The Effect of Partitioning on the Clustering Index of Randomly-Oriented Fiber Composites: A Parametric Study
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Accepted Manuscript (AM)
Author(s)
Javanbakht, Z
Hall, W
Öchsner, A
Year published
2017
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In the current study, five cases of fiber distributions are considered in a fiber-reinforced composite: one random, three partitioned (one uniform and two biased cases), and one aligned case for benchmarking. The finite element method and the principal component analysis were used to interpret the results of orientation tensors and detect any possible clusterings of a representative volume element (RVE). The obtained effective conductivity values were extensively controlled by the fiber volume fraction. At the same time, the uniformity of the random distributions could be recognized. Cross-partition resistance was also ...
View more >In the current study, five cases of fiber distributions are considered in a fiber-reinforced composite: one random, three partitioned (one uniform and two biased cases), and one aligned case for benchmarking. The finite element method and the principal component analysis were used to interpret the results of orientation tensors and detect any possible clusterings of a representative volume element (RVE). The obtained effective conductivity values were extensively controlled by the fiber volume fraction. At the same time, the uniformity of the random distributions could be recognized. Cross-partition resistance was also detected for the partitioned cases which contributed to a reduced heat transfer capability. Finally, the clustering indexes did not show a direct correlation with the conductivity results, and thus a case-by-case investigation is recommended to consider the anisotropic aspects of a microstructure.
View less >
View more >In the current study, five cases of fiber distributions are considered in a fiber-reinforced composite: one random, three partitioned (one uniform and two biased cases), and one aligned case for benchmarking. The finite element method and the principal component analysis were used to interpret the results of orientation tensors and detect any possible clusterings of a representative volume element (RVE). The obtained effective conductivity values were extensively controlled by the fiber volume fraction. At the same time, the uniformity of the random distributions could be recognized. Cross-partition resistance was also detected for the partitioned cases which contributed to a reduced heat transfer capability. Finally, the clustering indexes did not show a direct correlation with the conductivity results, and thus a case-by-case investigation is recommended to consider the anisotropic aspects of a microstructure.
View less >
Journal Title
Defect and Diffusion Forum
Volume
380
Copyright Statement
© 2017 Trans Tech Publications. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
Subject
Condensed matter physics
Physical chemistry
Materials engineering
Numerical modelling and mechanical characterisation