ENGINEERING CHARACTERIZATION OF EXPANSIVE SOIL IN ARBAMINCH TOWN (CASE STUDY OF ARBA MINCH TOWN

Abstract

Expansive soils, which are considered as problematic soils, have worldwide distribution and hence, their proper identification and characterization becomes an absolute requirement in the perspective of the present day geotechnical engineering practice. Expansive soils experience significant volume change associated with changes in moisture contents, these volume changes can either be in the form of swell or in the form of shrinkage; and this is why they are sometime known as Swell/Shrink soils. Arba Minch town experiences more damage from expansive soils throughout the year. It is known that the magnitude of swelling for expansive soil varies with environmental conditions. This study intends to characterize expansive soil found in Arba Minch town and develop correlation between index properties and swelling pressure (Ps) for the study area. The soil specimen were obtained from ten different test pits from which index properties, engineering properties and swell-consolidation tests were conducted according to American Society for Testing Materials (ASTM) standard. Tested soil samples from the study area have been found to meet the diagnostic criteria for expansive soils, having LL in the range from 96% to 120%, PL ranges from 36% to 51%, free swell ranges from 97.5% to 155%, PI from 49% to 77%, GS from 2.61 to 2.83, Clay content ranges between 35.18% and 48.94%. The laboratory results revealed that the study area has plastic-behavior. In this study, efforts were made to develop Artificial Neural Network (ANN) and Multiple Regression Analysis (MRA) models that can be employed for estimating swelling pressure. Equation with high regression coefficient has been selected to predict the swelling pressure. Comparison between two software (ANN and SPSS) was conducted, ANN resulted good prediction than SPSS. Further, different parameters were used to develop the prediction model and among those Atterberg’s Limit, Dry density and Moisture content result good coefficient of correlation. Furthermore, Index properties which are used for establishing the model can be conducted easily in soil laboratory without any tedious and time consuming procedure