Neural network for constitutive modelling in finite element analysis

Abstract

Finite element method has, in recent years, been widely used as a powerful tool in analysis of engineering problems. In this numerical analysis, the behavior of the actual material is approx-imated with that of an idealized material that deforms in accordance with some constitutive relationships. Therefore, the choice of an appropriate constitutive model, which adequately de-scribes the behavior of the material, plays a significant role in the accuracy and reliability of the numerical predictions. Several constitutive models have been developed for various materials. Most of these models involve determination of material parameters, many of which have no physical meaning [1, 2]. In this paper a neural network-based finite element analysis will be presented for modeling engineering problems. The methodology involves incorporation of neural network in a finite element program as a substitute to conventional constitutive material model. Capabilities of the presented methodology will be illustrated by application to practical engineering problems. The results of the analyses will be compared to those obtained from conventional constitutive models. Key words: finite element, neural network, constitutive modelling, soil 1 Intelligent finite element method An intelligent finite element method has been developed, based on the integration of neural network in a finite element framework. In the proposed methodology, a neural network is incorporated in the finite element analysis as a substitutive to constitutive material model. A neural network is ∗e-mail: