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  • Discrete element method for generating random fibre distributions_Final

    Rights statement: This is the author’s version of a work that was accepted for publication in Composites Part B : Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Composites Part B : Engineering, 90, 2016 DOI: 10.1016/j.compositesb.2016.01.037

    Accepted author manuscript, 1.77 MB, PDF document

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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Discrete element method for generating random fibre distributions in micromechanical models of fibre reinforced composite laminates

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published
<mark>Journal publication date</mark>1/04/2016
<mark>Journal</mark>Composites Part B: Engineering
Volume90
Number of pages8
Pages (from-to)485-492
Publication StatusPublished
Early online date4/02/16
<mark>Original language</mark>English

Abstract

A new approach is presented for generating random distribution of fibres in the representative volume element (RVE) of fibre reinforced composite laminates. The approach is based on discrete element method (DEM) and experimental data of fibre diameter distribution. It overcomes the jamming limit appeared in previous methods and is capable of generating high volume fractions of fibres with random distributions and any specified inter-fibre distances. Statistical analysis is then carried out on the fibre distributions generated within the RVEs, which show good agreement with experiments in all statistics analysed. The effective elastic properties of the generated RVEs are finally analysed by finite element method, which results show more reasonable agreement with the experimental results than previous methods.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Composites Part B : Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Composites Part B : Engineering, 90, 2016 DOI: 10.1016/j.compositesb.2016.01.037