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Micro-Scale Permeability Characterization of Carbon Fiber Composites Using Micrograph Volume Elements

Seuffert, Julian 1; Bittrich, Lars; Cardoso de Oliveira, Leonardo; Spickenheuer, Axel; Kärger, Luise 1
1 Institut für Fahrzeugsystemtechnik (FAST), Karlsruher Institut für Technologie (KIT)


To manufacture a high-performance structure made of continuous fiber reinforced plastics, Liquid Composite Molding processes are used, where a liquid resin infiltrates the dry fibers. For a good infiltration quality without dry spots, it is important to predict the resin flow correctly. Knowledge of the local permeability is an essential precondition for mold-filling simulations. In our approach, the intra-bundle permeability parallel and transverse to the fibers is characterized via periodic fluid dynamic simulations of micro-scale volume elements (VE). We evaluate and compare two approaches: First, an approach to generate VEs based on a statistical distribution of the fibers and fiber diameters. Second, an approach based on micrograph images of samples manufactured with Tailored Fiber Placement (TFP) using the measured fiber distribution. The micrograph images show a higher heterogeneity of the distribution than the statistically generated VEs, which is characterized by large resin areas. This heterogeneity leads to a significantly different permeability compared to the stochastic approach. In conclusion, a pure stochastic approach needs to contain the large heterogeneity of the fiber distribution to predict correct permeability values.

Verlagsausgabe §
DOI: 10.5445/IR/1000139745
Veröffentlicht am 12.11.2021
DOI: 10.3389/fmats.2021.745084
Zitationen: 3
Web of Science
Zitationen: 2
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Fahrzeugsystemtechnik (FAST)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 15.10.2021
Sprache Englisch
Identifikator ISSN: 2296-8016
KITopen-ID: 1000139745
Erschienen in Frontiers in Materials
Verlag Frontiers Media SA
Band 8
Seiten Art. Nr.: 745084
Nachgewiesen in Dimensions
Web of Science
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