Identification of an equivalent model for granular soils by FEM/NMM/p-EMP hybrid system

Abstract

The application of FEM/NMM/p-EMP computational hybrid system in formulation of the Neural Material Model (NMM) for granular soils is presented. NMM is a Multi Layer Preceptron formulated 'on-line'. The cumulative algorithm of the autoprogressive method was implemented into the FEM program. The patterns for NMM training were generated in the rigid strip footing analysis. Pseudo-empirical equilibrium paths p-EMP for verification of the NMM were computed by a FEM program for the elastic-plastic Drucker-Prage material model. The discussed inverse problem of NMM identification is illustrated by two study cases of footing: 1) rigid strip footing on plane semispace, 2) inclined slope analysis. It was numerically proved that the NMM identified in the first study case can be successfully applied to the analysis of the latter one.