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.
