Title
Coupled SelfSim and Genetic Programming for Non-Linear Material Constitutive Modelling
Document Type
Article
Publication Date
Fall 10-2014
Abstract
In the present study, an improved SelfSim is combined with a recent genetic programming technique called linear GP (LGP) for the inverse extraction of non-linear material behaviour. The SelfSim prepares a comprehensive database including stresses and strains of the structural elements. Then, a steady-state LGP is used to formulate the strain–stress relationship. In this research, a space truss with a reference material model is used as a hypothetical structure. The derived LGP-based formula is very simple and can be employed for design and pre-design purposes. The implementation of LGP-based model is also tested in a general purpose finite element programme. Since the proposed model is an explicit formula, its implementation becomes standard and practically useful. The results show that the procedure is reliable and can be used to derive and formulate the non-linear constitutive material models with a high degree of accuracy.
Publication Title
Inverse Problems in Science and Engineering
Volume
23
Issue
7
First Page
1101
Last Page
1119
Recommended Citation
Gandomi, Amir H. and Yun, Gun Jin, "Coupled SelfSim and Genetic Programming for Non-Linear Material Constitutive Modelling" (2014). Civil Engineering Faculty Research. 23.
https://ideaexchange.uakron.edu/civil_ideas/23