Artificial neural network as an incremental non-linear constitutive model for a finite element code

M. Lefik, B. A. Schrefler

Research output: Contribution to journalArticlepeer-review

133 Scopus citations

Abstract

A back propagation artificial neural network (BP ANN) is proposed as a tool for numerical modelling of the constitutive behaviour of a physically non-linear body. Training process of the ANN using experimental data is discussed in details and illustrated with an example. In particular, some difficulties in the constitutive description proposed in consistent, incremental form are discovered and two solutions are proposed to overcome them. Two numerical examples are presented. The first one deals with modelling of elasto-plastic hysteresis, the second shows the application of ANN to approximation of biaxial non-linear behaviour.

Original languageEnglish (US)
Pages (from-to)3265-3283
Number of pages19
JournalComputer Methods in Applied Mechanics and Engineering
Volume192
Issue number28-30
DOIs
StatePublished - Jul 18 2003

Keywords

  • Artificial neural network
  • Constitutive modelling
  • Finite elements method

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Mechanics

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