Greedy-based approach for generating anisotropic random fiber distributions of unidirectional composites and transverse mechanical properties prediction

[Display omitted] •A novel greedy-based algorithm is proposed to generate random fiber distributions.•The generated anisotropic RVEs are statistically equivalent to real composites.•The effects of anisotropy on transverse mechanical properties are discussed. A novel adaptive greedy-based generation...

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Bibliographic Details
Published in:Computational materials science Vol. 218; p. 111966
Main Authors: Li, Mengze, Zhang, Haowei, Ma, Jiahe, Li, Shuran, Zhu, Weidong, Ke, Yinglin
Format: Journal Article
Language:English
Published: Elsevier B.V 05.02.2023
Subjects:
Anisotropy
Greedy algorithm
Mechanical properties
Polymer-matrix composites
Statistics
Polymer-matrix composites
Mechanical properties
Greedy algorithm
Anisotropy
Statistics
ISSN:0927-0256, 1879-0801
Online Access:Get full text
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Summary:[Display omitted] •A novel greedy-based algorithm is proposed to generate random fiber distributions.•The generated anisotropic RVEs are statistically equivalent to real composites.•The effects of anisotropy on transverse mechanical properties are discussed. A novel adaptive greedy-based generation (GBG) algorithm is proposed to generate 2D random distribution of fibers for unidirectional composites. Inspired by greedy algorithm, the “fitness function” is introduced to better overcome the jamming limit of the traditional hard‐core method than most published algorithms and generate representative volume element (RVE) with high fiber volume fraction adaptively. The good agreement of statistical analysis with experiments suggests that the generated anisotropic RVEs is statistically equivalent to real composites. The influence of anisotropy on mechanical properties and progressive failure process is further revealed based on finite element method (FEM) using a progressive damage model. The results show that the predicted transverse elastic and strength properties are both anisotropic, which is not consistent with the traditional transverse isotropic hypothesis. The proposed algorithm can generate RVEs with high fiber volume fraction (up to 80%) and provide anisotropic RVEs statistically equivalent to real composites, and thus can serve as a promising method to guide the design and analysis of composites.
ISSN:0927-0256
1879-0801
DOI:10.1016/j.commatsci.2022.111966