Statistical models for the prediction of shear strength parameters at Sirsa, India

Shear strength is the principal engineering property of soil, which controls the stability of a soil mass under structural loads. Therefore, it is always required to measure before design of foundation of any structure. In this study, a detailed survey was carried out within a 5 km radius of Sirsa and 10 locations were identified for soil sampling. The soil samples were collected at 50 cm depth from ground surface and analysed for different geotechnical properties like bulk density, dry density, natural moisture content, specific gravity, particle size, liquid limit, plastic limit, plasticity index and shear strength parameters (cohesion and angle of shearing resistance). With the help of particle size distribution curves, coefficient of uniformity and coefficient of curvature were evaluated to find out the gradation of particles. Influence of the geotechnical properties on shear strength parameters was studied. Stepwise regression procedure was carried out for the selection of most influencing variables. Incorporating selected variables, multiple regression models were developed for the prediction of shear strength parameters. The performance of the multiple regression models were assessed in terms of correlation coefficient, F-statistics and residuals pattern. Using the developed models, shear strength parameters can be computed for the study area.