Prediction of CBR and Compaction Parameters using Index Soil Properties of Islamabad Soils

Abstract

California Bearing Ration (CBR) and standard compaction test are integral part of construction industry due to their reliability and inexpensiveness. However, the time taken to perform these tests and the physical effort required make their execution difficult. Thus, in order to save time and effort, there’s a need to correlate CBR and compaction parameters (OMC and MDD) with simpler less time taking laboratory tests. This study is based on prediction of CBR values and compaction parameters of cohesive soils using index soil properties (grainsize analysis, Atterberg limits, specific gravity). Thirty natural soil samples were collected from different areas across Islamabad: CBR, Standard proctor, sieve analysis, hydrometer analysis, specific gravity, liquid limit, and plastic limit tests were performed. Data analysis software SPSS was used to perform multi linear regression analysis. Regression analysis was performed in two stages; in the first stage MDD and OMC were taken as output parameters with grain-size, Atterberg limits and specific gravity being the input parameters while, in second stage CBR was taken as the output parameter with compaction parameters, grainsize values, Atterberg limits and specific gravity being the input variables. Seven predictive models were presented for OMC and MDD, out of which two models (one for each OMC and MDD) is recommended; similarly, fourteen predictive models were produced for CBR out of which three models are recommended. It is concluded from the study that Index soil properties along with compaction parameters are proven to be good predictive variables for California bearing ratio. Optimum moisture content can also be predicted with good accuracy using index soil properties as input variables; Maximum dry density, however, does not make a strong correlation with the index soil properties.