Ultimate Bearing Capacity of Eccentrically Inclined Loaded Circular Foundation on Sand Layer of Limited Thickness Using ANN

Abstract

Laboratory model tests were conducted for the ultimate bearing capacity of shallow rough circular surface foundation resting over a sand layer of limited thickness subjected to an eccentrically inclined load. Based on the laboratory model test results, a neural network model is developed to estimate the reduction factor (RF). The reduction factor can be used to estimate the ultimate eccentrically inclined load per unit area of the foundation supported by a sand layer of limited thickness from the ultimate bearing capacity of a foundation on a sand layer extending to a great depth under an eccentrically inclined load. A thorough sensitivity analysis was carried out to determine the important parameters affecting the reduction factor. Importance was given on the construction of neural interpretation diagram. Based on this neural interpretation diagram, the direct or inverse relationships that exists between the input and output parameters were determined. Results from the artificial neural network (ANN) were compared with the laboratory model test results and these results are well matched.