Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model

Ibrahim Abdulkarim Ikara; Ali Musa Kundiri; Abbagana Mohammed

doi:doi:10.11648/j.ajtte.20190401.15

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Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model

Ibrahim Abdulkarim Ikara, Ali Musa Kundiri, Abbagana Mohammed

Published in American Journal of Traffic and Transportation Engineering (Volume 4, Issue 1)

Received: 7 March 2019 Accepted: 22 April 2019 Published: 15 May 2019

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Abstract

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 MS_E 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, OMC_sp, MDD_sp) and (C_m, WG, PL, LL, OMC_mp, MDD_mp) 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.

Published in	American Journal of Traffic and Transportation Engineering (Volume 4, Issue 1)
DOI	10.11648/j.ajtte.20190401.15
Page(s)	31-36
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Soil Stabilization, Black Cotton Soil, Waste Glass Admixture, Regression Models

References

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[2]	Ramasubbarao, G. V., & Sankar, G. S. (2013). Predicting soaked CBR value of fine-grained soils using index and compaction characteristics. Jordan Journal of Civil Engineering, 7 (3), 354-360.
[3]	Shirur, N. B., & Hiremath, S. G. (2014). Establishing relationship between CBR value and physical properties of soil. IOSR journal of mechanical and civil engineering, 11 (5), 26-30.
[4]	Satyanarayana Reddy, C. N. V., & Pavani, K. (2006). Mechanically stabilised soils-regression equation for CBR evaluation. In Proceedings of the Indian geotechnical conference, Chennai, India (pp. 731-734).
[5]	Gregory, G. H., & Cross, S. A. (2007). Correlation of CBR with shear strength parameters. In Proceedings of 9th International Conference on Low Volume Roads, Austin, Texas
[6]	Vinod, P., & Reena, C. (2008). Prediction of CBR value of lateritic soils using liquid limit and gradation characteristics data. Highway Research Journal, IRC, 1 (1), 89-98.
[7]	Patel, R. S., & Desai, M. D. (2010). CBR predicted by index properties for alluvial soils of South Gujarat. In Proceedings of the Indian Geotechnical conference, Mumbai (pp. 79-82).
[8]	Yildrim, B. and Gunaydin, O. (2011). Estimation of CBR by Soft Computing Systems, Expert Systems with Applications, ELSEVIER, 38 (5): 6381-6391.
[9]	Patel, M. A., & Patel, H. S. (2012). Experimental Study to Correlate the Test Results of PBT, UCS, and CBR with DCP on Various soils in soaked condition. International Journal of Engineering (IJE), 6(5), 244.
[10]	Venkatasubramanian, C., & Dhinakaran, G. (2011). ANN model for predicting CBR from index properties of soils. International Journal of Civil & Structural Engineering, 2 (2), 614-620.
[11]	Sabat, A. K. (2013). Prediction of California bearing ratio of a soil stabilized with lime and quarry dust using artificial neural network. Electronic Journal of Geotechnical Engineering, 18, 3261-3272.
[12]	Alawi, M., and Rajab, M. (2013). Prediction of California bearing ratio of sub-base layer using multiple linear regression models. Road Materials and Pavement Design, 14 (1), 211-219.
[13]	Talukdar, D. K. (2014). A Study of Correlation between California Bearing Ratio (CBR) Values with Other Properties of Soil. International Journal of Emerging Technology and Advanced Engineering, 4 (1), 559-562.
[14]	Ikara, I. A., Kundiri, A. M., & Mohammed, A. (2015). Effects of Waste Glass (WG) on the Strength Characteristics of Cement Stabilized Expansive Soil. American Journal of Engineering Research (AJER), 4, 33-41.
[15]	BS 1377 (1990). Methods of Testing Soils for Civil Engineering Purposes. British Standard Specification, London.
[16]	BS 1924 (1990). Methods of Tests for Stabilized Soils. British Standard Specification. London.
[17]	Ugbe, F. C. (2012). Predicting Compaction Characteristics of Lateritic Soil of Western Niger Delta, Nigeria. Research Journal of Environmental and Earth Sciences, 4 (5), 553-559.
[18]	Alam MZ, Ameem ES, Muyibi SA, Kabbash NA (2009) the factors affecting the performance of activated carbon prepared from oil palm empty fruit bunches for adsorption of phenol. Chemical Engineering Journal doi: 10.106/J.cej.2009.07.033.
[19]	Montgomery DC, Runger GC (2011) Applied statistics and probability for engineers. 5th edn. Wiley and Sons, Asia, Pte, Ltd.

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Ibrahim Abdulkarim Ikara, Ali Musa Kundiri, Abbagana Mohammed. (2019). Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model. American Journal of Traffic and Transportation Engineering, 4(1), 31-36. https://doi.org/10.11648/j.ajtte.20190401.15

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ACS Style

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. Am. J. Traffic Transp. Eng. 2019, 4(1), 31-36. doi: 10.11648/j.ajtte.20190401.15

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AMA Style

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. Am J Traffic Transp Eng. 2019;4(1):31-36. doi: 10.11648/j.ajtte.20190401.15

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@article{10.11648/j.ajtte.20190401.15,
  author = {Ibrahim Abdulkarim Ikara and Ali Musa Kundiri and Abbagana Mohammed},
  title = {Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model},
  journal = {American Journal of Traffic and Transportation Engineering},
  volume = {4},
  number = {1},
  pages = {31-36},
  doi = {10.11648/j.ajtte.20190401.15},
  url = {https://doi.org/10.11648/j.ajtte.20190401.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtte.20190401.15},
  abstract = {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.},
 year = {2019}
}

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TY  - JOUR
T1  - Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model
AU  - Ibrahim Abdulkarim Ikara
AU  - Ali Musa Kundiri
AU  - Abbagana Mohammed
Y1  - 2019/05/15
PY  - 2019
N1  - https://doi.org/10.11648/j.ajtte.20190401.15
DO  - 10.11648/j.ajtte.20190401.15
T2  - American Journal of Traffic and Transportation Engineering
JF  - American Journal of Traffic and Transportation Engineering
JO  - American Journal of Traffic and Transportation Engineering
SP  - 31
EP  - 36
PB  - Science Publishing Group
SN  - 2578-8604
UR  - https://doi.org/10.11648/j.ajtte.20190401.15
AB  - 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.
VL  - 4
IS  - 1
ER  -

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Author Information

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

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APA Style

Ibrahim Abdulkarim Ikara, Ali Musa Kundiri, Abbagana Mohammed. (2019). Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model. American Journal of Traffic and Transportation Engineering, 4(1), 31-36. https://doi.org/10.11648/j.ajtte.20190401.15

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ACS Style

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. Am. J. Traffic Transp. Eng. 2019, 4(1), 31-36. doi: 10.11648/j.ajtte.20190401.15

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AMA Style

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. Am J Traffic Transp Eng. 2019;4(1):31-36. doi: 10.11648/j.ajtte.20190401.15

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@article{10.11648/j.ajtte.20190401.15,
  author = {Ibrahim Abdulkarim Ikara and Ali Musa Kundiri and Abbagana Mohammed},
  title = {Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model},
  journal = {American Journal of Traffic and Transportation Engineering},
  volume = {4},
  number = {1},
  pages = {31-36},
  doi = {10.11648/j.ajtte.20190401.15},
  url = {https://doi.org/10.11648/j.ajtte.20190401.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtte.20190401.15},
  abstract = {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.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Predicting CBR Values of Black Cotton Soil Stabilized with Cement and Waste Glass Admixture Using Regression Model
AU  - Ibrahim Abdulkarim Ikara
AU  - Ali Musa Kundiri
AU  - Abbagana Mohammed
Y1  - 2019/05/15
PY  - 2019
N1  - https://doi.org/10.11648/j.ajtte.20190401.15
DO  - 10.11648/j.ajtte.20190401.15
T2  - American Journal of Traffic and Transportation Engineering
JF  - American Journal of Traffic and Transportation Engineering
JO  - American Journal of Traffic and Transportation Engineering
SP  - 31
EP  - 36
PB  - Science Publishing Group
SN  - 2578-8604
UR  - https://doi.org/10.11648/j.ajtte.20190401.15
AB  - 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.
VL  - 4
IS  - 1
ER  -

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