Abstract:
A Prediction is a vital tool in engineering used to take right decisions. Therefore, it is very important for engineers to quickly predict the behavior of geomaterials used in the infrastructures. California Bearing Ratio (CBR) test is a common laboratory test, performed to evaluate the shear strength and stiffness modulus of sub grade for the design of pavement. CBR test is a laborious test, therefore, it is vital to develop the models for quick assessment of CBR value. This study is an attempt to develop valid models to determine the CBR value from index properties of soil which are quicker to estimate from their standard method of testing. In this study authors developed predictive models using 59 set of soil samples containing both fine grained and coarse grained soil samples. Three models were developed and validity of these models was checked on 25 set of soil samples tested separately. Authors developed separate models for coarse grained soil and fine grained soils. These models were developed, based on liquid limit and plasticity index for fine grained soil, the coefficient of uniformity and maximum dry density for coarse grained soil.
