An EPR-based self-learning approach to material modelling

Research output: Contribution to journalArticlepeer-review

Authors

Colleges, School and Institutes

Abstract

In this paper an EPR-based self-learning method is presented for modelling the constitutive behaviour of materials using evolutionary polynomial regression (EPR). The proposed approach takes advantage of the rich stress–strain data buried in non-homogenous structural tests. The load–deformation data collected from experiment are used to iteratively train EPR-based material model using finite element simulations of the structural test. Two numerical examples are presented to illustrate the application of the proposed approach. It is shown that the EPR model gradually improves during the self-learning training and provides accurate prediction for the constitutive behaviour of the material.

Details

Original languageEnglish
Pages (from-to)63-71
Number of pages9
JournalComputers & Structures
Volume137
Early online date12 Sep 2013
Publication statusPublished - Jun 2014

Keywords

  • Self-learning, Finite Element;, Evolutionary Computing, Material Modelling, EPR