Volume 4, Issue 1, January 2019, Page: 31-36
Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model
Ibrahim Abdulkarim Ikara, Department of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi, Bauchi State, Nigeria
Ali Musa Kundiri, Department of Civil and Water Resource Engineering, University of Maidugri, Maiduguri, Borno State, Nigeria
Abbagana Mohammed, Department of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi, Bauchi State, Nigeria
Received: Mar. 7, 2019;       Accepted: Apr. 22, 2019;       Published: May 15, 2019
DOI: 10.11648/j.ajtte.20190401.15      View  487      Downloads  108
In highway constructions, sub-grade and sub-base soil stabilization has been used as one of the prime and major process for many years in order to improve the engineering properties of soil. The strength of theses layers is indicated by their California bearing ratio (CBR) value which is quite expensive and time consuming. In order to overcome this situation, this study presents a methodology for predicting soaked California Bearing Ration (CBR) value of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture using Multiple Regression Analysis (MRA). Experimental test results such Atterberg limit (Liquid limit (LL), Plastic limit (PL) and Plasticity index (PI)), Compaction characteristics of two compactive efforts namely standard proctor (SP) and modified proctor (MP) (maximum dry density (MDD) and optimum moisture content (OMC)), CBR, Waste glass (WG) content and Cement content (Cm), obtained from a laboratory at Abubakar Tafawa Balewa University Bauchi, Nigeria, have been employed in developing multiple regression models. California Bearing Ration was taken as the dependent variables while Liquid limit, Plastic limit, maximum dry density, optimum moisture content, waste glass content and Cement content were taken as independent variables. The regression analysis calculated the error mean square (MSE) for each possible model, and models with large MSE were not selected for the best regression equations. The best models have a minimum value of MSE occurring for the six-variable model (Cm, WG, LL, PL, OMCsp, MDDsp) and (Cm, WG, PL, LL, OMCmp, MDDmp) with a corresponding higher value of coefficient of multiple determination R2 = 0.98 and 0.94. The performance evaluation of the fitted regression models indicates a strong correlation (R2 = 0.89 - 0.98) between the mentioned variables, and the model equations developed from this work provided a very good prediction of the response, as the equations can be employed for making estimates of soaked CBR of other black cotton soils having similar geotechnical properties.
Soil Stabilization, Black Cotton Soil, Waste Glass Admixture, Regression Models
To cite this article
Ibrahim Abdulkarim Ikara, Ali Musa Kundiri, Abbagana Mohammed, Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model, American Journal of Traffic and Transportation Engineering. Vol. 4, No. 1, 2019, pp. 31-36. doi: 10.11648/j.ajtte.20190401.15
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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