Faramarzi, Asaad, Alani, Amir and Javadi, Akbar A. (2013) An EPR-based self-learning approach to material modelling. Computers & Structures, 137. pp. 63-71. ISSN 0045-7949

Full text not available from this repository. (Request a copy)

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.

Item Type:	Article
Identifier:	10.1016/j.compstruc.2013.06.012
Keywords:	Self-learning; Finite element; Evolutionary computation; Material modelling; EPR
Subjects:	Construction and engineering > Built environment Construction and engineering > Civil and structural engineering Computing
Depositing User:	Fabio Tosti
Date Deposited:	25 May 2016 22:21
Last Modified:	06 Feb 2024 15:44
URI:	https://repository.uwl.ac.uk/id/eprint/2126

Actions (login required)

View Item