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Directional diffusion of moisture into unidirectional carbon fiber/epoxy Composites: Experiments and modeling / Feras Korkees, Sue Alston, Cris Arnold

Polymer Composites, Volume: 39, Issue: S4, Pages: E2305 - E2315

Swansea University Authors: Feras Korkees, Sue Alston, Cris Arnold

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DOI (Published version): 10.1002/pc.24626

Abstract

Water diffusion into composites in different directions was examined in this study with the aim of determining the best way of measuring diffusion coefficients and to provide values to compare with model predictions. Water absorption behavior of unreinforced epoxy resins and carbon fiber reinforced...

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Published in: Polymer Composites
ISSN: 0272-8397
Published: 2018
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URI: https://cronfa.swan.ac.uk/Record/cronfa36153
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Abstract: Water diffusion into composites in different directions was examined in this study with the aim of determining the best way of measuring diffusion coefficients and to provide values to compare with model predictions. Water absorption behavior of unreinforced epoxy resins and carbon fiber reinforced epoxy composite materials was investigated with long-term exposure to different environmental conditions. Initial Fickian absorption was observed followed by a slower second stage that continues for at least 3.7 years. Fiber architecture was found to be an important aspect of controlling absorption, where water diffusion along fibers was observed to be about three times faster than across the fibers and about seven times faster than through the thickness. A three-dimensional finite element computer model based on Fickian diffusion behavior was developed to predict the levels of moisture absorption under hot/humid environments. A multi-scale modeling approach was used which allowed the results of simulations at the micro-structural level to be used to predict the diffusivity in different directions. The modeled diffusion coefficients showed high dependency on the detailed micro-structure. Experimental results provided a baseline for the validation of the model, and it was found that these data could be closely predicted using a reasonable micro-structure characterization.
College: College of Engineering
Issue: S4
Start Page: E2305
End Page: E2315