Efficiency of pile groups installed in cohesionless soil using artificial neural networks

Abstract

This paper presents an artificial neural network (ANN) model that predicts the efficiency of pile groups installed in cohesionless soil and subjected to axial loading. The model accounts for the planar geometry of the group (pile diameter, pile spacing, and pile arrangement) and incorporates the effect of pile installation, pile length, cap condition, soil condition, and type of loading on the group efficiency. The results produced by the proposed ANN model compared well with the available results of laboratory and field tests. The ANN model is a viable design tool that assists foundation engineers in predicting the pile group efficiency in an accurate and realistic manner. In addition, this model can be easily updated to incorporate new data and accommodate new design parameters.Key words: axial load, pile foundation, group efficiency, cohesionless soil, artificial neural networks.