3D representative volume element reconstruction of fiber composites via orientation tensor and substructure features

Yi Li, Wei Chen, Xuejun Jin, Hongyi Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

To provide a seamless integration of manufacturing processing simulation and fiber microstructure modeling, two new stochastic 3D microstructure reconstruction methods are proposed for two types of random fiber composites: random short fiber composites, and Sheet Molding Compounds (SMC) chopped fiber composites. A Random Sequential Adsorption (RSA) algorithm is first developed to embed statistical orientation information into 3D RVE reconstruction of random short fiber composites. For the SMC composites, an optimized Voronoi diagram based approach is developed for capturing the substructure features of SMC chopped fiber composites. The proposed methods are distinguished from other reconstruction works by providing a way of integrating statistical information (fiber orientation tensor) obtained from material processing simulation, as well as capturing the multiscale substructures of the SMC composites.

Original languageEnglish (US)
Title of host publicationProceedings of the American Society for Composites - 31st Technical Conference, ASC 2016
EditorsBarry D. Davidson, Michael W. Czabaj, James G. Ratcliffe
PublisherDEStech Publications Inc.
ISBN (Electronic)9781605953168
StatePublished - 2016
Event31st Annual Technical Conference of the American Society for Composites, ASC 2016 - Williamsburg, United States
Duration: Sep 19 2016Sep 21 2016

Publication series

NameProceedings of the American Society for Composites - 31st Technical Conference, ASC 2016

Other

Other31st Annual Technical Conference of the American Society for Composites, ASC 2016
Country/TerritoryUnited States
CityWilliamsburg
Period9/19/169/21/16

ASJC Scopus subject areas

  • Ceramics and Composites

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