Artificial neural network prediction of transverse modulus in humid conditions for randomly distributed unidirectional fibre reinforced composites: A micromechanics approach-Reference-Cited by-同舟云学术

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Artificial neural network prediction of transverse modulus in humid conditions for randomly distributed unidirectional fibre reinforced composites: A micromechanics approach

Published:2024-06 Issue: Volume:337 Page:118073
ISSN:0263-8223
Container-title:Composite Structures
language:en
Short-container-title:Composite Structures

Author:

Aghabalaei Baghaei K.,Hadigheh S.A.

Funder

Australian Research Council

Publisher

Elsevier BV

Reference67 articles.

1. Durability assessment of FRP-to-concrete bonded connections under moisture condition using data-driven machine learning-based approaches;Aghabalaei Baghaei;Compos Struct,2021

2. Effect of acid attack on FRP-to-concrete bonded interfaces;Hadigheh;Constr Build Mater,2017

3. Effects of seawater immersion on water absorption and mechanical properties of GFRP composites;Bian;J Compos Mater,2012

4. Impact of sea and tap water exposure on the durability of GFRP laminates;Aldajah;Mater Des,2009

5. Hygromechanical coupling in laminate composites and its effect on interlaminar failure;Steinbrecher;Compos A Appl Sci Manuf,2016

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