Numerical predictions of the anisotropic viscoelastic response of uni-directional fibre composites
File(s)Pathan et al - JCOMA-2016 - revised.pdf (1.35 MB)
Accepted version
Author(s)
Pathan, MV
Tagarielli, VL
Patsias, S
Type
Journal Article
Abstract
Finite Element (FE) simulations are conducted to predict the viscoelastic properties of uni-directional (UD) fibre composites. The response of both periodic unit cells and random stochastic volume elements (SVEs) is analysed; the fibres are assumed to behave as linear elastic isotropic solids while the matrix is taken as a linear viscoelastic solid. Monte Carlo analyses are conducted to determine the probability distributions of all viscoelastic properties. Simulations are conducted on SVEs of increasing size in order to determine the suitable size of a representative volume element (RVE). The predictions of the FE simulations are compared to those of existing theories and it is found that the Mori-Tanaka (1973) and Lielens (1999) models are the most effective in predicting the anisotropic viscoelastic response of the RVE.
Date Issued
2016-11-01
Date Acceptance
2016-10-27
Citation
Composites Part A: Applied Science and Manufacturing, 2016, 93, pp.18-32
ISSN
1359-835X
Publisher
Elsevier
Start Page
18
End Page
32
Journal / Book Title
Composites Part A: Applied Science and Manufacturing
Volume
93
Copyright Statement
© 2016, Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Technology Strategy Board
Grant Number
110123
Subjects
Materials
0912 Materials Engineering
0913 Mechanical Engineering
0901 Aerospace Engineering
Notes
publisher: Elsevier articletitle: Numerical predictions of the anisotropic viscoelastic response of uni-directional fibre composites journaltitle: Composites Part A: Applied Science and Manufacturing articlelink: http://dx.doi.org/10.1016/j.compositesa.2016.10.029 content_type: article copyright: © 2016 Elsevier Ltd. All rights reserved.
Publication Status
Published