Hierarchical framework for quantifying multiscale structures of two-dimensional woven carbon fibre-reinforced composites considering geometric variability

Chao Zhu, Ping Zhu*, Zhao Liu, Wei Tao, Wei Chen

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

The processing and mechanical properties of two-dimensional woven carbon fibre-reinforced composites depend directly on the internal geometrical architecture, which presents typical multiscale nature, while the multiscale structures possess inevitable geometric variabilities during the manufacturing process. This work presents a stochastic multiscale geometric modelling framework containing two developed algorithms to facilitate reconstructing statistically equivalent structures on microscale and mesoscale of two-dimensional woven carbon fibre-reinforced composite considering internal geometric variability. The sequential random perturbation algorithm is proposed to realize the random distribution nature of fibres inside yarns on microscale by sequential smart movements of initial regular distributed fibres. Then, an algorithm based on Gaussian random sequence is developed to characterize the internal variabilities of yarn path and shape on mesoscale via reconstructing correlated stochastic deviations along yarns. The proposed modelling framework effectively reconstructs the geometric models of random microstructure and mesostructure, which is convenient to be implemented into computational micromechanical analysis on both scales, serving as the foundation of the numerical calculation of the multiscale processing and mechanical properties of the studied composite.

Original languageEnglish (US)
Pages (from-to)802-824
Number of pages23
JournalJournal of Industrial Textiles
Volume48
Issue number4
DOIs
StatePublished - Oct 1 2018

Keywords

  • Two-dimensional woven carbon fibre-reinforced composites
  • geometric variability
  • material structural images
  • multiscale geometric modelling
  • statistical analysis
  • statistically equivalent reconstruction

ASJC Scopus subject areas

  • Chemical Engineering (miscellaneous)
  • Materials Science (miscellaneous)
  • Polymers and Plastics
  • Industrial and Manufacturing Engineering

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