Prediction Of Soaked California Bearing Ratio (Cbr) Of Fine Grained Soils From Index Properties;Case Of Silty Clay Soils From Addis Abeba - Winta, Amare (My University, 2016)
California Bearing Ratio (CBR) is a test which is currently practiced in the design of pavement to assess the stiffness modulus and shear strength of subgrade material so as to determine the thickness of overlying pavement layers. Though various attempts have been made to predict the CBR value by different researchers from samples of their locality, adopting those developed prediction methods without adjustment leads us to misinterpretation of soil behavior. Therefore, this paper is intended to fill this gap and to minimize the time required to conduct the CBR value test by predicting the CBR value from the index properties of fine grained soils of the study area. In order to achieve this goal two types of data were collected. The first is laboratory test data which is called primary data as a control point. And the second data are collected from different consulting and construction companies, which are called secondary data. The laboratory tests conducted are, grain size analysis, atterberg limits, compaction test and free swelling on 10 soil samples. These samples were collected from Goro , Bole arabsa and koyefiche sites. And about 114 secondary data were collected from Addis Ababa City Road Authority (AACRA), Transport Construction Design (TCD) and Best Consulting Engineers. In the analysis part, both MS excel spreadsheet and the SPSS software have been used for the scatter plot, correlation, and regression analysis. Using these tools attempts were made to predict CBR from LL, PL, PI OMC and MDD. The analysis results show that CBR has strong negative relation with LL and relatively strong positive relation with MDD. From the regression analysis it can be observed that the combination of LL, OMC and MDD gives better prediction of CBR with R2 value of 0.770. This means 77% variation of CBR depends on the variation of these predictors.