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Benchmark exercise on image-based permeability determination of engineering textiles: Microscale predictions
Nantes Université, France.
RISE Research Institutes of Sweden, Materials and Production, Polymeric Materials and Composites. National University of Singapore, Singapore.ORCID iD: 0000-0001-9507-3023
Skolkovo Institute of Science and Technology, Russia.
Number of Authors: 402023 (English)In: Composites. Part A, Applied science and manufacturing, ISSN 1359-835X, E-ISSN 1878-5840, Vol. 167, article id 107397Article in journal (Refereed) Published
Abstract [en]

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. 

Place, publisher, year, edition, pages
Elsevier Ltd , 2023. Vol. 167, article id 107397
Keywords [en]
Fabrics/textiles, Tow, Permeability, Computational modelling, Besin flow, Forecasting, Mechanical permeability, Numerical methods, Textiles, A fabric/textile, A tow, B permeability, C computational modeling, Computational modelling, E resin flow, Fabric/textiles, Permeability identification, Permeability prediction, Resin flows, Boundary conditions
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:ri:diva-65472DOI: 10.1016/j.compositesa.2022.107397Scopus ID: 2-s2.0-85146147537OAI: oai:DiVA.org:ri-65472DiVA, id: diva2:1766457
Note

 Funding details: EP/P006701/1; Funding details: Engineering and Physical Sciences Research Council, EPSRC; Funding details: University of Nottingham; Funding text 1: M. Matveev and A. Endruweit are grateful for the support through the University of Nottingham's Digital Initiatives programme and access to the Augusta HPC service. M. Matveev was supported by the Engineering and Physical Sciences Research Council, UK, through the EPSRC Future Composites Manufacturing Research Hub [EP/P006701/1].; Funding text 2: M. Matveev and A. Endruweit are grateful for the support through the University of Nottingham’s Digital Initiatives programme and access to the Augusta HPC service. M. Matveev was supported by the Engineering and Physical Sciences Research Council, UK, through the EPSRC Future Composites Manufacturing Research Hub [EP/P006701/1].

Available from: 2023-06-13 Created: 2023-06-13 Last updated: 2023-12-22Bibliographically approved

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Rouhi, Mohammad

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