Prediction of California Bearing Ratio (CBR) Value from Index Properties of Soils. Case Studies Seka Town, Jimma, Ethiopia

Abstract

California Bearing Ratio (CBR) value is an important soil parameter considered as main design input in the design of flexible pavements and runways of air fields. The design of pavement thickness determined depending on the strength of subgrade soil expressed in terms of CBR (%). In the design of pavement, the suitability and stability of sub-grade materials are evaluated before construction of pavement by using CBR test. However, in a large scale road projects, conducting laboratory tests by using the CBR test is very expensive and time consuming. It also needs large soil samples which affects the cost and time of the project. In addition, Soil properties vary from region to region and season to season as it appears naturally. Therefore, developing empirical equations specific to a certain region and soil type could be considered nearly as good insight of soil behavior. Therefore, this study was conducted to predict the CBR value from the index properties of soil to solve the difficulties in the determination of CBR value. The study was carried out using thirty samples collected from the study area. The laboratory test procedures were based on the standard procedures of American Society for Testing Materials (ASTM) and American Association of State Highway and Transportation Officials (AASHTO) method. The laboratory test result and statistical analysis were carried out using Microsoft excel and SPSS software respectively. To develop the intended correlation model the procedures of data collection, laboratory test, normality test, and correlation and regression analysis were done. The index soil properties considered for this study to establish correlations with CBR values are Percentage Passing sieve No.200, Liquid Limit (LL), Plastic Limit (PL), Plastic Index (PI), Maximum Dry Density (MDD) and Optimum Moisture Content (OMC). From the regression analysis result, the equations developed are CBR = 28.188 – 0.67OMC, and CBR = -12.124 - 0.077LL – 0.178OMC + 20.37MDD, with coefficient of determination R 2 = 0.814 for single linear regression and R2 = 0.899 for multiple linear regression respectively. Based on the result of regression analysis, fairly good correlation of CBR value is obtained with multiple parameters (LL, OMC and MDD) in multiple linear regression than with single parameters (OMC) in single linear regression. Therefore, the study concluded that during the prediction of CBR value from the index properties, the combined parameters of index properties should be used rather than single parameters. Generally, it is recommended that the result of this research could be applied for the prediction of the CBR values in different civil engineering practices.