Integrating convolutional neural network and constitutive model for rapid prediction of stress-strain curves in fibre reinforced polymers: A generalisable approach-Reference-Cited by-同舟云学术

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Integrating convolutional neural network and constitutive model for rapid prediction of stress-strain curves in fibre reinforced polymers: A generalisable approach

Published:2024-05 Issue: Volume:241 Page:112849
ISSN:0264-1275
Container-title:Materials & Design
language:en
Short-container-title:Materials & Design

Author:

Ding Zerong^ORCID,Attar Hamid R^ORCID,Wang Hongyan,Liu Haibao^ORCID,Li Nan^ORCID

Funder

China Scholarship Council

Imperial College London

EPSRC

Publisher

Elsevier BV

Reference36 articles.

1. A mesoscopic approach for the simulation of woven fibre composite forming;Boisse;Compos. Sci. Technol.,2005

2. Forming optimisation embedded in a CAE chain to assess and enhance the structural performance of composite components;Kärger;Compos. Struct.,2018

3. A computationally efficient approach for generating RVEs of various inclusion/fibre shapes;Nakka;Compos. Struct.,2022

4. Structural composites for multifunctional applications: Current challenges and future trends;González;Prog. Mater Sci.,2017

5. Application of the finite element method in the analysis of composite materials: A review;David Muzel;Polym.,2020

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