fig. 4: Variation of OPC with Per cent Tannery Effluent

The variation in maximum dry unit weight with percentage of tannery effluent is shown in Fig.5. From the figure, it is seen that the maximum dry unit weight decreases slightly with the increase in percentage of tannery effluent. The percentage decrease in MDU at 100% of tannery effluent is about 6 %. Unconfined Compressive Strength test is, carried out to study the strength behaviour of soil treated with different percentages of effluents are critically discussed. The effect of curing on the strength behaviour of soil treated with different percentages of effluents is also studied. Five different curing periods are considered for the study namely 0 day, 1day, 3 days, 7 days and 15 days. The tests are conducted at the optimum pore fluid content. The effluents are varied from 20% to 100% in increment of 20%.In order to compare the results of treated soil, tests are also conducted on untreated soil. The variation in

Fig. 6: Variation of Undrained Cohesion with curing period for different percentages of tannery effluent

In general the shear strength of a soil can be considered to have three components viz: cohesion, friction and dilatancy. Cohesion in general is considered as a part of the shear strength that can be mobilized due to forces arising at particle level and is independent of the effective stress and hence, is regarded as a physico-chemical component of the shear strength. Undrained cohesion is estimated as half of the Unconfined Compressive Strength.

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Basically, two mechanisms control the undrained strength in clays, namely (a) cohesion or undrained strength is due to the net attractive forces and the mode of particle arrangement as governed by the interparticle forces, or (b) cohesion is due to the viscous shear resistance of the double layer water (Sridharan, 2002). The Undrained shear strength behaviour of kaolinitic soils is shown to be quite opposite to that observed for montmorillonitic soils under different physico-chemical environments.Concept (a) operates primarily for kaolinitic soil, and concept (b) dominates primarily for montmorillonitic soils. In general fine grained soils consist of different clay minerals with different exchangeable cations and varying ion concentration in the pore water and varying non clay size fraction. In view of this while both concepts (a) and (b) can coexist and operate simultaneously, or one of the mechanisms dominates. In the case of tannery effluent reduction in Undrained Cohesion value could be attributed to absorption of chromium ions present in the effluent. Due to its higher valence chromium ions causes decrease in double layer thicknesswhich in turn reduces the viscous resistance for the same water content under undrained condition (Sridharan, 2002). The reduction in strength of specimens with age was due to the long-term interaction between clay particles and effluent and predominant role of chromium ions in decreasing double layer thickness and viscous resistance.di

effluents generated from industrial activities are discharged either treated or untreated over the soil leading to changes in soil properties causing improvement or degradation of engineering behavior of soil. If there is an improvement in engineering behaviour of soil, there is a value addition to the industrial wastes serving three benefits of safe disposal of effluents, using as a stabiliser and return of income on it. If there is degradation of engineering behaviour of soil then solution for decontamination is to be obtained. Based on experimental study the following conclusions are drawn. If increasing tannery effluent Liquid limit and Plastic limits are decreased. Undrained Cohesion of the soil decreases with increase in percentage of Tannery Effluent irrespective of curing period. REFERENCES [1]

[2]

[3]

[4]

CONCLUSIONS The rapid growth in population and industrialization cause generation of large quantities of effluents. The bulk

233

Joshi, R.C.,Pan, X., and Lohinta, R.(1994)Volume Change in Calcareous Soils due to Phosphoric Acid Contamination, Proc.of the XIII CSMFE, New Delhi Vol:4, pp1569-1574. Kumapley, N.K. and Ishola, A.(1985)The Effect of Chemical Contamination on Soil Strength,Proc. XI ICSMFE, San Fransico.,A.A.Balkema, Rotter dam, Vol:3,pp1199- 1201. Sridharan, A., Nagaraj, T.S. and Sivapullaiah, P.V.(1981) Heaving of Soil due to Acid Contamination, ICFMFE, Stockholm,6,383-386. Sridharan, Asuri and El-Shafei, Ahmed and Miura, Norihiko (2002),“Mechanisms controlling the Undrained strength behavior of remolded Ariake marine clays”, In: Marine Georesources & Geotechnology, 20(1). 21-50.

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.234-239.

Problematic Soils and Mitigative Measures - A Review M. Nagalakshmi1, D.V. Sivasankara Reddy1, E. Anusha1 and M. Chittaranjan2 Students, 2Associate Professor, Department of Civil Engineering, Bapatla Engineering College, Bapatla

1

ABSTRACT In olden days if soil is problematic to maintain stability of structure it is simply avoided. But now-a-days due to increase in population and industrialization there is great demand for site. Hence we cannot avoid the site; we should find out the solutions to maintain stability of structures when constructed over this type of soils. In problematic soils regular pattern of design, conventional or commonly used foundations are not suitable. It requires special type of ground improvement techniques, special design and special type of foundations to counteract its effects. Hence it becomes a challenging for civil engineers particularly for geotechnical engineers to maintain stability of structures when constructed over problematic soils. After extensive research work it is observed that certain soils such as Expansive soils, Liquefiable soils, Collapsible soil, Contaminated Soils, Soils subjected to Frost heave and Frost boil, Soft ground poses several problems to Civil Engineering Structures which are constructed on them. In this paper the nature of these soils and different foundation practices adopted on these soils to counteract their effects are critically discussed. Keywords— Problematic soils-Expansive soils-Liquefiable soils-Collapsible soil-contaminated soils -Soft ground.  Collapse of buildings

INTRODUCTION The foundation of every civil engineering structure is located within the soil. Hence the stability of the structure not only depends on its effective design and quality of material used it also depends on the nature of the soil. If the soil is problematic then even though the structure is designed effectively the structure may cracks, heave, settle or in severe conditions it may collapse. Hence it is essential to know the behavior of problematic soils and suitable foundation or effective ground improvement technique to counteract the effect of problematic soil. Hence it becomes a challenging task for civil engineers particularly for geotechnical engineers to maintain stability of structures when constructed over problematic soils.

 Damages of floors and pavement  Chemical attack on foundations  Landslides  Lateral spreads TYPES OF PROBLEMATIC SOILS  Expansive soils  Liquefiable soils  Collapsible soils  Soft ground fills  Dispersive soils  Contaminated soils

PROBLEMATIC SOIL-DEFINITION

 Soils subjected to frost heave and frost boil

A soil is termed as problematic if it has undesirable engineering properties. It causes architectural and structural damages to the structures constructed over such soils.

EXPANSIVE SOILS

Problematic soils causes  Cracks in buildings  Sudden/Excessive Settlement  Tilting and Sinking of buildings

Expansive soils are those soils, which have tendency to increase in volume when water is available and decrease in volume when water is removed. These volumetric changes are due to the presence of Montmorillanite clay mineral in expansive soils. These volume changes of expansive soils cause severe damage to structures resting on it. The expansive soils of India are commonly known as Black Cotton Soils because of the colour and their property of growing Cotton.

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Mitigative Measures Under Reamed Piles— A pile which has an enlarged base at its bottom is known as under reamed pile. This type of foundation is suitable when there are alternate layers of expansive and non expansive soils.

construction is easy and is more economical when compared to other techniques. This technique uses anchor rod anchor plate made of steel.

The mechanism for this type of foundation is, the bulb portion of the under reamed piles is provided in the stable zone. During expansion of soil, the soil exerts uplift pressure on the pile and tries to lift it up but the bulbs provided in the stable zone acts an anchor and prevents the uplift of the pile there by prevents swelling of soil. Fig. 3

The mechanism for this type of foundation is, the uplift pressure due to swelling nature of expansive soil is resisted by the weight of the granular anchor pile and the friction between the pile and the soil. The uplift pressure is also resisted by the lateral swelling pressure and prevents it from lifting.

Fig. 1

Belled Piers— The pier which has enlarged base at its bottom is known as belled pier. The mechanism for this type of foundation is, the belled portion is constructed in non-expansive zone. When the soil expands it applies an upward drag on the pile. But the belled portion in the non-expansive zone acts as an anchor and counteracts the upward drag on the pile, so that the building constructed on this ground is not affected by expansive soil. Fig. 4

Soil replacement by CNS layer— In this method, expansive soil is replaced by cohesive and non-swelling soil. Lime treatment— Lime stabilization is quite effective in reducing the liquid limit and the plasticity index of the soil. Consequently, the swelling potential also reduces. Fig. 2

Raft Foundations— This type of foundation is suitable when soil is highly expansive in nature and where other foundations are not suitable. A concrete bed is laid over the entire area of construction. This does not allow the seepage of water into the soil there by prevents swelling. Granular Anchor Piles— Granular anchor pile is a new innovative technique suitable for soils having either expansive or non expansive strata at the bottom. Its

Prewetting— Before construction expansive soil is wetted by ponding at water content equal to equilibrium moisture content so that most of potential heave would occur. Compaction Control— Swelling potential of soil can be reduced if it is compacted wet of optimum water content. Compaction is effective only in cases when the probable expected heave is less than about 40mm. Prevention of Ingress of Water— In this method the swelling of expansive soil can be reduced by preventing entry of water to seep through it. It can be done by using

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Horizontal moisture barrier, Vertical moisture barrier, Sand drains, and Sub-surface sand drains.

1. The soil is cohesionless.

LIQUIFIABLE SOILS

3. The soil is saturated.

Liquefaction is phenomenon due to which water saturated loose sandy soils acts as a dense viscous fluid rather than as a solid when they are subjected to earthquake ground shaking.

2. The soil is loose. 4. There is shaking of ground of the required intensity and duration. 5. The undrained conditions developed in the soil due to its limited Permeability.

Mechanism of Liquefaction

Mitigative Measures

During an earthquake the application of cyclic shear stresses induced by the propagation of shear waves causes the loose sand to contract resulting in increasing pore water pressure. The increasing pore water pressure causes an upward flow of water to the ground surface in the form of mud sprouts or sand boils. The development of high pore water pressure due to ground shaking and upward flow of water may turn the sand into liquefied condition which has been termed as liquefaction. For this state of liquefaction the effective stress is zero. Hence the shear strength of cohesive less soil is equal to zero. The individual soil particles are released from any confinement as if the soil particles were floating in water.

Preventive measures to be taken in under to control liquefaction are i)

Providing deep foundations— The structure should be supported on deep foundations, such as Piles that extend through the liquefiable soil to the deeper strong and stable strata.

ii)

Compaction of soils— Liquefaction occurs in loose sands. By compacting the soil we can increase the relative density of the soil and the chances of liquefaction can be minimised. Compaction can be done by means of vibratory rollers, compaction piles, blasting and vibro floatation.

iii) Replacing the liquefiable soil— If the depth of the liquefiable soil is limited it can be excavated and replaced with a well compacted soil. But this method is not economical, if the depth of the liquefiable soil is large. iv)

Grouting the soil— In this method, the soil is stabilised by injecting the chemicals or cement grout into the soil. The chemical reaction between the soil and chemicals increase the cohesion consequently the shear strength of the soil.

v)

Providing stone columns— In this method a number of holes are bored into the soil deposit and later filled with gravel & stones and then compacted, thus stone columns are formed. The stone columns have high permeability and are quite effective for rapid drainage of pore water, thus the effective stress is increased. Stone columns also increase the bearing capacity of the soil.

vi)

Drainage of soil— The liquefaction hazard can be reduced to some extent by providing coarse sand blanket in the soil deposit. The dynamic pore water pressure is thus easily dissipated when water escape through these and the effective stress is increased.

Fig. 5

Liquefaction Phenomenon can be explained in terms mathematical expression as  Shear Strength, τ=c + σntanφ  Effective stress gives more realistic behavior of soil, Shear strength can be expressed as 1

τ=c + (σn-u) tanφ

1

 During the ground motion due to an earthquake, Static pore pressure may be increased by an amount udyn, then τ=c1 + (σn-(u +udyn)) tanφ1 Let us consider a situation when u +udyn= σn, then τ = c1 In cohesion less soil, c1=0, hence τ = 0. Liquefaction occurs in the following conditions

vii) Ground water pumping— The effective stress at a point increases as the water table is lowered, so that by pumping the ground water, the liquefaction can be prevented to some extent. However, this method is cost effective only when the water that is pumped can be used for municipal and industrial purposes. viii) Application of surcharge— When a surcharge load is applied to a soil deposit, the effective stress is

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Problematic Soils and Mitigative Measures - A Review

increased, thus the possibility of liquefaction can be reduced.

Pre Ponding— In this method, low dikes are constructed around the construction site and the whole site is flooded with water to cause collapse of soil before construction is started. This method is effective only when there is an impervious stratum beneath the collapsible soil to prevent seepage. Drilled piers and piles— For collapsible soils having large depths pipe ponding or precollapsing becomes difficult. In such cases foundations are extended beyond the depth of zone of possible wetting using drilled piers and piles so that damage of structures constructed over such soils can be prevented.

Fig. 6

COLLAPSIBLE SOILS In arid or semi-arid areas, temporary bonds develop between soil grains. These bonds dissolve upon wetting under pressure. This type of soil is known as collapsible soils. The temporary bonds are due to very small coating of clay or other bonding materials. Collapsible soils contain low water content and high void ratio in natural state. Sudden decrease in volume takes place when it becomes saturated. Aeolian soils for example Loess contain honey comb structure in which porous structure is maintained by water soluble bonds between soil particles. When it becomes saturated the bond between soil particles is broken and the soil mass suddenly decreases in volume causing its collapse.

Stone-Columns— In this method, holes are bored into the soil deposit and later filled with large boulders & then compacted, thus stone columns are formed. These large boulders penetrate the collapsible soil deposit and they transfer the load of structures to stable soil layers beneath the collapsible soil. Densification— Collapsible soils are densified by vibroflotation in order to increase the cohesion. This method is effective only for free-draining soils. Stabilization— Soil is stabilized by using solution of sodium silicate and calcium chloride. Due to stabilization, the collapsible soil behaves like a soft stone and resists collapse after saturation. This method is quite effective for fine sands. Control of Drainage— Potential water sources which cause wetting may be controlled by providing suitable drainage. Infiltrations wells are used for drainage. SOFT GROUND FILLS It is highly sensitive clay which has a tendency to change from a relatively stiff condition to a liquid mass when it is disturbed. It has a high water content of about 80%.

Fig. 7

Mitigative measures— Preventive measures to be taken in under to control liquefaction are Soil replacement— If the depth of the collapsible soil is limited it can be excavated and replaced with a well compacted soil. But this method is not economical, if the depth of the collapsible soil is large.

Fig. 8

Mitigative Measures Bypassing the soil— The structure should be supported on deep foundations, such as Piles that extend through the soft soil to the deeper strong and stable strata.

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Soil reinforcement— cohesion and friction of soil can be improved by providing micro piles, compaction piles etc. Grouting— Chemical grouts are introduced under pressure into the soil. Soil replacement— If the depth of the soft soil is limited it can be excavated and replaced with a hard soil, stone dust with fly-ash. Soil stabilization— soil can be stabilized by means of cement, fly-ash, lime, sodium silicate etc, in order to improve the engineering properties of soil and make it stable. CONTAMINATED SOILS Due to increase in population, industrialization huge quantities of wastes are generated. These wastes are disposed directly on to the land without any treatment. During rainy seasons the rain water mixed with wastes and creates a toxic chemical known as leachate. The leachate moves down under gravity and contaminates the site. Soil contamination decreases the engineering properties of soil. The modification of soil causes settlement or tilting or sinking or cracks and collapse of building. Hence decontamination is essential before the construction of a building. Decontamination Techniques Bio-Remediation— In this method the contaminated soil is supplemented with cultured aerobic microorganisms. The pollutants are degraded and mineralized by these microorganisms. Electro-Kinetic Remediation— In this method electrodes are implanted into the soil. The ionic species and charged particles in the soil migrate to one electrode and water migrates towards cathode. The contaminants arrived at the electrodes can be removed by adsorption or precipitation at the electrode or pumping of water near the electrode. Incineration Technologies— Hazardous wastes can be volatilized and combusted in incinerators such as the rotary kiln, infrared furnaces, liquid injection, plasma arc, fluidized bed etc at temperatures that range from 870 to 1200° C. Incineration at these temperatures can break the chemical bonds of organic compounds and other substances. In-Situ Grouting— Over the long term, voids are created in the backfill and waste matrices of landfills, creating surface depressions and areas prone to water infiltration. In-situ grouting of shallow landfills [17] has been used to effectively control the inflow of surface water, thus reducing leach rates, into hazardous waste sites. Grouting, or the injection of matter to fill the voids, can be done with chemical grouts, in solution form, or slurry grouts that are in particulate form.

In-Situ Vitrification— In this method, the contaminated soil is meted to render the soil nonhazardous. Soil is electrically heated to a temperature of 1600 to 2000° C. the high temperatures destroys the organic pollutants. SOILS SUBJECTED TO FROST HEAVE AND FROST BOIL Frost Heave When temperature falls below the freezing point the water in the capillary zone converts into ice crystals resulting in increase of volume of soil. The increase in volume results in expansion of soil i.e.; frost heave. Due to frost heave the soil at the ground surface is lifted. Lightly loaded structures constructed over such soils are lifted due to frost heave. Silts and fine sands are mostly prone to frost action. These soils have large capillary rise due to relatively fine particles and good permeability. Clayey soils have large capillary rise but their permeability is very low. Hence they have relatively small frost heave. Frost Boil After the occurrence of frost heave, if the temperature rises, the ice crystals start melting. Ice is converted into liquid. Hence water content increases and the soil becomes soft. The process of softening of soil due to liberation of water during thawing is known as frost boil. The effect of frost boil is more pronounced on highway pavements. A hole is generally formed in the pavement due to extrusion of soft soil and water under the action of wheel loads. Frost heave and frost boil occurs in case of fine sands and silts. Mitigative Measures Soil Replacement— Replace the frost-susceptible soil by coarse grained soils such as gravels or coarse sands. This method is not economical if the depth of frost-susceptible soil is more. Providing Coarse grained or insulated blanket— Insulating blanket is provided between the water table and the ground surface. It consists of gravel and reduces capillary action and hence the migration of water and the formation of ice lenses. Providing good drainage system— It prevents the frost action by lowering the water table and the water liberated during thawing is drained away quickly. Use of dispersive agents— Dispersive agents such as sodium poly phosphate when mixed with soil decease the permeability of soil there by reducing the frost action. CONCLUSIONS The following broad conclusions are drawn and recommendations are made for the design of safe buildings on problematic sites:

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1. For a building projects adequate amount of fields and laboratory studies must be carried out to Investigate the possibility of the presence of problematic soils. 2. In case the presence of problematic soils confirmed supplementary testing for quantification of the relevant parameters must be carried out. 3. The most cost effective remedial measures must be subsequently evolved, in keeping with the indigenous technology. 4. The engineering institutions must be considered launching a comprehensive research Program, for a detailed study on problematic soils and preparation of national guidelines, for the design buildings in such conditions.

[2] [3]

[4]

[5] [6] [7]

REFERENCES [1]

D.M.Ham by “site remediation techniques supporting environmental restoration activities-a rivew”.

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Geotechnical engineering by Manoj Dutta & gulati S.KTata McGraw-Hill Publishers New Delhi. Faisal-I.Khan, Thair Husain, Ramzi hejazi “An overview of site remediation technologies”, journal of environmental management 71(2004)95-122. Foundations on problematic soils by Sohail Kibria M.Sc.Civil Engg. General Manger, Geotech. &GeoEnvironmental Engg.Division, NESPAK http://www.authorstream.com/Presentation/rizwankhurram -508398-foundation-problems/ Soil Mechanics and Foundation Engineering by B.C. Punmia. Soil mechanics and foundation engineering by Dr.K.R.Arora Standard publishers. Soil Mechanics & foundation engineering by Gopal Ranjan & Rao. New age international publishers.

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.240-245.

Characterisation and Behavioural Analysis of Granular Pile Anchors in Terms of Heave and Strength Aswari Sultana1, B.R. Phani Kumar2 and A. Srirama Rao3 1

Assistant Professor in Department of Civil Engineering, Vasavi College of Engineering, Hyderabad, A.P. 2 Professor of Civil Engineering, Vellore Institute of Technology, Vellore, Tamilnadu 3 Formerly Principal & Professor in Civil Engineering, JNT University College of Engineering, Kakinada, A.P Email: [email protected]

ABSTRACT Expansive soils are one of the most problematic soils and the structures constructed on these soils experience distress and develop cracks due to alternate swellings and shrinkages of the soil. Due to this reason, the bearing capacity of the soil will be high in the dry state and quite low in the swollen state. Granular Pile-Anchor (GPA) system is a successful technique to arrest heave and to improve the overall engineering behaviour of expansive clay beds. Granular piles, anchored at the bottom to a steel plate, through a steel rod fastened to the surface footing are called granular pile-anchors. In this study, an approach has been developed to analyses the behavior of granular pile anchors in terms of heave and strength aspects. Heave has been found to vary curvilinear with depth and approach a zero value at the bottom of the pile, in a laboratory test. A mathematical equation was developed for heave which gave a curvilinear variation at various depths. Two cases are considered with respect to variation of shear stress i.e.; a constant shear stress with a linear variation. INTRODUCTION

REVIEW OF LITERATURE

Expansive soils experience alternative volumetric change corresponding to increase or decrease of moisture content. Lightly loaded structures constructed on expansive soils suffer cyclic swell and shrink movements due to alternate wetting and drying of these soils. Hence, an alternative foundation technique in the form of granular pile-anchors has been suggested (Phani Kumar, 1995) for reducing heave of foundations. So far, granular piles have been used as a ground improvement technique for improving the engineering performance of soft soils and loose cohesionless deposits, where the problem is large settlements and poor bearing capacity. But in expansive soils the problem is uplift of foundations, where the upward force exerted by the swelling soil and the foundation is tensile in nature. A mere granular pile, which can take only compressive loads effectively, cannot resist the upward force. On the other hand, if it is modified into a granular pile-anchor by anchoring the foundation to a mild steel plate at the bottom of the granular pile with the help of a mild steel anchor rod, it will be able to resist the tensile upward load. The granular pile-anchor must be with respect to shear stress, in order not to fail to in uplift. This shear stress is assumed to be constant with depth and vary linearly with depth. The shear strength which is dependent upon the swelling characteristics of expansive clay is determined at different depths based on the heave at those depths. Heave has been found to vary curvilinearly with depth and approach a zero value at the bottom of the pile, in a laboratory test. An equation developed for heave also gave a curvilinear variation (Dr Phani Kumar, 1995).

Several innovative techniques such as physical alteration, chemical alteration, and tension-resistant foundations were recommended to minimize the swell-shrink problems posed by expansive soils. The sand cushion technique (Satyanarayana 1966) and the Cohesive NonSwelling (CNS) layer technique (R. K. Katti Lecture 1978) are examples of physical alteration. Blending expansive soils with chemicals such as lime, CaCl2, fly ash, and Portland cement (SriRama rao, 1984) fall under the category of chemical alteration. Many well-known tension-resistant foundations in practice are under-reamed piles (Sharma et al. 1978), belled piers, and drilled piers (Chen 1988). While the alteration techniques either replace the expansive soils or change the mineralogy of the clay particles and thus reduce the volume changes in expansive soils, tension-resistant foundations absorb tensile uplift force caused on the foundation by the swelling soils. A granular pile-anchor (GPA), which is a modification of granular pile, is a recent foundation technique that has been found to be quite effective in reducing heave and improving the engineering behavior of expansive clay beds (Phanikumar 1995). CONCEPT OF GRANULAR PILES The Concept of Granular Pile Anchor is shown in the following figure 1.

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Characterisation and Behavioural Analysis of Granular Pile Anchors in Terms of Heave and Strength

Where, Pu = uplift load psm = mobilized swelling pressure and Df = annular area of a square plate of side .·. σz = 4z Pu / πD2pLp

(6)

Δ = 2 Pu Lp/πD2pEp

(7)

The deformation, Δ can be predicted for the given placement conditions of the soil and the granular pile. The placement conditions for the granular soil are an initial dry unit weight of14 kN/m3, and an initial water content of 14%. The granular pile is of length 0.3m and compacted at a relative density of 0.6. For these placement conditions, the Young’s modulus of the pile as suggested by Phani kumar, 1995 is 30 MPa.

Fig. 1: The Concept of Granular Pile Anchor

ANALYSIS OF THE FORCES ACTING ON THE GRANULAR PILE ANCHOR Various forces acting on the granular pile anchor are vertical stress and shear stress as shown in figure 2 below. σz is the vertical stress acting on the pile at depth z and τ is the shear stress.

For the placement conditions considered, Pu has been calculated as 786.8 N. the mobilized swelling pressure has been found from the relation between swell potential and surcharge pressure. Based on the measured deformation in the laboratory psm and Pu have been determined. It is important to know the variation of heave, “δ” with depth. Because of the overburden pressure “δ” varies either curvilinear or linearly with depth approaching zero or a minimum value at some depth. The depth where heave becomes negligible is important in the design of foundations. In this work, both the curvilinear and linear variations have been considered based on the suggestions given by Poulos (1973) and the depths where “δ” becomes zero have been arrived at analytically. The analysis is as follows:

Fig. 2: Forces Acting on the Granular pile

Considering an element of the pile of thickness dz at a depth z below the top of the pile, the equilibrium equation of forces acting on the element is (σz πDp2/4 + τ πDp dz) = (σz + dσz ) πDp2 /4

(1)

Or, dσz/ dz = 4 τ /Dp

(2)

Or, dσz = 4 τ dz /Dp

(3)

Firstly, the straight line variation of heave with depth is considered. This is assumed to decrease linearly with depth (Figure 3). If δ0 is the heave at top then the heave at any given depth z from the top (δz) can be written as δz = δ0 (1 – βz/L)

(8)

Where, Dp = dia of the pile This is the basic differential equation governing the equilibrium. Here two cases can be considered i) When τ is uniform throughout the depth, and ii) τ varies linearly with depth. Case (I): When τ is uniform throughout the depth Average shear stress, τav = Pu/πDpLp

(4)

Where, Pu = psm (D2f – πD2p/4)

(5)

Fig. 3: Assumed Linear Deformation with Depth

Swell potential is the ratio of the deformation of any given layer to the thickness of that layers, i.e, ΔH/H, and is expressed as a percent. The mobilized swelling pressure at different depths also varies with the swell potential. This can be studied from the relation between the surcharge pressure and swell potential. Based on the mobilized swelling pressure value, the factors of safety with respect to shear strength, τmax can be determined as

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F. S = (τmax /τz )

(9)

τmax is given by

When z = Lp σz = 4 τ0z/Dp (1+ β/2)

τmax = C' + σh tan ø'

(10)

But, σz. π D2p/4 = Pu

where, σh (horizontal stress) = (k σv + Psm)

(11)

Pu = π τ0zDp (1+ β/2)

(16)

(17)

Where, C' and ø' are the shear parameters of the soil interface, σv the overburden stress and k the co-efficient of lateral earth pressure.

When z = Lp Pu = π τ0 LpDp (1+ β/2)

(18)

As the contribution of overburden stress in comparison with that of swell pressure is insufficient, in cases of short granular pile-anchors, the shear strength is given by

τ0 = Pu /π LpDp (1+ β/2)

(19)

τmax = C' + psm tan ø'

(12)

The heave, δ, of the expansive soil layer which is recorded at the top is not constant throughout the depth. Based on its variation, psm has been determined and τmax arrived at the factors of safety with respect to shear strength are also calculated. The shear parameters of soil-pile interface C' and ø', for the given placement conditions, are 16 kN/m2 and 26° respectively, as determined from the results of shear box test.

This is the general equation for Pu for different values of β. However, if β = 0, Pu = π LpDp τav

(20)

Where, τ is uniform throughout the depth. Where τ varies linearly with depth, σz = 4 τ0z/Dp + 4 τ0 β2z/ 2DpLp

(21)

Being a cubic equation, this gives a curvilinear variation of ‘δ’ with depth (Figure 4)

Considering Eq. (8) which gives the linear variation of heave with depth, β which can be defined as “depth factor” reflecting the behaviour of different soils is given different values as 1.0, 1.5 and 2.0. These different values of β, give three different linear variations by which the depth where “δ” becomes zero changes in every case.

Fig. 4: Assumed curvilinear variation of deformation (δ)

In each variation δz at different depths has been determined and based on this psm and τmax have been arrived at. The corresponding factors of safety at different depths have also been determined.

Considering the curvilinear variation also, the depths where ‘δ’ becomes zero have been arrived at analytically by equating the first derivative of ‘δ’ with respect to z i.e, δz/dz to zero.

Case (II): Where τ linearly varies with depth

Therefore, δ = 4 τ0/ED[z2/2] + 4 τ0ED β/2. ½. [z3]

Assuming linear variation of shear stress (τ) with depth, the shear stress mobilized at the top is taken as τ = τ0 and that at any depth 'z' as

dδ/dz = 4 τ0/ED(z) + 4 τ0ED β/2. ½.(z3) = 0

τz = τ0 (1+βz/Lp)

z(1+z β/2.L) = 0

(13)

Therefore, at the bottom of the file, z = Lp, the shear stress is, τ = τ0 (1+β)

(14)

Where β is a co-efficient called the “depth co-efficient”, which reflects the behavior of different soils. Therefore, the basic differential equation becomes, σz = 4 τ0z/Dp + 4 τ0 β2z/ 2DpLp

(15)

(22)

z + β/L. z2/2 = 0

i.e either z = 0, or, (1+ β/2.L) = 0 Where, z = 0, heave becomes zero at the bottom of the pile. When 1+ β/2.L = 0, heave becomes zero or minimum When, z = -2L/β

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(23)

Characterisation and Behavioural Analysis of Granular Pile Anchors in Terms of Heave and Strength

β will be given different values to find out the depths at which heave becomes zero or minimum. Here, for the sake of convenience, β is taken as -4, -5 and -6. Only three cases are felt enough, as they give the trend sufficiently clearly. Based on the above values of β, τ0 has been determined. This 'δ' gives the minimum values of heave at the depth z for different values of β. For example, when β = -4, z = L/2. At this depth, heave has been found to be the minimum most value. The maximum value of heave occurs at the top of the pile, i.e, when z = L, the values of heave at intermediate depths have been obtained by substituting different values of 'z'. This gives the curvilinear variation of 'δ' for the given value of β. Swell potential of each layer has been calculated based on the value of δ at that depth. The mobilized swelling pressure has been obtained from graph based on the swell potential. The shear strength τmax at different depths has been calculated. The factors of safety with respect to shear strength have also been determined for curvilinear variation of 'δ' also. APPLICATION OF METHODOLOGY Fig. 6: Linear Variation of deformation and swell and Shear Stress and Shear Strength with depth β =1.5

1. Linear variation of heave and corresponding variation of shear strength Figures 5 to 7 shows the variation of ‘δ, ΔH/H %, τ0 and τmax for β = 1.5 and 2.0.

Fig. 7: Linear Variation of deformation and swell and Shear Stress and Shear Strength with depth β =2.0

Fig. 5: Linear Variation of deformation and swell and Shear Stress and Shear Strength with depth β =1.0

It can be seen from figure 6 that for β = 1.5, the pile movement occurs only up to a depth of 0.2 m from the top or the active zone in this case can be written as Za = 5d. The swell potential is constant up to a depth of 2L/3 = 5d

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from top and gradually approaches zero at the bottom of the active zone. Figure 7 shows that for β = 2, the pile movement occurs only up to a depth of 0.15 m from the top or the depth of active zone in this case can be written as Za = L/2 ≈ 4d. It is interesting to note that as β increases, swell potential in the top layers increases though the heave at the top is constant. But, the active zone decreases as β increases. This means that the pile should be embedded below the active zone to obviate the danger posed by increased swell potential. For example, when β = 1, the maximum swell potential is 1.0 %. The active zone is equal to the length of the pile. When β = 1.5 and 2.0, the swell potential increases to 1.56 % and 2.1 % respectively. Hence, in these two cases, the length of the pile is greater than the active zones and which are respectively Za = 5d and Za ≈ 4d

Similarly, curvilinear variation of heave and corresponding variation of shear strength at different depths of a pile calculated. Figures 8 and 11 shows the variation of ‘δ, ΔH/H %, τ0 and τmax for β = 0.0, 0.5, 1.0, 4.0, -5.0 and -6.0.

Figure 6 and Figure 7 show variation of increase τmax with depth. It can be seen as β increases τmax in the top layers reduces. This is understandable because the pile-soil slip should be more for increased swell potential to occur in the top layers. However, as swell potential decreases in the bottom layers τmax increases. From the above discussion, it follows that at some value of β, the shear strength becomes equal to shear stress as swell potential in the top layers goes on increasing. To preclude this possibility, it is important that the pile should be embedded below the active zone as β increases from 1.0.

Fig. 9: Curvilinear variation of deformation and swell and Shear Stress and Shear Strength with depth (-4.0)

Fig. 10: Curvilinear variation of deformation and swell and Shear Stress and Shear Strength with depth (-5.0) Fig. 8: Variation of deformation and swell and Shear Stress and Shear Strength with depth (0.0, 0.5 & 1.0)

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Characterisation and Behavioural Analysis of Granular Pile Anchors in Terms of Heave and Strength

strength τmax becoming equal to shear stress τ at the increased swell potential values and full slip occurring. 6. Shear stress can be assumed either to be constant with depth or to vary linearly. The shear strength, τmax mobilized can be obtained from the shear parameters of the interface and the mobilized swelling pressure, psm as well τmax vary with depth. 7. In curvilinear variation of heave with depth, the heave is expressed as δ = 4τ0(Z2/2)/ED+4τ0β(z3/3)/2LED Where, β is the ‘depth factor’. 8. As β increases the maximum swell potential in the top layers decreases and the depth of active zone increases. In soils exhibiting such behavior, it is necessary to anchor the pile well below the active zone. This is clearly reflected in the variation of swell potential and heave. 9. In both the linear and curvilinear variations, the granular pile-anchor is safe with respect to shear strength.

Fig. 11: Curvilinear variation of deformation and swell and Shear Stress and Shear Strength with depth (-6.0)

FINDINGS OF THE STUDY

CONCLUSION

1. Granular pile-anchors are an effective foundation technique in expansive soils because the upward load caused by the soil on the foundation is enormously resisted by the shear resistance mobilized along the pile-soil interface due to shear strength of the interface and also due to the lateral swelling pressure, which confines the granular pile-anchor and prevents the uplift. 2. The heave or the movement of granular pile-anchor varies with depth. This variation can be assumed to be either linear or curvilinear. The heave is maximum at the top of the pile-anchor and reaches a minimum value at some depth of the pile. 3. The linear variation of heave is expressed by the equation δz = δ0 (1-βZ/L) Where β is the 'depth factor' governing the swelling characteristics of different clays. 4. As β increases swell potential in the top layers increases ensuring a greater amount of slip, and a study of soil-movement profile shows that the depth of active zone decreases as β increases. 5. It is necessary to embed the pile below the active zone at higher values of β as there is a possibility of shear

A general expression for the swelling potential of the given expansive soil at an initial water content of 14%, reinforced with a granular pile-anchor, can be given in the form of equation developed in the study. A good correlation was obtained with the above expression. REFERENCES [1]

Phani Kumar B.R. (1995), “A Study of Swelling Characteristics of and Granular Pile Anchor- Foundation System in Expansive Soils”, Ph.D. Thesis submitted to the lawaharlal Nehru Technological University, Kakinada.

[2]

Satyanarayana, B. (1966), “Swelling pressure and related mechanical properties of black cotton soils”, Ph.D. Thesis, I.I.Sc., Bangalore.

[3]

Katti, R.K. (1978), Search for solutions to problems in black cotton soils”, First I.G.S. Annual Lecture, Indian Geotech. S9ciety at I.I.T., Delhi.

[4]

Sharma, D., Jain, M.P. and Prakash, C. (1978), “Handbook on under-reamed and bored compaction pile foundations”, Central Building Research Institute, Roorkee.

[5]

Chen, F.H.(1975),”Foundations on expansive soils”, Elsevier Scientific Publishing Co., Amsterdam.

[6]

Poulos (1973) in the Chapter on “ Piles in Swelling Clays” In his book on “pile Foundations” (pp 294 - 310).

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Transportation Systems

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.249-252.

Lane Distribution Factors – A Case Study on NH7 &NH9 S. Ramesh Kumar1 and K.V. Krishna Reddy2 1 Associate Prof., 2Professor Dept. of Civil Engg MVSR Engineering College, Hyderabad, AP, Email: [email protected], [email protected]

ABSTRACT Lane distribution factor (LDF), defined as percentage of the annual average daily truck traffic in a lane along a road way is assumed as per the codal provisions. This is basically due to inadequate and inconclusive data of commercial vehicles in traffic on Indian roads with mixed traffic conditions. LDF is assumed until reliable data of commercial vehicles on the carriage way lanes are available and the actual value is taken based on traffic studies. The Paper aims at presenting a case study on fixation of Lane Distribution Factor for 2-lane and 4-lane divided and undivided highway pavements on NH7 and NH9. Keywords— Lane Distribution Factor INTRODUCTION Traffic survey reports average the total traffic count in both the directions. However for design purposes the traffic along a particular lane needs to be considered. This factor is called Lane distribution factor and is defined as percentage of the annual average daily truck traffic in a lane along a road way. This is multiplied by the total number of commercial vehicles in both directions to obtain traffic along a single lane. Due to inadequate and inconclusive data of traffic for Indian conditions, IRC-372001 suggests to assume LDF until reliable data on placement of commercial vehicles on the carriage way lanes are available. In this study an attempt is made to evaluate LDF for NH-7 and NH-9.

for data collection. Various 2 lanes and 4 lane stretches were located on both NH7 and NH9 highways and data was collected in the format depicted in Table 1.

RESEARCH METHODOLOGY As stated in the introduction, NH7 and NH9 are considered for evaluation of LDF. The standard dimensions of various vehicles were obtained from the websites of vehicle manufacturers. In pilot study, it was observed and determined to divide the road width into stretches of 0.75m grids leaving a safe distance of 0.5m from the median. Figure 01 and Figure 02 depict in photograph and sketch, the grids arrangement considered

Fig. 2: Stretch marking on two lane Highway Table 1: Format for Data Collection

Date: weather

Day: Vehicle code St1

Lane: Grid no St2 St3

Loading Characte ristics

DATA ANALYSIS The data collected was analyzed and is presented by plots vide Figures 03 to 26. Fig. 1: Stretch marking on Four lane Divided Highway

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Fig. 3: Distribution of Loaded Vehicles on NH9-TwoLanes at Koilagudem (Vijayawada to Hyderabad)

Fig. 7: Distribution of Loaded Vehicles on NH7-TwoLanes at Manoharabad (Bangalore to Nagpur)

Fig. 4: Distribution of empty Vehicles on NH9-TwoLanes at Koilagudem (Vijayawada to Hyderabad)

Fig. 8: Distribution of Empty Vehicles on NH7-TwoLanes at Manoharabad (Bangalore to Nagpur)

Fig. 5: Distribution of Loaded Vehicles on NH9-TwoLanes at Koilagudem (Hyderabad to Vijayawada)

Fig. 9: Distribution of Loaded Vehicles on NH7-TwoLanes at Manoharabad (Nagpur to Bangalore)

Fig. 6: Distribution of empty Vehicles on NH9-TwoLanes at Koilagudem (Hyderabad to Vijayawada)

Fig. 10: Distribution of Empty Vehicles on NH7-TwoLanes at Manoharabad (Nagpur to Bangalore)

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Lane Distribution Factors – A Case Study on NH7 & NH9

Fig. 11: Distribution of Loaded Vehicles on NH9-Four Lane divided at Abdullapurmet (Hyderabad to Vijayawada)

Fig. 17: Distribution of Loaded Vehicles on NH9-Four Lane divided at Batasingaram (Hyderabad to Vijayawada)

Fig. 12: Distribution of Empty Vehicles on NH9-Four Lane divided at Abdullapurmet (Hyderabad to Vijayawada)

Fig. 15: Distribution of Loaded Vehicles on NH9-Four Lane divided at Batasingaram (Vijayawada to Hyderabad)

Fig. 18: Distribution of Loaded Vehicles on NH9-Four Lane divided at Batasingaram (Hyderabad to Vijayawada)

Fig. 19: Distribution of Loaded Vehicles on NH9- Two Lanes (Both ways)

Fig. 16: Distribution of Empty Vehicles on NH9-Four Lane divided at Batasingaram (Vijayawada to Hyderabad)

Fig. 20: Distribution of Empty Vehicles on NH9-Two Lanes (Both ways)

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end of the road with a value of 0.42. On NH9 the width was 7m and the maximum load distribution was found to be at 4.5m from left end and is 50% of the total vehicles. Four lane divided section of NH9 was found 12.6m wide with a maximum load distribution at 6m from left and is 34% of the total vehicles. LDFs obtained are reported in Table 2 as depicted below Table 2: LDFs Obtained from Data Analysis

Fig. 21: Distribution of Loaded Vehicles on NH7- Two Lanes (Both ways)

Highway

Stretch

NH7 –Both Ways NH9 –Both ways NH9 –Both ways

Single lane Single lane Four lane - Divided

Lane Distributi on Factor 42% 50% 34%

CONCLUSION  Lane Distribution Factor for two lane section of NH7 has been evaluated to be 42% as against 75% suggested by IRC  Lane distribution Factor for two lane section of NH9 has been evaluated to be 50% as against 75% suggested by IRC.  Lane distribution Factor for four lane divided highway section of NH9 has been evaluated to be 34% as against 40% suggested by IRC.

Fig. 22: Distribution of Empty Vehicles on NH9-Two Lanes (Both ways)

ACKNOWLEDGEMENT At the outset the author would thank the Head, CED MVSREC, Dr. Bhavnarayana, CT, MCH for their valuable guidance and encouragement during the study. Final year student group with rolls10,12,22,25,36and59 are acknowledged for their efforts in data collection. REFERENCES Fig. 23: Distribution of Empty Vehicles on NH9-Four Lane divided (Both ways)

[1]

[2]

[3] [4] Fig. 24: Distribution of Empty Vehicles on NH9-Four Lanes divided (Both ways)

RESULT On NH7 with two lanes, the width was 9m and the maximum load was observed at 1.5m and 5.25m from left

[5]

252

Goodrich, B. L., and J. A. Puckett, “Comparison of LFR and LRFR Bridges,” paper presented at National Concrete Bridge Conference, National Concrete Bridge Association, Nashville, TN (October 2002). Huo, X. S., S. O. Conner, and R. Iqbal, Re-Examination of the Simplified Method (Henry’s Method) of Distribution Factors for Live Load Moment and Shear. Final Report for Tennessee DOT Project TNSPR-RES 1218, Tennessee Technological University, Cookeville, TN (June 2003). IRC 37 - 2001: Guidelines for Design of Flexible Pavements Puckett, J. A., M. Mlynarski, C. M. Clancy, B. L. Goodrich, M. C.Jablin, W. Smyers, and K. Wilson, “Bridge Software Validation Guidelines and Examples,” Transportation Research Record 1696: Fifth International Bridge Engineering Conference, April 3-5, 2000,Tampa, Florida,Vol. 1, Transportation Research Board, Washington, D.C. (2001). Zokaie, T., and R. A. Imbsen, NCHRP Research Results Digest 187:Distribution of Wheel Loads on Highway Bridges, Transportation Research Board (1992).

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.253-258.

Use of “Trip Generation and Trip Distribution Analysis” in Solving Transportation Problems for Selected Areas of Kurnool City Sowjanya1 and Shaheena Parveen2 1 Assistant Professor, 2B.Tech (Civil Engineering) G.Pulla Reddy Engineering College, Kurnool Email: [email protected]

ABSTRACT The first phase of the transportation planning process deals with surveys, data collected and inventory. The next phase is the analysis of data so collected and building models to describe the mathematical relationship that can be discerned in the trip-making behaviour. The analysis and model building phase starts with the step commonly known as Trip Generation. It is desirable to understand the exact meaning of the various terms. A trip is oneway ends, an origin (the starts of the trip) and destination (the end of the trip). After having obtained an estimate of the trips generated from and attracted to the various zones, it is necessary to determine the direction of the travel. The number of trips generated in every zone of the area under study has to be apportioned to the various zones to which these trips are attracted. With this background, an attempt is made to understand the reasons behind the trip making behaviour and to produce mathematical relationships to synthesis the trip making and trip direction pattern in Kurnool city on selected study areas. For trip generation the selected study area is CCamp and the trips were observed on home and non-home. It is concluded that the number of trips are based affected by income, size and vehicle ownership of household. For trip distribution the selected study area are Rajvihar, C-Camp, Bellary Chowrastha and Old bus stand. Trip direction between the zones is observed and forecasting is done for further two years. It is concluded that the number of trips maximum towards Rajvihar and minimum towards Old busstand. Keywords— Tripgeneration,Ttrip distribution, Uniform, Average and Detroit models. INTRODUCTION The four-step travel forecasting model sequence has received extensive use in urban transportation planning. This method first focuses on trip generation, which aims at estimating the total number of trips generated from a zone which is one cell of a region. The amount of trip generation is the total number of trips generated over the region, and has been called trip production. Therefore, trip production has an important role of establishing the level of demand for travel. Actually, trip generation has been studied at two sequential phases; trip production and trip generation. Trip generation is a general term used in the transportation planning process to cover the field of calculating the number of trip ends in a given area. The objective of the trip generation stage is to understand the reason behind the trip making behaviour and to produce mathematical relationships to synthesise the trip making pattern on the basis of observed trips land use data and household characteristic. The goal of trip generation model development is to establish a functional relationship between travel and land use and socio economics characteristic of the units to and from which the travel is made.

Intensity is the amount of activity to be found in a given areal unit zone)and is usually stated in terms of density measure such as the number of employees per square foot of floor area or per acre of a particular land use category, or the number of dwelling unit per acre. Trip distribution analysis is the process by which trips originating in one zone are distributed to other zones in the study area. Trip distribution methods have evolved in the two decades from a total reliance on growth factor techniques to wide use of interaction travel models. When growth factor techniques are used, it is necessary to make adjustment to account for zones now vacant but which are expected to be developed, as well as for the zones in which future land uses will be materially different from the existing land uses. When an urban area is expected to experience significant growth, the adjustments to the present trip pattern become difficult and, to a considerable extent, speculative. The greatest advantage of the growth factor techniques is that they reflect the many unique travel relationships that exist in any urban area. They are most applicable in slowly growing areas, for short range TSM, planning, and for external travel forecasting. However, many cities are

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expe riencing rapid growth in the form of significant suburban development coupled with extensive downtown redevelopment. These land use changes make extensive adjustments to the procedure necessary. For this reason, many of the major urban studies have turned to mathematical travel models. Trips are made for different purposes and a classification of by purpose is necessary. The following are some of the important classes of trip purpose:  Work

Journey is an out way movement from a point of origin to a point of destination, whereas the word ``trip” denotes an outward and return journey. If either origin or destination of a trip is the home of the trip maker then such trips are called home based trips and the rest of the trips are called non home based trips. Trip production is defined as all the trips of home based or as the origin of the non-home based trips. See figure 1. TRIP PRODUCTION AND ATTRACTION The two types of generated types are:

 School

1. Trip production: Those trips which are generated by residential zones, where they may be origin trip or destination trip, i.e.,Atrip that has one end at home.(home based)

 Business  Social or recreational activities  Others.

2. Trip attraction: This term is used to describe trips generated by activities at the none home end from work to shop, employment to other offices etc.

TYPES OF TRIPS Some basic definitions are appropriate before we address the classification of trips in detail. We will attempt to clarify the meaning of journey, home based trip, nonhome based trip, trip production, trip attraction and trip generation.

The generation is considered as the sum of trip produced (Pi)and trip attracted (A j). Ti=Pi+Aj

Productions and Attractions Residential

1 Non-residential

8 A worker leaves Zone 1 in the morning to go to work in Zone 8

Non-residential Residential

This results in 2 trip ends: • One Production for Zone 1 • One Attraction for Zone 8 Total Number of Trip Ends When that same worker leaves Zone 8 in the evening to go to home to Zone 1 This results in another 2 trip ends: • One Production for Zone 1 • One Attraction for Zone 8

Zone 1: 2 Trip Ends (2 Productions) Zone 8: 2 Trip Ends (2 Attractions)

Norman W. Garrick

Fig. 3: Productions& Attractions

ANALYSIS AND RESULTS Fig. 1 A zone produces and attracts trips Zone i # of dwelling units Shopping center employees Etc.

Depending on the activities in the zone, it can produce and/or attract trips. Transportation planners estimate these trips first.

Fig. 2

Category Analysis at Kallur Trip Generation Based on Auto Mobile Ownership In our study, Kallur zone is selected as study area. The details of the selected area are given below and the number of household’s data is collected from the chief planning office (CPO) from collector complex. The above data gives the total number of households with different family sizes and with number of automobile ownership. Household trip rate is calculated from the number of household and the number of trips

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Use of “Trip Generation and Trip Distribution Analysis” in Solving Transportation Problems for Selected Areas of Kurnool City

Household trip rate= number of trips / number of household Table 1

State District 28 28 28

21 21 21

Level

Name

Mandal Mandal Mandal

Kallur Kallur Kallur

Table 5: Future number of trips from Kallur zone

No of house hold Urban 15177 Rural 10248 Total 25425 Total

No of house hold and total trips made categorized by house hold size and auto ownership Table 2: No of trips made by house holds

0 No of Family house size hold 1. 925 2. 1471 3. 1268 4 or 745 more

1 No of trips 1098 2105 1850 1509

No of house hold 1872 1934 3071 4181

The above values give the future daily number of trips after one year from the selected zone of Kallur Mandel in urban region.

No of trips 4821 6129 13989 18411

2 or more No of No of house trips hold 121 206 692 1501 4178 19782 4967 25106

Automobile ownership 2(or) 0 1 more 29 107 14 14 161 232 16 141 748 6 75 1560

Family size 1 2 3 4(or) more Regression Analysis in C-Camp

Table 6: Collected Socio-Economic data

S. No

Table 3: House hold trip rate based on Automobile ownership

0

1

2(or) more

1.19 1.43 1.45 2.02

2.57 3.16 4.55 4.40

1.70 2.17 4.74 5.05

Forecast number of household in one zone, categorized by house hold size and auto ownership level Table 4: Future No of house holds

Family size 1 2 3 4(or)more

Automobile ownership 0 1 24 42 10 51 11 31 3 17

150 407 905 1641

Establishing the Trip Generation Equation for C Camp Zone in Kurnool Town

The following data gives the total number of households based on automobile ownership and household size (or) family size of a small selected zone in kallur mandal. from which we can easily calculate the future number of trips by multiplying the trip rate with households having automobile ownership and households are not having automobile ownership.

Size of family 1 2 3 4(or)more

Total

2(or)more 8 107 158 309

65 484 2554 3103

255

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Household monthly income x1 200 250 150 100 250 340 180 150 200 240 250 100 150 200 250 350 150 100 250 350 300 200 150 250 200 350 300 200 150 300

Househol d size x2 4 6 6 8 4 4 9 7 6 4 5 8 4 5 5 6 5 7 4 3 5 5 5 4 4 4 6 5 7 7

Household Total Business Daily Trip y 2 4 5 6 2 3 6 4 4 5 6 6 6 8 7 6 4 3 4 10 8 6 4 3 6 5 9 7 4 6

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

Where,

∑I yx1 =∑yx1 – (∑y∑x1 /N) = 36260-(159*6660/30) =962

y =Dependent variable (Trip per day to be associated )

∑lX1X2x22 =∑x22 – ((∑x2)2/N) = 938-(1582/30) =105.86

X1=Per capita income per household

∑lyx2=∑yx2-(∑y∑x2/N) = 861-(159*158/30) =23.6

Y=Trips per day

∑lX1X2=∑X1X2-(∑X1∑X2/N) = 33190-(6660*158/30) =1886

X2=Persons in Household Taking only 30 number of households and there per capita income per household and size of household is taken as independent variables. Number of trips is the dependent variable. This data is collected from the direct survey method. Above are the socio-economic data collected for the trip generation of a zone in the study of a city.

X1

1 200 2 250 3 150 4 100 5 250 6 340 7 180 8 150 9 200 10 240 11 250 12 100 13 150 14 200 15 250 16 350 17 150 18 100 19 250 20 350 21 300 22 200 23 150 24 250 25 200 26 350 27 300 28 200 29 150 30 300 ∑ 6660

X2 Y

X12

4 2 6 4 6 5 8 6 4 2 4 3 9 6 7 4 6 4 4 5 5 6 8 6 4 6 5 8 5 7 6 6 5 4 7 3 4 4 3 10 5 8 5 6 5 4 4 3 4 6 4 5 6 9 5 7 7 4 7 6 158 159

40000 62500 22500 10000 62500 115600 32400 22500 40000 57600 62500 10000 22500 40000 62500 122500 22500 10000 62500 122500 90000 40000 22500 62500 40000 122500 90000 40000 22500 90000 1625600

X22 x1 x2 16 36 36 64 16 16 81 49 36 16 25 64 16 25 25 36 25 49 16 9 25 25 25 16 16 16 36 25 49 49 938

Yx1

800 400 1500 1000 900 750 800 600 1000 500 1360 1020 1620 1080 1050 600 1200 800 960 1200 1250 1500 800 600 600 900 1000 1600 1250 1750 2100 2100 750 600 700 300 1000 1000 1050 3500 1500 2400 1000 1200 750 600 1000 750 800 1200 1400 1750 1800 2700 1000 1400 1050 600 2100 1800 33190 36260

The Regression equation is: Y=a+b1x1+ b2x2

Yl=∑y/N =159/30 =5.3 X1l=∑x1/N = 6660/30 =222 X2l=∑x2/N =158/30 =5.26 b1= (∑I yx1∑l x22-∑lyx2∑lX1X2)/ (∑lx12∑l x22-∑l (X1X2)2) =0.0076

Table 7: Analysis of trip generation

S. No

∑lx12=∑ - ((∑x1)2/N) = 1625600-(66602/30) =147080

Yx2

Y2

8 24 30 48 8 12 54 28 24 20 30 48 24 40 35 36 20 21 16 30 40 30 20 12 24 20 54 35 28 42 861

4 16 25 36 4 9 36 16 16 25 36 36 36 64 49 36 16 9 16 100 64 36 16 9 36 25 81 49 16 36 953

b2=(∑lyx22∑lx12-∑I yx1∑lX1X2)/ (∑lx12∑lx22-∑l (X1X2)2) =0.27 a= yl- b1x1l- b2x2l =5.3-(0.0076*222)-(0.27*5.26) =2.19 COEFFICIENT OF CORRELATION r = [(b1∑x1y-∑x1∑y/N) +b2 (∑x2y-∑x2∑y/N)]/ [∑Y2(∑Y2/N)] r= [0.007*(36260-(6660*159/30)+0.27(861-(158*15/30)] / (953-1592/30) r=0.2 r=1( perfect relationship between variables) r=0 (no relationship between variable) The r value is in between 0 and 1 and it is nearly equal to 0 hence there is no good relationship between these variables. TRIP DISTRIBUTION ANALYSIS The trip distribution analysis for Kurnool town is given below. The four zones are taken in which A=Bellarychowrastha B= Rajvihar C= C camp D= Old busstand A study area has been divided in four zones A, B, C&D. The results of the trip generation analysis and the present trip distribution matrix are included in the following tables.

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Use of “Trip Generation and Trip Distribution Analysis” in Solving Transportation Problems for Selected Areas of Kurnool City Table 8: Present trip produced and attracted

Produced Trips Attracted Trips

Present Future Present Future

A 11620 35400 9377 27860

B 13329 39600 10715 31000

Fi factors for zones =

C D 9941 7940 29500 23500 12743 9995 37800 29000

FA=35400/11620 =0.34 FB=39600/1332 =2.9 FC=29500/9941 =2.96 FD=23500/7940 =2.95

Trip Distribution matrix (present)

Attraction factors of zones

Table 9: Present trip distribution matrix

D

A

B

C

D

2345 2887 2945 1200

4545 2890 1940 1340

2400 3943 4000 2400

2330 3609 1056 3000

O A B C D

Fj factors for zones= FA=27860/9377 =2.971 FB =31000/10715 =2.893 FC = 37800/1274 =2.966

Trip Distribution matrix (Future)

FD = 29000/9996 =2.90

 Uniform growth factor method

Table 11: Future trips

 Average growth factor method

D

 Detroit method

O

A(2.97)

B(2.89)

C(2.96)

D(2.9)

7046 8473 8732 3552

13475 8366 5674 3913

7200 11414 11840 7092

6921 10466 3094 8775

A(3.04) B(2.9) C(2.96) D(2.95)

Uniform Growth Factor Method: TIJ=TIJ×F F=

Detroit Method TFij=TIJ× (FI+FJ)/F

F= F=

=2.96

Using this value of F all the values of the present distribution matrix should be multiplied to get future interzonal trips

The individual growth factors as worked out above along the overall growth factor F of 2.96 as calculated before, the future trip distribution matrix using this method can be developed as: Table 12: Future trips

Table 10: Future inter zonal trips

D O A B C D

A

B

C

D

6940 8540 8700 3550

13450 8555 5743 3967

7104 11672 11840 7104

6890 10683 3125 8880

Average Growth Factor Method TFij=TIJ× (FI+FJ)/2 Individual growth factor for each zone. Production factors of zones

D O A(3.04) B(2.9) C(2.960) D(2.95)

A(2.97)

B(2.89)

C(2.96)

D(2.9)

4762 5725 5899 2400

9105 5653 3834 2645

4865 7806 8000 4792

4676 7653 2091 5929

A comparative listing of results is the following (using the three methods): CONCLUSION  From the analysis of trip distribution we can conclude that the vehicular traffic is increasing rapidly at every zone and it is difficult to distribute traffic for future

257

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

hence the adequate network design is required for future.

SCOPE FOR FUTURE WORK

Table 13: Future Trips (using three methods)

A

Uniform GF Average GF Detroit GF

A 6940 7046 4762

B 13450 13475 9105

C 7104 7200 4865

D 6890 6921 4676

B

Uniform GF Average GF Detroit GF

8540 8473 5725

8555 8366 5653

11672 11414 7806

10683 10466 7653

Uniform GF Average GF Detroit GF

8700 8732 5899

5743 5674 3834

11840 11840 8000

3125 3094 2091

Uniform GF Average GF Detroit GF

3550 3552 2400

3967 3913 2645

7104 7092 4792

8880 8775 5929

C

D

 In trip generation the number of trips are more for the house holder having own vehicles.

The study reveals that there is further scope for improving the content trip generation and distribution studies, to cover more areas of traffic improvement and easing up of traffic congestion near the busy junctions.  The study may be extended further to analyse the trip Assignment and Mode split models.  This trip generation and distribution analysis may be done based on other methods like geographical information system (GIS) and global positioning system (GPS).  This trip generation and trip distribution may be done based on pedestrians, age of households and occupation. REFERENCES [1]

 It is observed that the number of trips produced and attracted more at Rajvihar zone, as it is Central Business District (CBD) area.

[2] [3]

 It is observed that number trips produced and attracted less at Old Bus Stand zone compare to other zones.

[4]

 In trip analysis it was observed that the number of trips between the zones or terminals is based on income of house holders.

[5]

 The numbers of trips are increased as the size of family is increases.

258

Text book of Traffic Engineering and Transport Planning, Dr. L.R. Kadiyali, Khanna publishers. Text book of Traffic Planning and Design, Saxena. Dhanpat Rai& sons. A.A. Douglas and Lewis, Trip Generation Techniques, 4 category analysis, Traffic Engineering And Control, Vol.12.No. 10,1971. Wooton, H.J. and G.W.Pick, A Model For Trips Generated By Households, Journal Or Transport Economic And Policy, May, 1967. A.A. Douglas and R.J. Lewis, Trip Generation Techniques, 2-zonal least squares regression analysis, Traffic Engineering and Control, Vol. 12, No.8, 1970

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.259-261.

Cost Effective Method for Short-Term Aging of Bitumen M. Rajesh, P. Ramu, I. Hussen and G. Krishna Parandhama Civil Engineering Department, Rajiv Gandhi University of Knowledge Technologies – IIIT Email: [email protected], [email protected]

ABSTRACT Many agencies are only testing the bitumen properties by following traditional methods like penetration, viscosity, ductility, Ring & Ball tests etc, which are not much simulated to filed, results of which cannot be much helpful in determining pavement failure performance. So, there is need to test the bitumen through filed simulated testing methods which are classified as Short-term and Long-term aging with TFOT and PAV equipments, which are cost ineffective. So, they may not be available for many agencies to test these properties. We made an attempt on providing a cost effective method for short-term aging by simulating TFOT results with NORMAL OVEN. Generally in short term ageing, the bitumen is tested in TFOT, which results simulates the ageing of bitumen during plant mixing, production, transportation and construction and predict binder rutting performance. In this method VG-10 sample has tested in TFOT and NORMAL OVEN and it is found that results of them got approximately similar and also observed that when compared to original binders properties, shortterm aged binder properties has changed in their penetration values, as gets decreased and softening point has increased. Keywords— TFOT, Normal Oven, Short-term aging classified as Two types i.e., 1) Short-term aging 2) Longterm aging

INTRODUCTION Need Finding What is the problem or need— Short-term ageing of bituminous binders is a well-accepted concept that represents ageing of binders during plant mixing, production, transportation and construction. Simulation of this ageing is carried out in controlled laboratory conditions and these aged binders are used to predict binder rutting performance [1]. Who has the problem or need— Thin film oven equipment is costly and may not be available to different agencies and thereby it has become difficult to adopt any studies involving short-term ageing of binders [1].

Short-term aging— Short-term ageing of bituminous binders is a well-accepted concept that represents ageing of binders during plant mixing, production, transportation and construction. Simulation of this ageing is carried out in controlled laboratory conditions and these aged binders are used to predict binder rutting performance [1]. Long-term aging— The simulation of long-term ageing of binders accounts to ageing of the binder during service life of the pavements and these binders are used to characterize the binder response to fatigue performance [1].

Why it is important to solve— Transportation facilities are required for the economic development of a country, Population growth and economic development result extensive development of asphalt-paved roadways, where Bitumen is using as major pavement construction material.Bitumen serves as a satisfactory binder in improvement of physical interlocking of aggregate bitumen mixes and Its properties changes as it ages in bulk storage, transport and storage on site and rest of its life. The ageing of bitumen then leads to deterioration of pavement.

As Project object is mainly concerns on providing costeffective method for short-term aging by using Normal Oven instead of Thin Film Oven.

Aging— Asphalt/bitumen properties change over time on exposure to high temperature and the atmosphere. This process is referred to as ageing. Generally Aging

2. Rolling Thin Film Oven (RTFO)— Simulates shortterm ageing by heating a moving film of bitumen in an oven for 85 minutes at 163 0C (325 0F)

IDEATION Existed Aging Simulation Tests Short-Term Aging:[2] 1. Thin Film Oven(TFO)[3]— Simulates short-term ageing by heating a film of bitumen in an oven for 5 hours at 163 0C (325 0F)

259

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 1: Testing conditions as per ASTM Standards

Test Type

Heating Temp (C)

Penetration[4] Softening TFOT

75-85 75-85 75-85

Time of Exposure to Air(27oC) 1.5hours 0.5 hour 3 Minutes

3. Stirred Air-Flow Test (SAFT)— The RTFOT and TFOT tests required a lengthy amount of time to properly age samples, SAFT expedites the process by using bitumen air blowing. The blowing air oxidizes the crude oil products in the asphalt and ages the samples for 35 min. Long-Term Aging:[2] 1. Pressure ageing Vessel (PAV)— Simulate the effects of long-term bitumen ageing that occurs as a result of 5 to 10 years HMA pavement service. Proposed Alternate Aging Method Any alternative procedure developed that provides similar ageing effects comparable to the SUPERPAVE method would help highway agencies to adopt and study the effect of ageing on binders. Keeping this as the main concern, an attempt is made to develop a cheap and generalized method for short-term ageing effects using a “Normal laboratory oven”. LITERATURE REVIEW Li, Zofka, Marasteanu, and Clyne (2006) were conducted tests to evaluate the rheological properties of the recovered binders as well as original binders aged in laboratory conditions using standard testing procedures (RTFO and PAV) as well as additional test methods. The results indicated significant differences between the recovered and the laboratory-aged binders. Suleiman ArafatYero, 2 Mohd Rosli Hainin (2012) The short-term aging properties of neat bitumen were investigated using the rolling thin film oven test (RTFOT) to simulate aging during mixing, compaction and laying of asphalt mixtures, though the actual time of short-term aging in the field varies depending on haulage distances or paving times. The results from the study also indicated that the magnitude of the short-term aging depends on the binder source, and aging time, as with longer aging time, the binder hardness and viscosity increases, thereby decreasing the penetration and increasing the binder softening point.that aging resulted in oxidation of the bitumen with increase in the stiffness of the binder. Pramod Kumar Behera, A.K. Singh and M. Amaranatha Reddy(2013)

Time of Exposure to Water bath(25oC) 1.5hours Placed in container at 5oC

Test Conditions 27+/- 5oC Start at 5oC 163oC for 5hr

Study included predicting the aging of binders with alternate method for aging. The study revealed that it is possible to correlate ageing methods of SUPERPAVE with a normal oven method. In order to compare the actual short-term ageing of one of the modified binders, bituminous mixes were collected from the field during mix production, transportation and compaction, and binders from these were extracted. Rheological parameters of the extracted bitumen from field samples collected during different stages of construction, RTFO and normal oven-aged samples were evaluated and compared. It was found that the actual ageing is different from RTFO and a normal oven ageing and thereby there is a need to carry out a detailed study on ageing characteristics of Indian binders. METHODOLOGY ADOPTED Testing Procedure 1. Heat the grade of (VG 10) bitumen sample at 75o C85oC and pours it in respective moulds of TFOT[3], Oven and tests at 163oC for 5 hours. 2. Complete the traditional testing methods appropriate ASTM test methods( Appendix 1)

by

Once after TFOT and Oven test completed at a standard temperature of 163oC for 5 hours, residue of TFOT and Oven, filled in moulds of traditional tests, complete it by appropriate ASTM test methods and Results reported in table 3, 4 respectively. RESULTS & DISCUSSIONS Table 2: Results of Virgin Bitumen Grades

i) Penetration Test Initial 381 373 385

Final 68 71 74

Penetration Value 87 98 89

ii) Ring & Ball Test

260

Ball 1(o C) 48

Ball 2(o C) 48

Softening Point (To C) 48

Cost Effective Method for Short-Term Aging of Bitumen

an alternative for TFOT. From our limited study it has observed that:

Table 3: Results of TFOT residue

i) Penetration Test Initial 399 394 395

Final 81 78 78

1) TFOT and OVEN residue properties of Penetration and Softening Point tests results are approximately same

Penetration Value 82 84 83

2) Compare to original binder properties, aged binder properties of penetration and short-term aged binder properties has changed in their penetration values, as gets decreased and softening point has increased.

ii) Ring & Ball Test Ball 1(o C) 48

Ball 2(o C) 49

So, It can be concluded that NORMAL OVEN can be used as cost-effective for short-term aging preferable for VG-10 sample not sure about other grade of bitumen but it can be expected to use for other grades of bitumen also.

Softening Point (To C) 48.5

Table 4: Results of Oven residue

REFERENCES

i) Penetration Test Initial 374 375 368

Final 54 62 58

[1]

Penetration Value 80 81 80

[2]

[3]

ii) Ring & Ball Test Ball 1(o C) 49

Ball 2(o C) 49

Softening Point (To C) 49

[4] [5]

CONCLUSION As of our aim is concern providing a cost effective method for short-term aging by showing normal oven as

261

An alternative method for short- and long-term ageing for bitumen binders by Pramod Kumar Behera, A.K. Singh and M. Amaranatha Reddy AF2903 Highway Construction and Maintenance Laboratory: Binder rheology and ageing by Prabir Kumar Das Standard Test Method for Effects of Heat and Air on Asphaltic Materials (Thin-Film Oven Test) D 1754 – 97 (Reapproved 2002) Standard Test Method for Penetration of Bituminous Materials ASTM D 5 – 06 Test Method for Softening Point of Bitumen (Ring-andBall Apparatus) ASTM D 36

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.262-266.

Analysis of Flexible Pavement using Kenlayer Software for Bypass in Kurnool City Sowjanya and P. Manjula Asst. professor, Civil Engineering Dept, G.Pulla Reddy Engg. College (Autonomous), Kurnool.

ABSTRACT Transportation contributes to the economic, industrial, social and cultural development of any region. Progress follows the line of transportation. Attempts are being made of decentralize the population centers away from the sides of the main transportation routes. Of all the means of transportation, the transportation by road is the only mode, which could give maximum service to one and all. The present study deals with the analysis of flexible pavement using KENLAYER software developed by Dr. Young Huang for a bypass connecting NH 18 and NH 44. The main purpose of this road is to provide a convenient way to the heavy commercial vehicles, with out entering in to the Kurnool city and also reduce the traffic in Kurnool thereby decreasing the delay. The proposed road is at 9.9 Kms from the Kurnool town. In this project the road is categorized as the National High way and it is designed as a flexible pavement according to the IRC guidelines. The total length of project actually is 18 kms. Thickness of the pavement is carried out as per IRC 37:2001 and the stresses and strains are analyzed using KENLAYER software. Keywords— KENLAYER software, flexible pavement, IRC 37 :2001. INTRODUCTION The KENLAYER software programme was introduced by Dr. Young Huang. The KENLAYER computer program can be applied only to flexible pavements with no joint for rigid layers, such as PCC and composite pavements, the KENSLABS program described in chapter should be used. The back bone of KENLAYER is solution for an elastic multilayer system under a circular loaded area. The solutions are super imposed for multiple wheels, applied iteratively for nonlinear layers. as a result KENLAYER can be applied to layered systems under single, duel, dueltandem, or duel-tridem wheels with each layer behaving differently either linear elastic, nonlinear elastic or visco elastic damage analysis can be made by dividing each year in to a maximum of 24 load groups, either single or multiple. The damage caused by fatigue cracking and permanent deformation in each period over all load groups is summed up to evaluate the design life. A major change in KENLAYER is the inclusion of the Mohr's Coulomb failure theory to adjust the stress invariant for computing the elastic modulus. This method is used when the granular base is not subdivided and the stress point is located at the mid height of the layer, instead of at the upper third or quarter point. ELASTIC MULTILAYER SYSTEM Fig. 1 shows an n-layer system in cylindrical coordinates, the nth layer being of infinite thickness. the modulus of

elasticity and the poison’s ratio of the ith layer are E and vi respectively. For axisymmetric problems in elasticity, a convenient method is to assume a stress function that satisfies the governing differential equation and the boundary and continuity conditions. After the stress functions is found, the stress and displacements can be determined. The governing differential equation to be satisfied is fourth-order differential equations. The stress function for each layer has four constants of integration, Ai, Bi, Ci and Di, where the subscript i is layer number. Because the stress function must vanish at an infinite depth, the constants An and Cn should be zero, i.e., the bottom most layer has only two constants. For an n-layer system, the total number of constants or unknowns is 4n-2, which must be evaluated by conditions are that the vertical stress under the circular loaded area is equal to q and that the surface is free of shear stress. The four conditions at each of the n-1 interfaces are the continuity of vertical stress, vertical displacement, shear stress, and radial displacement. If the interface is frictionless, the continuity of shear stress and radial displacement is replaced by the vanish of shear stress both above and below the interface. SUPERIMPOSITION OF WHEEL LOADS Solution for elastic multilayer system under a single load can be extended to cases involving multiple loads by applying the super position principle, Fig shows the plan of a view of a set of dual-tandem wheels, The vertical

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Analysis of Flexible Pavement using Kenlayer Software for Bypass in Kurnool City

Fig. 1: Elastic Multilayer System

stress and vertical displacement under point A due to the four loads can be easily obtained by adding those due to each of the loads because they are all in the same vertical, or z, direction. However, the radial stress σr, the tangential stress σt, and the shear stress τrz,, due to each load cannot be added directly because they are not in the same direction. Damage Analysis Damage analysis is performed for the fatigue cracking and permanent deformation Multiple Axils Due to the large spacing between the two axils, the critical tensile and compressive strains under multiple axles are only slightly different those under multiple axils are only slightly different from those under a single axles is assumed to be one repetition, the damage caused by an 80-KN single axle is nearly same as that caused by 160KN tandem axles or 240 KN tridem axles. Nonlinear Layers It is well known that granular materials and Subgrade soils are nonlinear with an elastic modulus varying with the levels of stress. The elastic modulus to be used with the layered system is the resilient modulus obtained from repeated unconfined or triaxial compression tests. Details about resilient modulus are presented in table. The resilient modulus of granular materials increases with the increase in stress intensity, while that of fine grained soils decreases with the increase in stress intensity. If the relationship between the resilient modulus and the state of

stress is given, a method of successive approximation can be used, as explained previously for the nonlinear homogenous mass. Non linear material properties, which have been incorporated in KENLAYER, are described below. It is well known that most granular materials cannot take any tension. Unfortunately when they are used as a base or sub base on a weaker Subgrade, the horizontal stress at the bottom of these materials are more likely in tension. It should be noted that the use of layered system for nonlinear analysis is an approximate approach. It is desirable to have more exact solution system for the nonlinear analysis is an approximate approach. It is desirable to have more exact solutions so that the results of KENLAYER can be compared. Theoretically, the finite element method should be best solutions for such nonlinear problems but it have serious defects and cannot be used for the accuracy of solution. Program Description KENLAYER was written in FORTRAN 77 and requires a storage of 509k. There are 12 command buttons on the Main Screen. The three on the left belong exclusively to asphalt pavements, while the five on the right apply only to concrete pavements. The remaining four between are for general use. If the same Data Path is used for asphalt and concrete, as in the case of these 12 examples, be sure that the correct file is shown on the Filename box. If file LAY1.DAT is used to run KENSLABS, or SLA1.DAT to run KENLAYER, the program will not run or an error message will appear.

Table 1: Properties of materials

Property Unit weight (KN/m3) Coefficient of earth pressure at rest Poisson’s ratio Modulus (kpa)

Hot Mix Asphalt 0 40 F 700F 1000F 22.75 22.78 22.78

Crushed Stone Base 22

Stiff 19

Subgrade Soils medium soft 18 18

Very soft 18

0.37

0.67

0.85

0.60

0.82

0.82

0.82

0.82

0.27 9660

0.40 3450

0.46 690

0.38 9000

0.45 3105

0.45 3105

0.45 3105

0.45 3105

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

As per IRC, For the CBR 3.6% and total thickness of pavement 640 mm Thickness of a) Bituminous surfacing = 25mm+55mm b) Base course = 240 mm c) Sub base = 320 mm + Sub grade compacted at OMC = 500mm Total = 1140mm For Sample 2 Total thickness of pavement at CBR value of 3.5% and traffic 3.95 msa, as per IRC: 37-2001 =650 mm

Fig. 2: Main screen of KENLAYER Software

EXPERIMENTAL WORK

As per IRC, For the CBR 3.5% and total thickness of pavement 650 mm

Design of Flexible Pavement Thickness Soil samples were collected from the site at every 50m intervals. Liquid limit, plastic limit, proctor and CBR tests were conducted on the collected samples in the soil mechanics laboratory for the design of flexible pavement. The test results are tabulated as below

a) Bituminous surfacing = 25mm+55mm b) Base course = 250 mm c) Sub base = 320 mm + Sub grade compacted at OMC = 500mm Total = 1150mm

Table 7.1: Test results of soil samples

Type test

sample: 1 44% 29% 15% 17.8% 1.76 3.6%

LL PL PI OMC MDD (g/cc) CBR (soaked)

Analysis of Stresses Due to Wheel Load Under the Pavements by Kenlayer Software Figure 7.1 shows the Main Menu of LAYERINP for creating and editing data file. This menu appears when the LAYERINP button on the Main Screen of KENPAVE is clicked. The data is divided into groups and can be found by clicking the appropriate menu. Always start from the left menu to the right because data entered in the left menu may affect the type of form to be used in the right menu. When we finish reading this page, you can use the scrollbar or the PgDn key to read down the page. To edit an existing file click 'File' and 'Open' and a dialog box showing a list of data files will appear.

sample:2 56.2% 39.9 % 16.2% 23.8% 1.53 3.5%

Analysis of Traffic Volume Vehicle damage factor for a plain terrain = 3.5 Distribution factor = 0.75 Growth rate r = 7.5% Traffic in the year of completion of construction = 158 CV/day ( Traffic flow from NH 7 to NH 18 ) Vehicle damage factor, D = 3.5 n = design life of pavement = 15years Cumulative

number

[

]

[

of

standard

axles,

ADF ]

= 3.95 msa

Fig. 3: Main menu of KENLAYER

For Sample 1 Total thickness of pavement at CBR value of 3.6% and traffic 3.95 msa, as per IRC: 37-2001 =640 mm

Give the input data for every data entry file by carefully studying the instructions given. After completing the data entry for a given menu, the 'input' on the label will be

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Analysis of Flexible Pavement using Kenlayer Software for Bypass in Kurnool City

changed to 'done'. Click the 'Save' or 'Save As' button before exit. Input Data Figure 4.shows the input given to KENLAYER software in a graphical form. For the damage analysis of 1 period the analysis of stresses at each layer were carried out. Here the thickness of each layer obtained as per the IRC are given as input data. 1. They are bituminous asphalt layer (80 mm), base course (250 mm), sub base (320mm) and lastly the subgrade which has a infinite thickness. 2. In the ‘Moduli’ file Poison’s ratio and Modulus of elasticity of each layer should be given as input data.

Fig. 5: Input data (sample:2)

3. The data related to wheel loads (i.e., contact pressure, dual and tandam spacings and contact radius are also given in the file ‘loads’.

Output from KENLAYER programme for the above input data :

Fig. 4: Input data (sample:1)

Output from KENLAYER programme for the above input date :

CONCLUSIONS In the present study an approach road to the bypass of NH 18 & NH 44 is analyzed using KENLAYER software. Where a s the depth of pavement is carried out as per IRC 37:2001. 1) The displacements, major principle stresses and principle strains were observed as maximum at the inter face of wearing coarse and base coarse.

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2) The analysis was carried out for sample1 &sample2. It is observed that the displacements are slightly decreased and the stresses were slightly increased at the interface of wearing coarse and base course. Limitations  Poisson’s ratio and elastic modulus of pavement materials are obtained from the text book of Principles of Pavement Design by E.J. YODER.

Scope for Further Studies  Conduct the Triaxial compression test on soil samples and Check whether stresses and strains coming from KENLAYER software are less (safe) than the principle stresses and strains in the soil  Considering the damage and Tridem axle load pavement may be analysed. REFERENCES

 Dual tandem vehicle load is considered as maximum wheel load on the top of the pavement.

[1]

 Damage analysis is not considered as the part present study.

[2] [3] [4]

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“Guidelines for the Design of Flexible Pavements” IRC37:2001. KENLAYER Computer Program by YANG H. HAUNG, university of Kentucky, Englewood Cliffs, New Jersey. “Soil Mechanics and Foundation Engineering”, K.R. Arora, Standard Publishers. ‘’ Principles of pavement Design’’ by E.J. Yoder.

Emerging Technologies in Infrastructure

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.269-274.

Review of Sensor Technologies in Infrastructure Construction K. Madhavi Reddy1, K. Jayasree2 and B. Sridhar3 1 Academic Assistant, 2Associate Professor, 3Professor and Head Department of Civil Engineering, Vasavi College of Engineering, Hyderabad.

ABSTRACT Recent advances in technology have enabled the development of automated equipments, means and methods in infrastructure construction. Although adaption of automation in the building construction sector has been slow, principles of industrial automation are applicable to this domain, both to building construction, civil engineering, and to prefabrication of construction components. Improved sensor technologies offers new possibilities to cover various needs and operations taking place throughout the infrastructure life cycle. This paper reviews a survey of potential sensor technologies for building construction automation, highlighting their potential also with contributions from robotics. INTRODUCTION Effective utilization of technologies is essential for economic development of any nation. Engineering skills possessed by community is vital. It can be said that most of the infrastructure need detailed planning adoption of latest technologies with deployment of modern machineries for better reliability, quality and speed. This can be provided only by sophisticated technologies and their utility to get the real time assessment and evaluation during construction and maintenance. Wireless sensor networks(WSN) are the networks of smart and wirelessly connected devices equipped with reduced communication, computation and sensing capabilities for communication control and monitoring applications. A variety of wireless technologies have used in the construction industry. These technologies include circuit switched technologies. Health and safety are the major issues in any industry especially in the construction industry. This occurs due to fall of material, wrong use of construction material in the construction. These can be prevented by use of sensor applications in the construction. An important application of WSN’S that attracts the interest of construction process is the measurement of relative humidity (RH) in the curing process of concrete slabs or precast production. The curing of concrete is one of the most critical elements within the building process and a system that could reliably deliver the status of the curing would greatly optimise the work flows and reduce the failure rates. The common practice related to the measurement of the (RH) is to use manual methodologies or involve a specialist humidity consultant. Due to the inefficiency of these approaches in terms of accuracy and flexibility, a new WSN technology is used to ease the monitoring process by signalling the status of curing.

The construction industry is characterised by a number of problems in crucial fields such as health, safety and logistics. Since these problems affect the progress of construction projects, the construction industry has attempted to introduce the use of innovative information and communication technologies on the construction site. RFID is innovative scientific technology with a number of scientific and technical fields. This belongs to the field of wireless sensing technologies and its operation is based on transmission of sensing and electro-magnetic energy. RFID tagging is a technology capable of tracking items. The technology has been applied on the construction site for various applications, such as asset tracking. LITERATURE RIVIEW Westermo and Thompson (1997) presented a technology using peak strain sensors, which can be used to assess structural health. Their network consisted of three gauges, which, along with a digital junction, were installed on a three-storey, wood-frame building. The system was powered by a 12-VDC battery pack; it was intended to routinely interrogate all sensors and store pertinent data or changes on each cycle. To transmit the information, the wireless system was connected to a cellular modem that was set to receive incoming calls from a PC for data downloading or reprogramming. Pines and Lovell (1998, 1999) discussed an approach using sensors and wireless communication technology to monitor the health of large civil structures remotely using spread-spectrum wireless modems, data communication software, and conventional strain sensors. Their work described examples of condition-based health-monitoring systems that use cellular and through wire for data retrieval. A simple yet inexpensive device was realized and validated on a laboratory test structure at a range of

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up to approximately communication signal.

1

mile

without

loss

of

Williams et al. (1998) presented a novel idea in which self-sufficient (i.e., generates its own power) wireless sensors were achieved. In their approach, the vibrational energy of the structure was used to power an accelerometer. The feasibility studies on reinforced concrete bridges indicated that the resonant frequency of the electric generator should match the fundamental frequency of the bridge so as to maximize the power generation. Subramanian (1997) and Varadan et al. (1997, 1998, 1999, 2001) showed the wireless integration of MEMS and surface acoustic wave (SAW) devices employing inter digital transducers (IDT). These devices have a unique advantage in that they do not require an on-board power supply at the sensor location. The acceleration is measured when a wave (produced by a wave generator localized at the base station) is reflected by the sensor; the phase change in the reflected wave is proportional to the acceleration. This sensor has a wide dynamic range. The fabrication of the accelerometer is discussed. The wireless accelerometer provides an attractive opportunity to study the response of a “dummy” in automobile crash tests and may be potentially useful in the deployment of “smart skins” (intelligent fuselage) for aircraft. Krantz, et al. (1999) presented the Remotely-Queried Embedded Microsensor (RQEM). The objective of this research was to develop a microsensor that could retrieve data from embedded strain gauges. This system consisted of two main parts: the sensor package and the reader. The sensor package consisted of a microsensor (conventional strain gauge), signal conditioner, receiver/transmitter, data encoder, and power supply. The reader consisted of an external antenna coil attached to a Trovan RFID Tag Reader. The measurement occurred when the reader antenna was placed 3 - 12 inches from the embedded sensor. Lemke (2000) described a remote vibration monitoring system integrated with the internet in order to acquire field data, which was then uploaded to a web server using a wireless connection. The selection of the ground motion transducer with respect to the desired frequency response was discussed. The network was wired, but the transmission from the field site was performed by cellular telephony. Battery power considerations were also studied and the results showed that the system could be dialed just over 5000 times. With a peak transmission every thirty minutes, the system could last for over 200 days. Oshima et al. (2000) also presented a monitoring system that could be interrogated via a mobile telephone. This system consisted of a photocell, an accelerometer, and a displacement sensor. The sampling frequency was 200 Hz. Experimental results for the structural frequencies and

mode shapes were presented that closely agreed with the analytical results. A comparison between a fiber-optic strain sensor and a standard strain gage for crack propagation was presented. A difference of 5–10% in strain measurements between theses sensors was found. Evans (2001) provides a very good compendium of the various alternatives that can be used for wireless transmission of data, including free bandwidth frequencies, such as 915 MHz and 2.45 GHz, cellular phone lines, two-way paging, and satellites services. A description of the available sensors, such as the micro machined and force balance accelerometers, is also provided. The author indicates the performance and cost of each one of the wireless devices. Finally, two examples of wireless networks are presented: an application to a highway bridge used to determine damage, and free-field measurements to produce a real-time seismicity map for Oakland, California. Mita and Takahira (2001) presented a wireless peak strain and displacement sensor.This sensor consisted of a variable capacitor made of an outer cylinder and an inner cylinder, in which the capacitance depended on the overlapping length. In order to retrieve data, a inductor was added to the variable capacitor, creating a resonant circuit. This circuit was excited by a dip meter and a frequency was read (a dip meter is the equipment which measures the frequency of the resonance circuit). A comparison of measurement results between a laser sensor and the peak strain sensor was presented. The agreement of these measurements assured the feasibility and accuracy of the system. Some of the first efforts in developing a smart sensor for civil engineering applications were presented by Straser and Kiremidjian (1996, 1998), Straser et al. (1998), and Kiremidjian et al. (1997). This research sought to develop a near real-time damage diagnostic and monitoring system which evaluated both extreme and long-term structural health. Two types of monitoring systems were identified: (i) extreme event, and (ii) longterm monitoring systems. Damage detection methods were further categorized into global and local methods. Several damage detection methods were discussed, as well as strategies for optimal sensor placement. The authors noted that one complicating aspect of long term monitoring indicated that the characteristics of a structure could vary significantly due to environmental changes such as loading, boundary conditions, temperature, and humidity. The hardware was designed to acquire and manage such data, while the software was designed to facilitate damage detection diagnosis. The proposed network provided ease of installation, low per unit cost, portability, and broad functionality. The sensor unit consisted of a microprocessor, radio modem, data storage, and batteries. One of the problems in having many sensors trying to communicate simultaneously with the base is time

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synchronization of the signals. To solve this problem, a second AM type radio was implemented to perform synchronization. The authors found that the time delay for this approach was 0.05 millisecond, which for the frequency spectrum of interest, namely 1- 50Hz, represented a maximum phase delay of less than one degree. To save battery life, the sensor unit remained in sleep mode most of the time, periodically checking its hardware interrupt to determine if there were external events that require attention. The analysis software determined the maximum inter-story drift ratio over the entire time history, as well as the cumulative normalized Arias Intensity to measure of the total kinetic energy of each floor. A damage detection algorithm called DIAMOND was developed in MATLAB. Maser et al. (1997) proposed the Wireless Global Bridge Evaluation and Monitoring System (WGBEMS) to remotely monitor the condition and performance of bridges. WGBEMS used small, self-contained, battery operated transducers, each containing a sensor, a small radio transponder, and a battery. The complete system consisted of a local controller placed off a bridge with several transducers distributed throughout the bridge. The data collection at the transducer involves signal conditioning, filtering, sampling, quantization, and digital signal processing. The radio link used a wide band Agre et al. (1999) presented a prototype wireless sensor node called “AWAIRS I” This smart sensor could support bidirectional, peer-to-peer communications with a small number of neighbours. The current device consists of a processor, radio, power supply and sensors (seismic, magnetic and acoustic). Multiple portals for transporting information in or out of the sensor network can be established. The authors discussed some of the networking problems in a wireless sensor network, which include limited battery energy, size of the overhead of the messages communication protocols, and non-real-time delivery, among others. This prototype will run approximately 15 hours continuously on two 9V batteries. The time-division multiple access (TDMA) scheme used allows nodes to turn off their receiver and/or transmitter when they are not scheduled to communicate. Mitchell et al. (1999) presents a wireless data acquisition system for health monitoring of smart structures. The authors developed a microsensor that uses an analog multiplexer to allow data from multiple sensors to be communicated over a single communication channel. The data is converted to a digital format before transmission, using an 80C515CO microcontroller. A 900 MHz spread spectrum transceiver system, capable of transmitting serial data at the rate of 50Kbps, is used to perform the wireless transmission, over a range of approximately 0.25 miles. Damage can be detected via variations in the natural frequencies of the structure. The system employs the Numerical Algorithms for Subspace State Space

System Identification (NASID) method. The main advantage of this algorithm is that it is non-iterative and does not involve nonlinear optimization. This health monitoring system has been applied to a cantilever beam in which a loss of mass represents the damage of the structure. Mitchell et al. (2001) have continued this work to extend the cellular communication between the central cluster and the web server, allowing web-control of the network. The proposed Web-Controlled Wireless Network Sensors (WCWNS) consist of two main parts: the wireless network sensors and the web interface. Building on the work of Kiremidjian et al. (1997), Lynch et al. (2001) demonstrated a proof-of-concept wireless sensor that used a standard integrated circuit component. This unit consists of an 8-bit Motorola 68HC11E1 microcontroller with a 3MHz CPU that can accommodate a wide range of analog sensors. The systems communicate via direct sequence spread spectrum radio multiplied by a pseudo noise spreading sequence (also known as a chirp code). This approach allows multiple users to access the same bandwidth simultaneously without interference. For the spread-spectrum modems to operate properly, both the sending and receiving modems must be self-synchronized and follow a prescribed sequence of frequencies. Some units use the ADXL210 accelerometer along with a duty cycle modulator that provides a 14-bit output with an anti-aliased digital signal. In other units, a high performance planar accelerometer is used along with a 16-bit A/D converter. This accelerometer has a resolution of 20 μg at a bandwidth of 650 Hz. The whole system can be accommodated within a sealed package with a roughly size of 5” by 4” by 1” The sensor unit was validated through various controlled experiments in the laboratory. Kiremidjian et al. (2001) indicates that pushing data acquisition and computation forward is fundamental to the smart sensing and monitoring systems but represents radical departure from the conventional instrumentation design and computational strategies for monitoring civil structures. CATEGORISATION OF SENSOR TECHNOLOGIES USED IN CONSTRUCTION Different types of sensors that can be used are classified as below.  Thermal sensors  Radio frequency sensors  Magnetic sensors  Laser frequency sensors  Ultra sound sensors  Electric sensors

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Some of the sensor technology used in the construction process are : Thermal Sensors  Measurement of relative humidity in the curing process of concrete slabs or precast production  Highly accurate techniques to measure water level inside the concrete during its drying Radio Frequency Sensors  Propagation variations of radio-signals concrete when humidity increases

through

 Ground penetrating radar (GPR) GPR is the general term applied to techniques that employ radio waves, typically in the 10 to 2000MHz, to map structures and features buried in the ground or manmade structures. It uses electromagnetic waves generated into surface of the object studied by means of antenna moving along the surface. Configuration consists of an antenna connected via a signal or power cable to a computer based system control unit. Surveys are conducted by towing an antenna across a surface as it is repeatedly transmitting radar pulses into the subsurface. Whenever a radar pulse strikes a boundary interface of contrasting dielectric, a portion of the pulse is reflected back to the surface and a receiving antenna. Subsurface profiles will be generated by simultaneously towing the antenna across the surface and displaying the resulting echoes of individual pulses as a composite image displays on the controls units monitor. GPR uses the same principle by processing the signal reflected from various depths of a structural element.

Magnetic Sensors  Equipping construction helmets with sensors can detect onset of carbon dioxide poisoning This wearable computing system in helmet protect the workers and tool users from carbon dioxide poisioning which results to a serious threat in industry. All this happens because of exhaust from the gasoline powered hand tools that easily built up in enclosed places. Installation of pulse oximetry in the typical wearable helmet helps to diagnoise the workers blood gas saturation levels. The use of this sensor in the helmet showed that it will warn from occurring of carbon dioxide poisioning.

Fig. 1: Construction helmets with sensors can detect onset of carbon dioxide poisoning

Laser Frequency Sensors Propagation of light waves through concrete pipes and assume to know the length of the pipe through proper channel

This is also applicable for

Ultra Sound Sensors

 Measure thickness of slab

Long Range Ultra-Sonic testing(LURT) is a sensor that can measure significant lengths of pipe from a single point to rapidly locate areas of corrosion

 Void identification  Inspection, locating metallic and non-metallic targets in walls, ceilings and floors  Inspection of structures: bridges, towers columns and beams. GPR is thus valuable in locating defects and voids in concrete structures. Masonry structures can be scanned for predicting problems in inner layers of the structure. Any void or crack in concrete or in any product results in an interface with air or moisture with a variation if in dielectric constant. Reinforcement embedded in concrete present interfaces with large variation in conductivity due to larger density of steel then of concrete. In such cases distinct and clear images indicate the location of subsurface objects such as pipes and bars or even cracks and voids. Corrosion of embedded steel in concrete too can be located with the help of radar image.

Fig. 2: Long Range Ultra-Sonic testing

In LRUT, a pulse guided ultrasonic wave mode is propagated in a pipe wall from a ring of equally spaced ultrasound probes supported by a collar wrapped around the pipe. It is a technique in which the loss of metal

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features is detected such as corrosion and erosion in pipes. significantly it can measure up to length of 350m long pipe at single point in which the areas are corroded. It is capable of detecting 9% of metal loss, once the area which effected is located then the inspection is done to know the reasons for defects. Magnetic Sensors Soil moisture sensor is used to measure the water content in the soil the instrument used for this is a frequency domain sensor which consist of an oscillating circuit. The sensing part is embedded in the soil and the cable is connected to the operating system. The moisture content is thus detected by the data logger. thus the sensor is most widely used in the western countries as it gives 100% probability result. Sensors can be used in order to alert the owner of a building when there is emission of large amount of gas or if there is smoke. In this case, they can alert the owner of the house by triggering the alarm. The detection of smoke can be done by the use of optical and ionisation detectors. Gas detection is achieved by the use of gas sensors which are capable of sensing different gas particles. An array of gas sensors which consists of semiconductor metal oxide sensors for the detection of CO, H2 and NH3, can be used on this case. A signal-processing method is also used in order to distinguish situations of fire and non-fire. The monitoring of the living conditions inside a house is important for its residents. Wireless sensor networks can be used in order to monitor the light, the temperature and the indoor air pollution so that useful conclusions are extracted about the quality of the indoor environment. The American Society of Heating, Refrigerating and AirConditioning Engineers (ASHRAE) has deployed a wireless sensor network in a part of the Pacific Northwest National Laboratory at Washington in order to examine the advantages and disadvantages of the technology in heating, ventilation and air conditioning (HVAC) systems.

the areas which are to be monitored, which records each tag’s position. The system is for indoor use only. [1]

[2]

[3]

Mita, A. and Takahira S. (2001). “Peak strain and displacement sensors for structural health monitoring.” Proceedings of the 3rd International Workshop on Structural Health Monitoring: The Demands and Challenges. 1033–1040. Kiremidjian, A.S., Straser, E.G., Meng, T.H., Law, K. and Soon, H. (1997). “Structural damage monitoring for civil structures.” International Workshop – Structural Health Monitoring. 371–382. Maser, K., Egri, R., Lichtenstein, A. and Chase, S. (1997). “Development of a wireless global bridge evaluation and monitoring system (WGBEMS).” Proceedings of the Specialty Conference on Infrastructure Condition Assessment: Art, Science, Practice. 91–100

CONCLUSION Wireless Sensor Networking Technology is a field which is still at the research stage in the construction industry. It is characterised by a number of advantages, such as the quick handling of information and the integration of a number of processes, but also by a number of disadvantages, such as routing issues especially in large sensor networks. However, even in these cases, the introduction of a number of techniques, such as ground penetrating radar and Ultra wide band, has enabled the resolution of these issues. In general, the application of the Wireless Sensor Networking technology in the field of construction is expected to produce a number of benefits. REFERENCES [4]

[5]

[6]

Wireless Sensor Networks can be implemented for the purpose of tracking of items on the construction site. In addition, they are capable of gathering data, either for the purpose of monitoring the site or for reasons of item identification. Wireless sensor networks are able to provide security on the construction site, either by constantly monitoring the site or by alerting the engineers when an item has been stolen.

[7]

Researchers have developed a new tool to improve safety on construction site using remote sensing technology in tracking things to monitor movement in the construction site. The use of ultra wide-band(UWB) radio frequency develops a new system which helps to reduce accidents in the work place and also helps in recovery of theft items. The tag readers or transceivers are placed in the corners of

[9]

[8]

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Westermo, B. and Thompson, L.D. (1997). “A peak strain sensor for damage assessment and health monitoring.” International Workshop on Structural Health Monitoring. 515–526 Pines D.J. and Lovell P.A. (1998). “Conceptual framework of a remote wireless health monitoring system for large civil structures.” Smart materials & Structures Vol. 7. No. 5. 627–636 Williams, C.B., Pavic, A., Crouch, R.S. and Woods, R.C. (1998). “Feasibility study of vibration-electric generator for bridge vibration sensors.” Proceedings of the 16th International Modal Analysis Conference IMAC. 1111– 1117. Subramanian, H.; Varadan, V. and Varadan, V. K. (1997). “Wireless remotely readable microaccelerometer.” Proceedings- SPIE The international society for optical engineering. 3046:220–228 .Krantz, D., Belk, J., Biermann, P. J., Dubow, J., Gause, L. W., Harjani, R., Mantell, S., Polla, D. and Troyk, P. (1999). “Project update: applied research on remotely queried embedded micro sensors.” Proceedings of SPIE The International Society for Optical Engineering, v3673 Lemke, J. (2000). “A remote vibration monitoring system using wireless internet data transfer.” Proceedings – SPIE, International Society for Optical Engineering. 3995:436– 445

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development [10] Oshima, T., Rahman, M. S., Makami, S., Yamazaki, T., Takada, N., Lesko, J.J. and Kriz, R.D. (2000). “Application of smart materials and systems to long-term bridge health monitoring.” Proceedings – SPIE The International Society for Optical Engineering, issue 3995:253–263. [11] Evans, J.R. (2001). “Wireless monitoring and low-cost accelerometers for structures and urban sites.” Strong Motion Instrumentation for Civil Engineering Structures [12] Evans, J.R. (2001). “Wireless monitoring and low-cost accelerometers for structures and urban sites.” Strong Motion Instrumentation for Civil Engineering Structures. 229–242 [13] Agre, J.R., Clare, L.P., Pottie, G.J. and Romanov, N.P. (1999). “Development platform for self-organizing

wireless sensor networks.” Proceedings of SPIE - The International Society for Optical Engineering. Apr. 8–Apr. 9 1999. Orlando, FL, USA. 3713:257–267. [14] 12.Mitchell, K., Sana, S., Balakrishnan, V.S., Rao, V. and Pottinger, H.J. (1999). “Micro sensors for health monitoring of smart structures.” SPIE Conference on Smart Electronics and MEMS. 3673:351–358. [15] Mitchell, K., Dang, N., Liu, P., Rao, V. and Pottinger H.J. (2001). “Web-controlled wireless network sensors for structural health monitoring.” Proceedings - SPIE The International Society for Optical Engineering. 4334: 234– 243. [16] Kiremidjian, A.S., Kenny, T.W., Law, K.H. and Lee, T. (2001). “A wireless modular health monitoring system for civil structures.” Proposal to the National Science

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Construction Techniques and Management

Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.277-281.

Cost Estimation using Fuzzy Logic M. Venu Gopal1 and V.S.S. Kumar2 1

Associate Professor, Civil Engineering Department, M.V.S.R. Engineering College, Nadergul, Hyderabad. 2 Principal, University College of Engineering (Autonomous), Osmania university, Hyderabad. Email: [email protected]

ABSTRACT Decisions in construction industry take place under conditions of risk and uncertainty. Financial appraisals of long term duration infrastructure projects are made using a variety of assumptions about the future. Some of these assumptions may be statistical in nature even if statistical data is not used in reaching the assumption and some are considered opinions based on experience and knowledge. The construction contractors face situations in which there may be statistical data available. In such circumstances, it is possible to attach probabilities to alternative outcomes and decisions made under such situations deal with random uncertainty. However, all uncertainty is not random in nature. Some forms of uncertainty associated with complex systems like environmental issues, costs related to macro and micro economic issues which knowledge experts address linguistically in the decision making process is non random in nature. The decisions in such situations are made under very high uncertainty. The cost estimation starts with a realistic assessment of all uncertainties associated with the data using fuzzy logic. Cost estimation of concrete is demonstrated using fuzzy logic approach. INTRODUCTION Decision making is most important scientific, social, and economic endeavor. Selecting correct alternative amongst available choices is the essence of any decision making process under uncertainty. The problem in making decisions under uncertainty is that the bulk of the information about the possible outcomes, about the value of new information, about the way the conditions change with time, about the utility of each outcome, and about preferences for each outcome is typically vague, ambiguous and otherwise fuzzy. Here an attempt is made for making decision in fuzzy environment. There is a need to incorporate fuzziness in human decision making, as originally proposed by Bellman and Zadeh (1970). In most decision situations the goals, constraints, and consequences of the proposed alternatives are not known with precision. Much of this imprecision is not measurable, and not random. The imprecision can be due to vague, ambiguous, or fuzzy information. Methods to address this form of imprecision are necessary to deal with many of the uncertainties within humanistic systems. UNCERTAINTY Decision making in engineering involves uncertainty and it is important and diverse. Uncertainty arises because of the gap between the information required to assess an outcome and the information possessed by the decision maker. Availability of information that is necessary for reducing the complexity of the system to a manageable level is expressed in uncertainty. Therefore the concept of uncertainty is concerned with complexity and

information. The uncertainties can be broadly categorized into two types: Random uncertainty and non- random uncertainty. Random uncertainty is also termed as the predictable uncertainty for the reason that it follows the characteristics of random process in which an outcome of a process is only a matter of chance. The prediction of risk associated with this uncertainty is possible quantitatively based on the availability of historical data, information and experience. In such assessment, the accuracy of results is expressed in terms of confidence limits. This random uncertainty can be modeled by using statistics and probability theory. The non-random uncertainty arises due to incomplete data, imprecision, non availability of data. This leads to unpredictability of outcome. Such unpredictable uncertainties are assessed qualitatively as enough information is not available to predict the risk associated quantitatively. The project complexity in construction industries which lacks the back ground of experience of similar projects and past records because of which the outcome of a situation becomes uncertain. Such uncertainty condition is difficult to assess compared to random uncertainty. For example assessment of variations in ground conditions, price escalations, labor productivity, wages, and weather conditions etc., This uncertainty can be subjectively assessed and evaluated by the decision maker in consultations with knowledge experts. The non-random uncertainty is broadly categorized (Klir and Folger, 2004) into vagueness and ambiguity.

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Vagueness is associated with the difficulty of providing a sharp and precise distinction of a specific event or phenomenon due to complexity involved in the project. The other related words associated with vagueness are fuzziness, haziness, cloudiness, unclearness, indistinctiveness and sharplessness. The ambiguity describes the situation in which there is difficulty in making a specific selection or decision between two or more related alternatives due to their ambiguity. Some of the concepts connected with ambiguity are nonspecificity, one to many relation, variety, generality, diversity and divergence. The ambiguity is classified into three categories, 1. Non-specificity in evidence, 2. Conflict or dissonance in evidence and 3. Confusion in evidence METHODS TO MODEL UNCERTAINTY Methods to model uncertainty are classified as classical set theory, probability theory, fuzzy logic and set theory, neural networks, neuro-fuzzy techniques etc. Probability theory is a simple and good approach to represent information or knowledge whose boundaries are clearly defined. In probability theory, there is a need to assume correlation among all input variables and there is disadvantage in sensitivity to uncertainty about probability distribution function of input variables (Ferson, 2002). Random uncertainty is modeled by using statistics and probability theory. This approach provides rigorous tools to evaluate the statistics of the model. However, this method requires development of probability density function for each uncertain parameter and also all possible dependencies between the uncertain parameters. Such knowledge and information is rarely available. On the other hand, modeling uncertainty using fuzzy arithmetic is computationally simple, not very sensitive to moderate changes in the shapes of input distribution and does not require analyst to assume particular correlation among inputs. Therefore Fuzzy set theory can be used to circumvent the limitation due to the choice of a unique probability density function. The uncertainty due to lack of information (stochastic character) is addressed appropriately by statistics and probability theory. This type of probability is essentially based on set theoretic considerations. Koopman’s probability refers to the truth statements and therefore is based on the logic. The events (elements of sets) or the statements are assumed to be well defined in both the types of probabilities. This type of uncertainty is also called the stochastic uncertainty and is concerned with the usage of the linguistic words for the description of the events, perceptions or statements. This is called fuzziness in fuzzy set theory (Zimmermann 2001). Fuzzy set theory is also known as possibility theory which is used to represent knowledge or information whose boundaries are not clearly defined.

The complexity associated with large amount information coupled with uncertainty due to long term duration of projects are part of the future construction activity and this becomes the ground for many of the problems that the industry faces. The fuzzy set theory is very much useful in such situations. FUZZY SET THEORY Fuzzy Set Theory was first introduced by Lofti Zadeh in 1965 to convert the linguistic descriptions of complexity associated with real world projects into useful mathematical propositions for assessing, predicting or controlling the system behavior. A fuzzy logic proposition is a statement involving some concept without clearly defined boundaries. Linguistic statements that tend to express subjective ideas and that can be interpreted slightly differently by various individuals typically involve fuzzy proportions. Statements describing low heat, Medium heat, and High heat can be used as example of fuzzy prepositions and these prepositions are assigned to fuzzy sets. Fuzzy logic theory provides foundation for approximate reasoning with imprecise propositions using fuzzy set theory as principal tool. In classical set theory, the grade of membership of an element is binary either one or zero. Here, precise boundaries exist that separate the elements belonging to the set and not belonging to the set. For example, the grade of membership of element ‘x’ in set A in classical theory is described by its membership function µA(x) in the following manner: 1, if the element x belongs to set A µA(x) =

(1) 0, if the element x does not belong to set A

However, it is difficult to make a sharp distinction between the members and non members of a set. Here, Zadeh introduced the concept of degree of membership in the range between 0 and 1. The infinite number of values in between the end points represent various degrees of membership of element x in a fuzzy set. This value or grade of membership indicates the degree to which an element belongs to a fuzzy set (Paek et al.1993, Ayyub and Haldar, 1984). Such sets which take into account grades of membership (strength of belongingness of element to the set) are defined as fuzzy sets. Zadeh (1965) defined a fuzzy set as “ a class of objects with a continuum of grades of membership […] and characterized by a membership (characteristic) function which assigns to each object a grade of membership ranging between zero and one. Zadeh (1965) provided the following definitions related to fuzzy sets. Suppose X is a space of objects and a generic element of X is denoted by x. Then fuzzy set A is defined as a set of ordered pairs A= {x, µA(x) | x

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(2)

Cost Estimation using Fuzzy Logic

where µA(x) is the grade of membership function of element x in fuzzy set A. The membership has grades in the real continuous interval [0,1] i.e., µA(x) [0,1]. The degree of belongingness of element x to the fuzzy set A is represented by the membership function. Therefore the central theme of fuzzy set is development and construction of membership function (Paek et al. 1993). Zadeh (1965) extended the definitions for ordinary sets to derive definitions for fuzzy sets. These definitions are consistent with topological concepts such as equality, complementation, containment, union, intersection, algebraic product, and algebraic sum, normality, support, relation, composition, mapping, convexity, and concavity. FUZZY NUMBER (MEMBERSHIP FUNCTION) A fuzzy number is continuous fuzzy set that contains two properties: (1) convexity and (2) normality. These two properties make the concept of fuzzy numbers attractive and naturally suitable for modeling imprecise quantity such as “approximately one lakh rupees” or “more or less than fifty thousand rupees”. Theoretically fuzzy numbers can take various shapes. In modeling real life problems, however, linear approximations such as the trapezoidal and triangular fuzzy numbers are frequently used. A fuzzy number is also defined as a bell-shaped, triangular and trapezoidal shaped fuzzy set representing a central value. Membership functions (MFs) characterize the fuzziness in a fuzzy set whether the elements in the set are discrete or continuous in a graphical form for eventual use in the mathematical formalisms of fuzzy set theory (Ross 1997). The main features of membership function (Fuzzy Number) are as shown in Fig. 1. There are many ways to graphically represent the membership function that describe fuzziness. There are more ways to assign membership values or functions to fuzzy variables than there are to assign probability density functions to random variables. Core (most likely interval) 1.0

µA(x)

Domain of consequence of α - cut α – cut level

0.0

sets d) Neural Networks e) Genetic algorithms f) Inductive reasoning g) Soft partitioning h) Meta rules i) Fuzzy statistics. Out of all the above methods the assignment of membership functions to fuzzy variables based on experience and intuition of human is one of the fundamental issues in the FST. Constructing membership function is mainly dependent on the knowledge acquisition from knowledge engineer and it involves one or more experts in the application area and knowledge engineering. The membership function assessment involves eliciting subjective information about parameters of interest in each work package of contract from an estimator, and elicitation is a corner stone of fuzzy set theory. The literature is rich in this topic (e.g. Kaufmann and Gupta 1988; Pedrycz and Gomide 1998). In these methods, experts are expected to give answers to some questions necessary to construct the MF of the variable under consideration. For example, Kaufmann and Gupta (1985) proposed the answering of the following three questions for the subjective construction of membership function. What is the smallest value given to the uncertain variable? What is the highest value? If we are authorized to give one and only one value, what value should be given? The above questions lead to construction of a triangular/Trapezoidal fuzzy number and this can be refined to suit the subjective variable of the problem. Based on the above questions, an expert gives the smallest value, the highest value and the value with maximum level of presumption. Therefore it is the triangular numbers that are more realistic to use. The α-cut is the horizontal cross section at various levels of membership function. The membership value is not simply a quantitative variable. Its measurement level is complex and does not fit easily in the standard classification of scale types. A membership is not a probability despite being normalized to the unit interval. Probability gives the mass of a particular event. In a normalized space, a membership is a generalized truth value. when a fuzzy number maintains the range and the shape of a bounded or a truncated probabilistic distribution, the defuzzified value of the fuzzy number using centre of area will be equal to the mean value of the probabilistic distribution. The variance of the fuzzy number is also equal to the variance of the related probability distribution. Methods to assign membership functions are broadly subdivided into the following three categories. DIRECT ASSIGNMENT METHOD

x Support (largest likely interval)

Fig. 1: Features of Fuzzy Number

Some of the methods described in the literature to assign membership values or functions to fuzzy variables are: a) Intuition b) Inference c) Rank Ordering d)Angular fuzzy

In this, a judge or a Knowledge Engineer provides a numeric or linguistic membership value based on his experience or knowledge after considering the objects and relevant evidence. The main disadvantages of direct assignment (Verkuilen 2005) are 1) interpretation of directly scaled numbers is difficult and contentious issue. 2) It is too hard for the judges to do reliably, particularly

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development

for very abstract concepts such as economic development, forecasting cost over long-term periods etc., 3) the direct assignment with regard to other methods of assignment is frequently biased. It is also argued that direct assignment is to tap into a judge’s expertise, which in a sense is a bias. 4) Many direct scaling methods do not generate uncertainty estimates that would allow users to put error bars on assigned scores. To overcome this disadvantage, a simple procedure can be developed to elicit a range of possible values from the judge (e.g. low, medium and high values of membership for each variable). 5) Combining the results of direct assignment by multiple judges to generate a composite membership functions is not recommended if the standard deviation is quite wide. The differences probably reflect the systematic differences in meaning across subject experts. INDIRECT SCALING METHOD Indirect scaling method elicits responses of some kind about the objects to be scaled from judges and then applies a model to the judgments to generate scale values. The cost involved is high in this methodology due to data gathering and model formulation. TRANSFORMATION METHOD In this method, a numerical variable is mapped into membership values with a theoretically motivated transformation. Transformation often makes use of statistical data gathered. Uncertainty estimates in the original variable should be propagated through the transformation to give uncertainty boundaries for the transformed membership. EXAMPLE OF COST ESTIMATION USING FUZZY NUMBER Construction of membership function for fuzzy number is illustrated by following example: The cost of concrete per cubic meter can be arrived at depending upon the prices of raw materials estimated. The prices of raw materials are again depending on the season, fluctuation in demand, labor cost and inflation etc. The four different estimations of concrete are made by the cost engineer and are represented as fuzzy number. 2600

2800

1.0

Domain of Consequence at α-cut α-cut level

µA(x)

0.0 2400

2600

2800

3200

x Fig. 2: Membership Function for Price of Concrete

The smallest value for the price of concrete may be Rs.2400=00, the highest price may be Rs.3200=00, and the most likely interval may be in the range of two values i.e., Rs.2600=00 to Rs.2800=00. The above information may be expressed as fuzzy trapezoidal number as shown in the Fig.2. In the membership function shown, the largest likely interval is between Rs.2400=00 and Rs.3200=00, the most likely interval is between Rs.2600=00 and Rs.2800=00. The membership function also indicate that the cost of concrete approximately lies between Rs.2600=00 and Rs.2800=00 and is definitely above Rs.2400=00 and is certainly below Rs.3200=00. The sloped lines are part of the trapezoidal fuzzy number which defines the degree of belongingness of the element x to the crisp set. The engineer has given different belief values to different estimates between Rs.2400=00 and Rs.2600=00, Rs.2800=00 and Rs.3200=00. The flat or uniform range in the Fig. 2 indicates that there is lack of precision in determining the exact belief value for the variable (x) thereby decision becomes ambiguous. Here in this example, cost engineer represented the range with same preference to all values between Rs.2600=00 and Rs.2800=00. The cost engineer would have given different membership values to different estimates between Rs.2600=00 and Rs.2800=00 had there been a precision in the information for decision making. Therefore the decision making is most ambiguous between the range Rs.2600=00 and Rs.2800=00 of the trapezoidal fuzzy number. The ambiguity reduces when the core width reduces and when the core width is zero; the fuzzy number becomes triangular fuzzy number. The triangular fuzzy number is less ambiguous than trapezoidal fuzzy number. When the support range and core range reduces to a point, the number becomes a crisp number. The number is a uniform fuzzy number when the width of core and support are equal and is called a rectangular Membership Function which represents only one interval of confidence and the degree of belief of any number in that interval is same and decision makers’ choice becomes most ambiguous. This is due to the fact that there is more than one local maximum in membership function. CONCLUSION Fuzzy set theory and fuzzy logic plays a vital role in combining the subjective and objective knowledge of estimator. Estimation of construction costs is frequently done in the early stages of construction work in order to inform project owner of their likely financial liability. Early stage forecasts are by their nature imprecise and generally dependent on the skill of the forecaster. Fuzzy formulation is useful to represent the linguistic assertions. Membership functions can be developed numerically to build the system. Membership function of the estimated cost provides insight into the risk associated with the estimate. Low and high truth values, along with spread of

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Cost Estimation using Fuzzy Logic

the membership function over the universe of discourse for cost suggest relative uncertainty. The membership function of the cost can be used as an alternative to the traditional ways of estimation of risk associated with the uncertainty. REFERENCES [1]

[2] [3]

[4]

Ayyub, B.M., and Haldar, A. M. ASCE. (1984). “Project Scheduling Using Fuzzy Set Concepts.” J. Constr. Eng. Manage., 110(2), 189-204. Bellman, R., and Zadeh, L. (1970). “Decision Making in a Fuzzy Environment.” Management Science, 17, 141-164. Ferson, S. (2002). “Ramas risk calc 4.0 software: Risk assessment with uncertain numbers.” CRC, Bocaraton, Fla. Kaufmann, A., and Gupta, M.M. (1985). “Introduction to fuzzy arithmetic, theory and applications.” Van Nostrand Reinhold, New York.

[5]

Kaufmann, A., and Gupta, M.M. (1988). “Fuzzy mathematical models in engineering and management science.” Elsevier Science, Amsterdam, The Netherlands. [6] Klir, G.J., and Folger, T.A (2004). “Fuzzy sets, Uncertainty, and information.” Prentice-Hall of India limited, N.D., 138-139. [7] Paek, J.H., Lee, Y.W., and Ock, J.H. (1993). “Pricing construction risk-fuzzy set application.”J. Constr. Eng. Manage., 119(4), 743-56. [8] Pedrycz, W., and Gomide, F. (1998). “An Introduction to Fuzzy Sets – Analysis and Design.” The MIT Press, Massachusetts. [9] Ross, T. J. (1997). “Fuzzy Logic with Engineering Applications.” McGraw- Hill book company- Singapore. [10] Verkuilen, J. (2005). “Assigning Membership in a Fuzzy Set Analysis.” Socialogical Methods & Research, 33(4), 462-496. [11] Zadeh, L.A. (1965). “Fuzzy sets”. Information and Control, 8, 338-353.

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development (ACEID-2014), Vasavi College of Engineering, Hyderabad, A.P. 6 - 7 February, 2014. pp.282-288.

Comparision of MCDM Methods in Project Selection S.V.S.N.D.L. Prasanna1 and C. Nutan Kumar2 1

Assistant Professor, Department of Civil Engineering, 2M. E student, CED, University College of Engineering, Osmania University Hyderabad

ABSTRACT Multi-criteria decision support systems are used in various fields of human activities. Every alternative in multicriteria decision making problem can be represented by a set of properties or constraints. The properties can be qualitative and quantitative. For measurement of these properties, there are different units, as well as there are different optimization techniques. Depending upon the desired goal, the normalization aims for obtaining reference scales of values of these properties. Economy project often becomes one of the strong selecting points to attract contractors. However, economy projects sometimes mislead contractors to select. Therefore, it is crucial for contractors to mark projects comparison before deciding to select a smart one. Smart contractors might wisely try to include all criteria when evaluating which project is the best one. Most selection methods either ignore or barely include non-quantifiable factors. The successful methods that take in consideration these factors are the Fuzzy, VIKOR, Fuzzy VIKOR selection techniques. In the present study, an attempt is made to evaluate different crucial parameters that are required for the selection of a project. In this study three different methods like Fuzzy, VIKOR and Fuzzy VIKOR are applied for three different projects (roads and bridges) out of which the Fuzzy VIKOR method is the best suited for selection of any construction project. Keywords— Multi-criteria, fuzzy, decision constraints. INTRODUCTION Construction projects are unique which involve a temporary project team that is assembled from different companies, place and etc. Moreover, the size and complexity of construction projects are increasing which adds to the risks, in addition to the political, economic, social conditions where the project is to be undertaken. Project risk can be defined as an uncertain event or condition that, if it occurs, has a positive or negative effect on at least one project objective, such as time, cost, and quality. Construction clients are always facing with difficulties in selecting projects that offer return on investment. Due to scarce resources, they cannot undertake all projects simultaneously. Instead, they have to select the most viable projects, which not only maximize positive outcomes (e.g., profits, reputation, etc.) but also minimize any negative results (e.g., technical deficiency, environmental harm, etc.). This raises the need for relying on a set of selection criteria for prioritizing a number of projects. Selection of project among a set of possible alternatives is a difficult task that decision maker (DM) has to face. Construction projects shape the built environment in which people live and work. The built environment is typically a country's most important asset, both economically and socially. The performance of construction projects and the whole-of life management of constructed assets influences a country's productivity,

competitiveness, living quality and ecological sustainability. Financial incentives are typically used on construction projects to invigorate motivation towards above business-as-usual (BAU) goals and provide the contractor with the opportunity for higher profit margins if exceptional performance is achieved. The reason for this is no two constructions are alike. So, the same methodology cannot be exactly applied to other project. In some cases, surveys are conducted to make the decision. Due to the complexity of the work and technological development, the construction clients are placing increasing demands upon the industry in terms of the project quality, costs of delivery, time from inception to occupation, above all, value for money of projects. To facilitate them to develop ideas that are suitable to the project and are satisfactory to all the team members, multi criteria decision making techniques are implemented. Construction industry has witnessed the failure of many contractors due to varying reasons such as financial problems, poor performance, or accidents arising from the lack of adequate safety consideration at worksites. Decision of selecting an engineering, construction or R&D project is often fundamental for business survival. Such decisions usually involve prediction of future outcomes considering different alternatives. The fact of matter is that modern businesses face a more severe and challenging environment than ever before. As the decision maker tries to maximize or minimize outcomes associated with each objective depending on its nature, so a multiple

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Comparision of MCDM Methods in Project Selection

criteria decision-making problem arises. Multi-criteria decision making (MCDM) is applied to preferable decisions among available classified alternatives by multiple attributes and is one of the most widely used decision methodology in project selection. Project selection problem has attracted great endeavour by practitioners and academicians in recent years. Moreover, since different conflicting criteria and objective functions are involved in selection of projects, the multi-criteria decision making methods have been vastly employed to cope with the problem. OBJECTIVES OF THE PRESNT STUDY 1. To identify various criteria’s that are considered in project selection and implement MCDM methods and relative rank index to ascertain the viability of selection process. 2. To compare the MCDM methods and to know the process of selecting and select the best project from the feasible alternatives. LITERATURE REVIEW Selection of a project constitutes one of the main problems that construction managers are facing with, decision of selecting engineering, construction or R&D project is often fundamental for business survival. Such decisions usually involve prediction of future outcomes considering different alternatives. The fact of matter is that modern businesses face a more severe and challenging environment than ever before. The increasing volatility in interest and exchange rates, lifting trade barriers and development of new technologies in electronics, nanotechnology, and bio technology result in a high level of uncertainty in managerial decision making. A comprehensive review of literature has been carried out and contributions of part researches are summarized as follows. Chitrasen et al (2012) used FUZZY VIKOR for a case study in supplier selection. The nature of the supplier selection process is a complex multi-attribute group decision making (MAGDM) problem which deals with both quantitative and qualitative factors may be conflicting in nature as well as contain incomplete and uncertain information. In order to solve such a kind of MAGDM problems, the development of an effective supplier selection model is evidently desirable. In this paper, an application of the VIKOR method combined with FUZZY LOGIC has been used to solve supplier selection problems with conflicting and noncommensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution. The decision maker wants a solution, which must be closest to the ideal, and the alternatives are evaluated according to all established criteria. Linguistic values are used to assess the ratings and weights for the conflicting factors.

These linguistic ratings can be expressed in triangular fuzzy numbers. Then, a hierarchy MAGDM model based on fuzzy sets theory and the VIKOR method has been proposed to deal with the supplier selection problems in the supply chain system. Fouladgar et al (2011) used FUZZY VIKOR for Project portfolio Selection Using VIKOR Technique under Fuzzy Environment. Project portfolio selection for making decisions on investment is a critical decision in such companies. This selection is a multi-criteria problem, due to miscellaneous criteria which are often in conflicting with each other. The authors define six criteria for selecting the optimal project as cost criteria (risk, payback period) and benefit criteria (Profitability, consistent with corporate goals and objectives, flexibility, and sustainability). On the other, project portfolio selection problem is often influenced by uncertainty in practice; also because of the uncertainty associated with imprecision, loss of information and lack of understanding. In this paper, the implementation of an organized framework for project portfolio selection has discussed through the proposed model base on VIKOR technique using linguistic terms in order to calculate the importance weights of evaluation criteria and rank the feasible projects in descending order. Jose et al (2009) used VIKOR for selection of materials under aggressive environment. The selection of materials in industrial applications has always been important to product designers as a consequence that the choice of a material has usually been based on their mechanical and chemical properties. Traditional product design tools employ detailed theoretical and empirical relationships to estimate the engineering performance of a product as a function of its geometry and materials. Advances in materials science and in the development of new processing technologies have presented product designers with a wide array of choices previously unavailable to them. This has made the selection of materials for a given application a far more challenging and difficult task, in particular in the selection of materials under high risk of failure. The traditional single criteria decision making is no longer able to handle these problems. The Compromise Ranking method, also known as the VIKOR method, introduces the Multi-Criteria ranking index based on the particular measure of “closeness” to the “ideal” solution. For their study the above method were adopted in the selection of materials taking into account the risk of failure under aggressive environments. Mehrez et al (1983) formulated a project selection problem as a Multi Criteria Decision Making (MCDM) problem and applied it to a utility function. They described an interactive method for presenting a sequence of feasible sets of indivisible projects to a decision-maker. For each set as a whole, the decision-maker evaluates its utilities with respect to each of several attributes; the

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Proceedings of the National Conference on Advances in Civil Engineering and Infrastructure Development Table 3.1: Project Selection Data Case Study

S.No 1

Criteria’s Type of the Project

Project A Construction of Grade Separator i.e. Flyover at Tolichowki Junction

Project B Construction of Road from Botanical Garden to old Mumbai Road via Masjeed banda Village, Serilingampally

2 3

Value of project Exact design

43.78 Cr Perfect

35.00 Cr Perfect

4

Work Experience Of Supervisor Time of completion Past experience in similar projects Availability of capital Quality management system Timelines in getting all permits, license and permissions Material regional condition Timelines in project approvals Project safety Capital structure of company Various ion of material prices Market availability Financial plan for the project

15 years

20 years

Project C Construction of Improvement of Old Mumbai Highway from Tolichowki to Gachibowli, Hyderabad (Phase-I) under IALA 48.48 Cr Some details are missing 23 years

18 months 8 similar projects

24 months 6 similar projects

24 months 5 similar projects

25 Cr

24 Cr

24Cr

Excellent quality

Good quality

Low quality

4 months

2 months

1 month

Average

Good

Poor

45 days

90 days

60 days

Excellent Moderate

Excellent Moderate

Average Moderate

Flexible

Flexible

Non flexible

Excellent Moderate

Good Good

Good Moderate

5 6 7 8 9

10 11 12 13 14 15 16

utilities are then combined to give a single utility for the set.

Hyderabad) is considered as a case study whose details are as given in the table 3.1.

Literature review tells us that in any of the project selection process of the construction industry, in view of its ability to handle both qualitative and quantitative parameters the application of FUZZY SET THEORY method, VIKOR Method, FUZZY VIKOR Method has been a powerful tool. The present study deals with the selection of optimal/best project in construction industry using the three MCDM methods.

METHODOLOGY

CASE STUDY A construction firm having following three options of M/s. M.Venkat Rao Infra Projects Pvt. Ltd. an ISO 9001:2008 company (Formerly M/S M.Venkat Rao,

Fuzzy Method This method deals with the linguistic variables and trapezoidal fuzzy numbers that are assigned for the various criteria (C1 to C15). The evaluation of criteria by decision makers is done based on experience and the average fuzzy score for the criteria is calculated. After finding the average fuzzy score, defuzzification is done to produce fuzzy value by which the normalized fuzzy score is obtained as presented in the table 3.2. The overall priority of projects is obtained by taking the sum product of criteria priority and projects priority for that particular alternative and is shown in table 3.3. Since the overall

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Comparision of MCDM Methods in Project Selection

priority of the project B is maximum, that shall be considered as the Optimal Project by this method.

{

Table 3.2: Normalized Defuzzified Values of Projects

Criteria C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15

A 0.7167 0.7750 0.6833 0.7167 0.5333 0.8667 0.5833 0.8333 0.8667 0.5500 0.6667 0.5333 0.6333 0.5500 0.7167

B 0.6917 0.7750 0.8667 0.6917 0.9250 0.6667 0.7833 0.6917 0.5333 0.8667 0.7250 0.9250 0.6333 0.5500 0.8083

{

C 0.6167 0.3167 0.6417 0.6167 0.5833 0.3667 0.3667 0.3667 0.3667 0.2833 0.6083 0.5833 0.5000 0.3500 0.5500

(3.1)

∑

(

)⁄( [

(

) )⁄(

)]

(3.2)

Rank the alternatives by sorting each S, R, and Q values in ascending order is taken up and alternatives are shown in the table 3.8. By satisfying the following two conditions simultaneously, the scheme with minimum value of Q in ranking is considered for the optimal compromise solution such as, C1. The alternative Q(A(1)) has an acceptable advantage in other words, (

VIKOR METHOD In this method, the Linguistic Variables Scale is considered as shown in the table 3.4. The calculation of weights for criteria’s and normalization of weights is done to determine the details about evaluation of the projects to which normalization of the payoff matrix is obtained as shown in table 3.5. Thereafter, the computation of the positive-ideal solutions (best) value fj∗ and negative ideal solutions (worst) value fj− for all criterion rating and the values of Si and Ri (i = 1,... ,m), by using the following relations and the fj∗ and fj− values are presented in the table 3.6. The S and R values are shown in the table 3.7.

( )

)

(

( )

)

⁄(

)

(3.3)

Where, A(2) is the alternative with the second position in the ranking list and m is the number of alternatives. C2. The alternative Q(A(1)) is stable within the decision making process in other words, it is also best ranked in Si and Ri. If condition C1 is not satisfied, that means QA(m)_Q(A(1) )