Multiscale modeling of combined deterministic and stochastic fabric non-uniformity for realistic resin injection simulation

Endruweit, A. and Zeng, X. and Long, A. C . (2014) Multiscale modeling of combined deterministic and stochastic fabric non-uniformity for realistic resin injection simulation. Advanced Manufacturing: Polymer & Composites Science, 1 (1). pp. 3-15. ISSN 2055-0340

Abstract

The local fiber arrangement in a bi-directional fabric formed to a complex shape was modeled considering the stochastic arrangement of filaments within yarns, which determines axial and transverse yarn permeabilities, and the stochastic arrangement of yarns in a fabric, which determines the dimensions of interyarn gap spaces locally. To mimic the uncertainty in fabric forming, drape simulation was randomized in terms of start point and yarn start orientations. From yarn permeabilities and simulated local yarn spacing distributions, local fiber volume fractions and fabric permeabilities were approximated. This allowed resin injection into a deformed fabric to be simulated for different drape scenarios with different probabilities and different degrees of fabric randomness. The results indicate that variability in fabric properties and the forming process affects flow front shapes and times for complete impregnation of the reinforcement.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version cannot be displayed due to copyright restrictions.
Faculty / Department / School: No Faculty
Date Deposited: 19 Jun 2017 00:11
Last Modified: 12 Jul 2017 04:46
Uncontrolled Keywords: fabrics/textiles; resin transfer moulding; permeability, drape; stochastic analysis
Fields of Research : 09 Engineering > 0912 Materials Engineering > 091205 Functional Materials
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: 10.1179/2055035914Y.0000000002
URI: http://eprints.usq.edu.au/id/eprint/32555

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