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  4. Benchmark exercise on image-based permeability determination of engineering textiles: Microscale predictions
 
research article

Benchmark exercise on image-based permeability determination of engineering textiles: Microscale predictions

Syerko, E.
•
Schmidt, T.
•
May, D.
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January 6, 2023
Composites Part A: Applied Science and Manufacturing

Permeability measurements of engineering textiles exhibit large variability as no standardization method currently exists; numerical permeability prediction is thus an attractive alternative. It has all advantages of virtual material characterization, including the possibility to study the impact of material variability and small-scale parameters. This paper presents the results of an international virtual permeability benchmark, which is a first contribution to permeability predictions for fibrous reinforcements based on real images. In this first stage, the focus was on the microscale computation of fiber bundle permeability. In total 16 participants provided 50 results using different numerical methods, boundary conditions, permeability identification techniques. The scatter of the predicted axial permeability after the elimination of inconsistent results was found to be smaller (14%) than that of the transverse permeability (∼24%). Dominant effects on the permeability were found to be the boundary conditions in tangential direction, number of sub-domains used in the renormalization approach, and the permeability identification technique.

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Type
research article
DOI
10.1016/j.compositesa.2022.107397
Author(s)
Syerko, E.
Schmidt, T.
May, D.
Binetruy, C.
Advani, S.G.
Lomov, S.
Silva, L.
Abaimov, S.
Aissa, N.
Akhatov, I.
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Corporate authors
Michaud, V
•
Broggi, G
Date Issued

2023-01-06

Published in
Composites Part A: Applied Science and Manufacturing
Volume

167

Article Number

107397

Subjects

Fabrics/textiles

•

Tow

•

Permeability

•

Computational modellingResin flow

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LPAC  
Available on Infoscience
January 23, 2023
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/194198
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