Paper Title:
Complex CBR (of BC Soil-RHA-Cement Mix) Estimation: Made Easy by ANN Approach [a Soft Computing Technique]
  Abstract

In past days many researchers have been worked on the expansive soil to determine the California Bearing Ratio (CBR) values in a conventional ways, which are time consuming and require lot of manual involvements. So we the authors of this research paper attempted to develop a soft computing technique to prognosticate CBR value by using Artificial Neural Network (ANN), a data driven technique. ANN is a mathematical model inspired from the human brain’s information-processing characteristics, including the parallel processing ability. Over the last few years, the use of ANN has increased in many areas of engineering. In particular have been applied to many geotechnical engineering problems and have demonstrated some degree of success. A review of the literature reveals that ANN has been used successfully in the pile capacity prediction, site characterization and so on. In the present study the Black Cotton (BC) soil has been stabilized by using Rice Husk Ash (RHA) and cement, several experiments have been conducted for different mix combinations under soaked condition. From the obtained results, it is observed that the CBR value of BC soil increases with the addition of RHA and cement combination. The soaked CBR value found to be maximum for the mix of BC soil + 15% RHA + 12% cement. The present study deals with collection of input data base from experimental results, ANN’s training and its testing are adopted to fix the appropriate weighted matrix (Illustrated in Fig (1)) which in turn Prognosticates the CBR value. Experimental results have been compared with the CBR values prognosticated by using ANN and comparison graphs also plotted (Illustrated in fig (4)). The results of this study will contribute for the prognostication of CBR, which will assist a geotechnical engineer in estimation of CBR, with minimum effort.

  Info
Periodical
Advanced Materials Research (Volumes 261-263)
Edited by
Jingying Zhao
Pages
675-679
DOI
10.4028/www.scientific.net/AMR.261-263.675
Citation
A.N. Ramakrishna, A.V. Pradeep Kumar, K. Gowda, "Complex CBR (of BC Soil-RHA-Cement Mix) Estimation: Made Easy by ANN Approach [a Soft Computing Technique]", Advanced Materials Research, Vols. 261-263, pp. 675-679, 2011
Online since
May 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Dong Xing Wang, Rachid Zentar, Nor Edine Abriak, Wei Ya Xu
Abstract:Traditional approaches such as ocean dumping and inland deposit are unsatisfactory for the management of dredged sediments, in the context of...
755
Authors: Guang Qing Yang, Bao Lin Xiong, Bao Jian Zhang
Abstract:The California Bearing Ratio(CBR) denotes the potential strength of subgrade material and is the important index of evaluating its using...
3759
Authors: Yun Dong, Bao Tian Wang
Chapter 1: Traditional Building Materials
Abstract:Lime Stabilized expansive soil is often used as filler in road subgrade, although many scholars have done a lot of research, the mechanical...
166
Authors: Bazid Khan, Abdus Siraj, Riaz A. Khattak
Abstract:The subgrade soil of western by Pass Road Mardan, Pakistan consists of silty clay belonging to A-6(14) group of the AASHTO soil...
93
Authors: Ahmad Rifa’i, Noriyuki Yasufuku, Kiyoshi Omine
Chapter 3: Chemical, Biological, Composites, Functional Materials Science and Technology
Abstract:Volcanic ash becomes environmental important issues as waste material if it is not effectively reduced or reused. In engineering practice,...
292