An efficient deep learning model to predict the structural response of CFRP isogrid tubes-Reference-Cited by-同舟云学术

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An efficient deep learning model to predict the structural response of CFRP isogrid tubes

Published:2023-07 Issue: Volume:316 Page:117043
ISSN:0263-8223
Container-title:Composite Structures
language:en
Short-container-title:Composite Structures

Author:

Gomes Guilherme Ferreira,Ribeiro Junior Ronny Francis,Pereira João Luiz Junho,Francisco Matheus Brendon

Funder

Fundação de Amparo à Pesquisa do Estado de Minas Gerais

Fundação de Amparo à Pesquisa do Estado de São Paulo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Elsevier BV

Subject

Civil and Structural Engineering,Ceramics and Composites

Reference37 articles.

1. Optimization of the static and dynamic characteristics of plates with isogrid stiffeners;Akl;Finite Elem Anal Des,2008

2. Prediction of temperature-frequency-dependent mechanical properties of composites based on thermoplastic liquid resin reinforced with carbon fibers using artificial neural networks;Barbosa;Int J Adv Manuf Technol,2019

3. Buckling behavior of 3D printed composite isogrid structures;Ciccarelli;Proc CIRP,2021

4. Development of an artificial neural network for predicting energy absorption capability of thermoplastic commingled composites;Di Benedetto;Compos Struct,2021

5. Optimization of the layers of composite materials from neural networks with Tsai–Wu failure criterion;Diniz;J Fail Anal Prev,2019

Cited by 2 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. Neural network assisted for parameters uncertainty of isogrid tube under different load types;Mechanics of Advanced Materials and Structures;2024-05

2. Collaborative optimization for variable stiffness composite laminates using a fiber angle description method based on Archimedean spiral function;Composite Structures;2024-02

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