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Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution
Modeling the random fiber distribution of a fiber-reinforced composite is of great importance for studying the progressive failure behavior of the material on the micro scale. In this paper, we develop a new algorithm for generating random representative volume elements (RVEs) with statistical equiv...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5509042/ https://www.ncbi.nlm.nih.gov/pubmed/28773744 http://dx.doi.org/10.3390/ma9080624 |
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author | Wang, Wenzhi Dai, Yonghui Zhang, Chao Gao, Xiaosheng Zhao, Meiying |
author_facet | Wang, Wenzhi Dai, Yonghui Zhang, Chao Gao, Xiaosheng Zhao, Meiying |
author_sort | Wang, Wenzhi |
collection | PubMed |
description | Modeling the random fiber distribution of a fiber-reinforced composite is of great importance for studying the progressive failure behavior of the material on the micro scale. In this paper, we develop a new algorithm for generating random representative volume elements (RVEs) with statistical equivalent fiber distribution against the actual material microstructure. The realistic statistical data is utilized as inputs of the new method, which is archived through implementation of the probability equations. Extensive statistical analysis is conducted to examine the capability of the proposed method and to compare it with existing methods. It is found that the proposed method presents a good match with experimental results in all aspects including the nearest neighbor distance, nearest neighbor orientation, Ripley’s K function, and the radial distribution function. Finite element analysis is presented to predict the effective elastic properties of a carbon/epoxy composite, to validate the generated random representative volume elements, and to provide insights of the effect of fiber distribution on the elastic properties. The present algorithm is shown to be highly accurate and can be used to generate statistically equivalent RVEs for not only fiber-reinforced composites but also other materials such as foam materials and particle-reinforced composites. |
format | Online Article Text |
id | pubmed-5509042 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-55090422017-07-28 Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution Wang, Wenzhi Dai, Yonghui Zhang, Chao Gao, Xiaosheng Zhao, Meiying Materials (Basel) Article Modeling the random fiber distribution of a fiber-reinforced composite is of great importance for studying the progressive failure behavior of the material on the micro scale. In this paper, we develop a new algorithm for generating random representative volume elements (RVEs) with statistical equivalent fiber distribution against the actual material microstructure. The realistic statistical data is utilized as inputs of the new method, which is archived through implementation of the probability equations. Extensive statistical analysis is conducted to examine the capability of the proposed method and to compare it with existing methods. It is found that the proposed method presents a good match with experimental results in all aspects including the nearest neighbor distance, nearest neighbor orientation, Ripley’s K function, and the radial distribution function. Finite element analysis is presented to predict the effective elastic properties of a carbon/epoxy composite, to validate the generated random representative volume elements, and to provide insights of the effect of fiber distribution on the elastic properties. The present algorithm is shown to be highly accurate and can be used to generate statistically equivalent RVEs for not only fiber-reinforced composites but also other materials such as foam materials and particle-reinforced composites. MDPI 2016-07-27 /pmc/articles/PMC5509042/ /pubmed/28773744 http://dx.doi.org/10.3390/ma9080624 Text en © 2016 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Wang, Wenzhi Dai, Yonghui Zhang, Chao Gao, Xiaosheng Zhao, Meiying Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution |
title | Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution |
title_full | Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution |
title_fullStr | Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution |
title_full_unstemmed | Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution |
title_short | Micromechanical Modeling of Fiber-Reinforced Composites with Statistically Equivalent Random Fiber Distribution |
title_sort | micromechanical modeling of fiber-reinforced composites with statistically equivalent random fiber distribution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5509042/ https://www.ncbi.nlm.nih.gov/pubmed/28773744 http://dx.doi.org/10.3390/ma9080624 |
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