Abstract:
The California Bearing Ratio is a penetration test for evaluation of the mechanical
strength of road sub-grades and base-courses. This can be used as a mean of designing
the road pavement required for a particular strength of sub-grade by comparing the
strength of different sub-grade materials.
However; civil engineers always encounter difficulties in obtaining representative
CBR value for design of pavement. Over the years, many correlations had been
proposed by various researchers in which the soil index properties were used to
develop these correlations.
A study was carried out to find correlations between CBR value with soil index
properties those best suit the type of soils in Sri Lanka. Analyses were carried out
based on the published correlations and soil data obtained from several Sri Lankan
project sites. Based on the results, it is observed that the current published correlations
are not in good agreement with Sri Lanka soils. In addition, no typical range could be
found based on the soil index properties.
Mechanical Strength of soil depends not only on the soil type but also on the
observable physical characteristics which significantly influence on a soil’s behavior.
Therefore, a method is proposed for correlating soaked CBR value and compaction
parameters with such index properties, for Sri Lankan soils. This research covers the
entire soil types according to Unified Soil Classification System which are generally
used as sub-grades and base-courses.
Among the several soil index properties, Atterberg Limits and grain size distribution
data are used in this regard as these tests are much more economical and rapid than
Compaction and CBR tests. The correlations are established in the form of an
equation as a function of different soil properties by the method of regression
analysis. Finally, results of the laboratory test are used to compare with the results of
regression equation for the compiled data for the validation of the correlation.
Key Words : California Bearing ratio, Compaction Parameters, Index Properties,
Regression Analysis