Multi-scale collaborative prediction of optimal configuration for carbon fiber woven composites based on deep learning neural networks-Reference-Cited by-同舟云学术

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Multi-scale collaborative prediction of optimal configuration for carbon fiber woven composites based on deep learning neural networks

Published:2024-07 Issue: Volume:339 Page:118165
ISSN:0263-8223
Container-title:Composite Structures
language:en
Short-container-title:Composite Structures

Author:

Wang Zefei^ORCID,Zhao Changcai,Yang Zhuoyun,Wang Keqi,Dong Guojiang,Starostenkov M.D.^ORCID

Publisher

Elsevier BV

Reference47 articles.

1. Reliability-based design for lightweight vehicle structures with uncertain manufacturing accuracy;Xu;App Math Model,2021

2. Design and manufacture of thermoplastic carbon fiber/polyethylene terephthalate composites underbody shield to protect the lithium-ion batteries for electric mobility from ground impact;Um;Compos B Eng,2022

3. Design and manufacture of automotive hybrid steel/carbon fiber composite B-pillar component with high crashworthiness;Kim;International Journal of Precision Engineering and Manufacturing-Green Technology,2021

4. 3D printed continuous fiber reinforced composite lightweight structures: A review and outlook;Cheng;Compos B Eng,2023

5. Tensile behavior of improved CFRP-square hollow steel tube composite member strengthened with thick-walled steel tube;Zu;Constr Build Mater,2023

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial neural network-based homogenization model for predicting multiscale thermo-mechanical properties of woven composites;International Journal of Solids and Structures;2024-09

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