Stochastic homogenized effective properties of three-dimensional composite material with full randomness and correlation in the microstructure

authored by: Juan Ma, Suqin Zhang, Peter Wriggers, Wei Gao, Laura De Lorenzis
Abstract: In this work, random homogenization analysis for the effective properties of composite materials with unidirectional fibers is addressed by combining the equivalent inclusion method with the Random Factor Method (RFM). The randomness of the micro-structural morphology and constituent material properties as well as the correlation among these random parameters are fully considered, and stochastic effective properties including effective elastic tensor and effective elastic properties together with their correlation are sought. Results from the RFM and the Monte-Carlo Method (MCM) are compared, and the impact of randomness and correlation of the micro-structural parameters on the random homogenized results are investigated by the two methods. Finally, the correlation coefficients of the effective properties are obtained by the MCM. The RFM is found to deliver rapid results with comparable accuracy to the MCM approach.
Organisation(s): Institute of Continuum Mechanics
External Organisation(s): Xidian University
University of New South Wales (UNSW)
Technische Universität Braunschweig
Type: Article
Journal: Computers and Structures
Volume: 144
Pages: 62-74
No. of pages: 13
ISSN: 0045-7949
Publication date: 03.09.2014
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Civil and Structural Engineering, Modelling and Simulation, General Materials Science, Mechanical Engineering, Computer Science Applications
Electronic version(s): https://doi.org/10.1016/j.compstruc.2014.06.003 (Access: Closed)
: Details in the research portal "Research@Leibniz University"

BibTeX

@article{4e6ee06f48064ad3b8ca1ca75e4ddb13,
title = "Stochastic homogenized effective properties of three-dimensional composite material with full randomness and correlation in the microstructure",
abstract = "In this work, random homogenization analysis for the effective properties of composite materials with unidirectional fibers is addressed by combining the equivalent inclusion method with the Random Factor Method (RFM). The randomness of the micro-structural morphology and constituent material properties as well as the correlation among these random parameters are fully considered, and stochastic effective properties including effective elastic tensor and effective elastic properties together with their correlation are sought. Results from the RFM and the Monte-Carlo Method (MCM) are compared, and the impact of randomness and correlation of the micro-structural parameters on the random homogenized results are investigated by the two methods. Finally, the correlation coefficients of the effective properties are obtained by the MCM. The RFM is found to deliver rapid results with comparable accuracy to the MCM approach.",
keywords = "Monte-Carlo method, Random effective properties, Random factor method, Random homogenization, Randomness and correlation",
author = "Juan Ma and Suqin Zhang and Peter Wriggers and Wei Gao and {De Lorenzis}, Laura",
note = "Funding Information: The first author gratefully acknowledges the support of the Alexander von Humboldt-Stiftung through a {\textquoteleft}Humboldt Research Fellowship for Postdoctoral Researchers{\textquoteright} for a research stay at the Leibniz Universit{\"a}t Hannover. The support of Natural Science Foundation of China to the Project ( 11102143 ) “Random homogenization of heterogeneous materials with infinitesimal and finite deformation” is also sincerely acknowledged. L. De Lorenzis would like to acknowledge the European Research Council , ERC Starting Researcher Grant “INTERFACES”, Grant Agreement N. 279439 . Publisher Copyright: {\textcopyright} 2014 Elsevier Ltd. All rights reserved. Copyright: Copyright 2014 Elsevier B.V., All rights reserved.",
year = "2014",
month = sep,
day = "3",
doi = "10.1016/j.compstruc.2014.06.003",
language = "English",
volume = "144",
pages = "62--74",
journal = "Computers and Structures",
issn = "0045-7949",
publisher = "Elsevier Ltd.",
}