Training Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloys

Fatigue cracks are a major defect in metal alloys, and specifically, their study poses defect evaluation challenges in aluminum aircraft alloys. Existing inline inspection tools exhibit measurement uncertainties. The physical-based methods for crack growth prediction utilize stress analysis models a...

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Detalles Bibliográficos
Autores principales: Zafar, Muhammad Hamza, Younis, Hassaan Bin, Mansoor, Majad, Moosavi, Syed Kumayl Raza, Khan, Noman Mujeeb, Akhtar, Naureen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9505683/
https://www.ncbi.nlm.nih.gov/pubmed/36143505
http://dx.doi.org/10.3390/ma15186198

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9505683/
https://www.ncbi.nlm.nih.gov/pubmed/36143505
http://dx.doi.org/10.3390/ma15186198

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