A Multiple Regression Equation for Prediction of Bearing Capacity of Geosynthetic Reinforced Sand Beds

Abstract

Several researchers have studied the effects of various important parameters like number of layers of reinforcement (N), depth of the upper most layer of reinforcement from the base of the footing (u), spacing of the reinforcement layers (h), width of reinforcement layer (b), tensile strength of reinforcement (T) and density of soil (γ) on the ultimate bearing capacity of footings on reinforced soils. However, very few of them have attempted to develop equations to estimate the bearing capacity of the footings on reinforced soils by considering all the above parameters. Review of the existing state of the art in this area is presented in this paper and the ability of the existing analytical models to predict the ultimate bearing capacity of reinforced sand beds is verified using results from laboratory model tests. A multiple regression equation to estimate the ultimate bearing capacity of square footing resting on geosynthetic reinforced sand beds based on the laboratory model studies is presented. This equation is verified against the experimental results of model studies and also with the experimental measurements of other researchers. Statistical analysis of the model test data revealed that the aperture size of the reinforcement is very influential in altering the bearing capacity of reinforced sand beds. The regression equation developed in this study is reasonably good in predicting the bearing capacity of square footing on dense sand reinforced with planar geosynthetics.