Abstract:
Soil properties vary from region to region and season to season as it appears naturally.
studying this variation in different soil type and origin are a very important task for
geotechnical engineers. To overcome the effects from this variation geotechnical engineers
as well as other professionals attempt to develop empirical equations specific to a
certain region and soil type in order to use the soil for different purpose. However, these
empirical equations are more reliable for the type of soil where the correlation is
developed .Hence, it is good practice developing empirical equations that best fit for the
soil available in the area that we can access.
In the flexible pavements sub-grade is considered to be an ideal layer to resist wheel load
and its CBR value is considered as the strength measuring parameter. Conducting CBR test
is an expensive and time consuming procedure , moreover it is very difficult to mould
the sample at a desired in-situ density in the laboratory. Furthermore, if the available soil is
of a poor quality, suitable additives are mixed with soil and resulting strength of soil is
assessed by CBR value which is cumbersome. To overcome such problems, the other method
such as regression based models (simple & multiple) has to be used from quick and easily
determined parameters.
Therefore ,this study is conducted to develop the correlation between CBR values with
soil index properties specifically located along the way Welkite- Arekit –Hossana Road
which is 121 km long. The study was carried out using thirty samples retrieved from this road
and tested in a laboratory. By using the test result regression based statistical analysis is
carried out to develop the intended correlation. The correlation development is performed in
the form of an equation of CBR as a function of grain size parameters, Atterberg limits
and compaction parameters by considering the effect of an individual soil properties
and effect of a combination of soil properties on the CBR value.
Based on both simple and multiple linear regression analysis relatively fair correlation is
obtained by combining plasticity index, percentage of fine content and maximum dry density
which are basically strength determinant of fine grained soils. From the correlation analysis
the equations developed are , with
coefficient of determination of R
2=0.731 for multiple linear regression and
with coefficient of determination of R
2=0.682 single
linear regression respectively. Statistical data analysis commercially available soft wares
namely MINITAB, SPSS and Microsoft Excel used. After developing the correlation,
comparison of predicting capacity of the developed model with control samples and previous
researchers correlation have been applied for conformity. The result shows that the
correlation is sufficiently accurate in determining the CBR and hence can be used for
preliminary characterization purpose within the soil property ranges used in the study