Artificial neural network application to estimate kinematic soil pile interaction response parameters

Abstract

Six artificial neural network (ANN) models are developed to predict various response parameters of kinematic soil pile interaction. These responses include (1) kinematic response factors for free and fixed head piles in homogenous soil layer to derive foundation input motion (2) normalized bending moment at fixed head of pile in homogenous soil layer (3) normalized kinematic pile moment at the interface of two soil layers of sharply different soil stiffnesses. These ANN models represent simple solutions that can be implemented in a simple calculator capable of matrix operation and bypass the site response analysis and the complex wave diffraction analysis. The data required for ANN training is generated using beam on dynamic Winkler formulation (BDWF). Fifty percent of the data is used to train the ANN models while remaining 50% is used to test the ANN models. The trained ANN models show good agreement with BDWF results.