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A self-supervised learning framework based on physics-infor..:
Hanna, John M.
;
Aguado, José V.
;
Comas-Cardona, Sebastien
..
Composites Part A: Applied Science and Manufacturing. 179 (2024) - p. 108019 , 2024
Link:
https://doi.org/10.1016/j.compositesa.2024.108019
RT Journal T1
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
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.compositesa.2024.108019&Exemplar=1&LAN=DE A1 Hanna, John M. A1 Aguado, José V. A1 Comas-Cardona, Sebastien A1 Le Guennec, Yves A1 Borzacchiello, Domenico PB Elsevier BV YR 2024 SN 1359-835X JF Composites Part A: Applied Science and Manufacturing VO 179 SP 108019 LK http://dx.doi.org/https://doi.org/10.1016/j.compositesa.2024.108019 DO https://doi.org/10.1016/j.compositesa.2024.108019 SF ELIB - SuUB Bremen
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