Details
| Original language | English |
|---|---|
| Pages (from-to) | 15-31 |
| Number of pages | 17 |
| Journal | Finite Elements in Analysis and Design |
| Volume | 149 |
| Early online date | 5 Jul 2018 |
| Publication status | Published - 15 Sept 2018 |
Abstract
A new computationally interval homogenization modelling for heterogeneous materials with uncertain-but-bounded parameters is presented in a deformation controlled setting, and the homogenization analysis in the context of elasticity at finite deformation is then addressed by an integrative approach of finite element method with the optimization algorithms where the interval uncertainty in the microstructure of the material is fully considered. Different deformation-controlled boundary conditions are imposed on the representative volume element, and the interval effective quantities involving the tangent tensor and the first Piola–Kirchhoff stress tensor as well as the strain energy together with the effective moduli are obtained. The influences of different uncertain cases on the interval effective quantities are also analyzed. For the purpose of verification, the results from particle swarm optimization (PSO) algorithm are compared with those obtained from genetic algorithm (GA) and Monte-carlo simulation. The feasibility and validity of the proposed modelling method are evidenced by the well-agreed consequences among the above algorithms.
Keywords
- Finite deformation, Finite element method, GA, Interval homogenization, PSO algorithm
ASJC Scopus subject areas
- Mathematics(all)
- Analysis
- Engineering(all)
- General Engineering
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Mathematics(all)
- Applied Mathematics
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In: Finite Elements in Analysis and Design, Vol. 149, 15.09.2018, p. 15-31.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Multiscale finite element analysis of uncertain-but-bounded heterogeneous materials at finite deformation
AU - Ma, Juan
AU - Du, Wenyi
AU - Gao, Wei
AU - Wriggers, Peter
AU - Xue, Xiangdong
PY - 2018/9/15
Y1 - 2018/9/15
N2 - A new computationally interval homogenization modelling for heterogeneous materials with uncertain-but-bounded parameters is presented in a deformation controlled setting, and the homogenization analysis in the context of elasticity at finite deformation is then addressed by an integrative approach of finite element method with the optimization algorithms where the interval uncertainty in the microstructure of the material is fully considered. Different deformation-controlled boundary conditions are imposed on the representative volume element, and the interval effective quantities involving the tangent tensor and the first Piola–Kirchhoff stress tensor as well as the strain energy together with the effective moduli are obtained. The influences of different uncertain cases on the interval effective quantities are also analyzed. For the purpose of verification, the results from particle swarm optimization (PSO) algorithm are compared with those obtained from genetic algorithm (GA) and Monte-carlo simulation. The feasibility and validity of the proposed modelling method are evidenced by the well-agreed consequences among the above algorithms.
AB - A new computationally interval homogenization modelling for heterogeneous materials with uncertain-but-bounded parameters is presented in a deformation controlled setting, and the homogenization analysis in the context of elasticity at finite deformation is then addressed by an integrative approach of finite element method with the optimization algorithms where the interval uncertainty in the microstructure of the material is fully considered. Different deformation-controlled boundary conditions are imposed on the representative volume element, and the interval effective quantities involving the tangent tensor and the first Piola–Kirchhoff stress tensor as well as the strain energy together with the effective moduli are obtained. The influences of different uncertain cases on the interval effective quantities are also analyzed. For the purpose of verification, the results from particle swarm optimization (PSO) algorithm are compared with those obtained from genetic algorithm (GA) and Monte-carlo simulation. The feasibility and validity of the proposed modelling method are evidenced by the well-agreed consequences among the above algorithms.
KW - Finite deformation
KW - Finite element method
KW - GA
KW - Interval homogenization
KW - PSO algorithm
UR - http://www.scopus.com/inward/record.url?scp=85049458333&partnerID=8YFLogxK
U2 - 10.1016/j.finel.2018.06.001
DO - 10.1016/j.finel.2018.06.001
M3 - Article
AN - SCOPUS:85049458333
VL - 149
SP - 15
EP - 31
JO - Finite Elements in Analysis and Design
JF - Finite Elements in Analysis and Design
SN - 0168-874X
ER -