A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction-Reference-Cited by-同舟云学术

A self-supervised learning framework based on physics-informed and convolutional neural networks to identify local anisotropic permeability tensor from textiles 2D images for filling pattern prediction

Published:2024-04 Issue: Volume:179 Page:108019
ISSN:1359-835X
Container-title:Composites Part A: Applied Science and Manufacturing
language:en
Short-container-title:Composites Part A: Applied Science and Manufacturing

Author:

Hanna John M.^ORCID,Aguado José V.^ORCID,Comas-Cardona Sebastien^ORCID,Le Guennec Yves^ORCID,Borzacchiello Domenico

Publisher

Elsevier BV

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4. Experimental determination of the permeability of textiles: A benchmark exercise;Arbter;Composites A,2011

5. Experimental determination of the permeability of engineering textiles: Benchmark II;Vernet;Composites A,2014

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