Perturbation-based stochastic multi-scale computational homogenization method for the determination of the effective properties of composite materials with random properties

Zhou, X.-Y.; Gosling, P.D.; Pearce, C.J.; Kaczmarczyk, L.; Ullah, Z.

Abstract

Quantifying uncertainty in the overall elastic properties of composite materials arising from randomness in the material properties and geometry of composites at microscopic level is crucial in the stochastic analysis of composites. In this paper, a stochastic multi-scale finite element method, which couples the multi-scale computational homogenization method with the second-order perturbation technique, is proposed to calculate the statistics of the overall elasticity properties of composite materials in terms of the mean value and standard deviation. The uncertainties associated with the material properties of the constituents are considered. Performance of the proposed method is evaluated by comparing mean values and coefficients of variation for components of the effective elastic tensor against corresponding values calculated using Monte Carlo simulation for three numerical examples. Results demonstrate that the proposed method has sufficient accuracy to capture the variability in effective elastic properties of the composite induced by randomness in the constituent material properties.

Citation

Zhou, X.-Y., Gosling, P., Pearce, C., Kaczmarczyk, L., & Ullah, Z. (2016). Perturbation-based stochastic multi-scale computational homogenization method for the determination of the effective properties of composite materials with random properties. Computer Methods in Applied Mechanics and Engineering, 300, 84-105. https://doi.org/10.1016/j.cma.2015.10.020

• Journal Article Type: Article
• Acceptance Date: Oct 15, 2015
• Online Publication Date: Nov 17, 2015
• Publication Date: Mar 1, 2016
• Deposit Date: Sep 11, 2024
• Journal: Computer Methods in Applied Mechanics and Engineering
• Print ISSN: 0045-7825
• Electronic ISSN: 1879-2138
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 300
• Pages: 84-105
• DOI: https://doi.org/10.1016/j.cma.2015.10.020
• Public URL: https://durham-repository.worktribe.com/output/2852103
• Additional Information: This article is Open Access at: https://doi.org/10.1016/j.cma.2015.10.020