Numerical prediction strategy of fabric in‐plane permeability considering realistic inter‐ and intra‐tow geometry

Abstract Permeability quantifies the flow conductivity of fabric reinforcements and is key to predicting mold filling times and resin flow in liquid composite molding (LCM). Flow depends on the micron‐level channels within the tows and the millimeter‐level channels between them. This study presents a general multi‐scale permeability prediction framework for fabrics considering realistic inter‐ and intra‐tow geometry. A misaligned fiber representative volume element model was constructed by a random perturbation method at the micro‐scale with orientation parameters identified from microscopic images of the cross‐section. At the meso‐scale, a tow cross‐section wrapping algorithm and an interference elimination algorithm were proposed to construct continuous as‐woven tows from the virtual fiber compression simulation. The governing fluid dynamics equations were solved to obtain the flow field within the multi‐scale gaps and compute the permeability. The simplified model's permeability predictions differed from experimental results by 12.7% to 16%. This work provides valuable insights for further research and development in LCM. Highlights Fabric permeability framework considers realistic tow geometry for prediction. Microscale misaligned fiber SVE model predicts tow permeability. Adaptive winding & interference algorithms aid tow description transition. A simplified model predicts permeability reasonably without 3D measurements.

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Publication Details

Journal
Polymer Composites
Published
2024-08-23
DOI
https://doi.org/10.1002/pc.28962
Citations
5
Primary Topic
Textile materials and evaluations
Type
article
Field-Weighted Citation Impact
0.84

Funders

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article

Numerical prediction strategy of fabric in‐plane permeability considering realistic inter‐ and intra‐tow geometry

Long Cheng, Junzhen Chen, Jianjun Jiang, Scott E. Stapleton et al.
5 citations
Polymer Composites
Textile materials and evaluations
0.84
article

Numerical prediction strategy of fabric in‐plane permeability considering realistic inter‐ and intra‐tow geometry

Long Cheng, Junzhen Chen, Jianjun Jiang, Scott E. Stapleton, Yujun Li, Yongkang Wang
article en
5 citations

Abstract

Abstract Permeability quantifies the flow conductivity of fabric reinforcements and is key to predicting mold filling times and resin flow in liquid composite molding (LCM). Flow depends on the micron‐level channels within the tows and the millimeter‐level channels between them. This study presents a general multi‐scale permeability prediction framework for fabrics considering realistic inter‐ and intra‐tow geometry. A misaligned fiber representative volume element model was constructed by a random perturbation method at the micro‐scale with orientation parameters identified from microscopic images of the cross‐section. At the meso‐scale, a tow cross‐section wrapping algorithm and an interference elimination algorithm were proposed to construct continuous as‐woven tows from the virtual fiber compression simulation. The governing fluid dynamics equations were solved to obtain the flow field within the multi‐scale gaps and compute the permeability. The simplified model's permeability predictions differed from experimental results by 12.7% to 16%. This work provides valuable insights for further research and development in LCM. Highlights Fabric permeability framework considers realistic tow geometry for prediction. Microscale misaligned fiber SVE model predicts tow permeability. Adaptive winding & interference algorithms aid tow description transition. A simplified model predicts permeability reasonably without 3D measurements.

Polymer CompositesVol. 45(18)
University of Massachusetts Lowell (US), Northwestern Polytechnical University (CN)
China Postdoctoral Science Foundation, Chinese Aeronautical Establishment, Key Research and Development Projects of Shaanxi Province, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 33%
Textile materials and evaluations
0.84
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