Study of fatigue crack propagation on modified CT specimens under variable amplitude loadings using machine learning-Reference-Cited by-同舟云学术

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Study of fatigue crack propagation on modified CT specimens under variable amplitude loadings using machine learning

Published:2024-07 Issue: Volume:184 Page:108332
ISSN:0142-1123
Container-title:International Journal of Fatigue
language:en
Short-container-title:International Journal of Fatigue

Author:

Santos B.^ORCID,Infante V.,Barros T.^ORCID,Baptista R.^ORCID

Publisher

Elsevier BV

Reference40 articles.

1. Fatigue failure of aircraft components;Bhaumik;Eng Fail Anal,2008

2. Machine learning-based fatigue life prediction of metal materials: Perspectives of physics-informed and data-driven hybrid methods;Wang;Eng Fract Mech,2023

3. Curved fatigue crack growth prediction under variable amplitude loading by artificial neural network;Wang;Int J Fatigue,2021

4. R. Plank and G. Kuhn, “Fatigue crack propagation under non-proportional mixed mode loading.”.

5. Optimization of a cruciform specimen for fatigue crack growth under in and out-of-phase in-plane biaxial loading conditions;Baptista;Mech Adv Mater Struct,2023

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