Enhancing pipeline integrity: a comprehensive review of deep learning-enabled finite element analysis for stress corrosion cracking prediction

Pipelines are crucial for transporting energy sources, yet corrosion especially stress corrosion cracking (SCC) poses a complex and potentially catastrophic form of material degradation. Traditional techniques like finite element analysis (FEA) have been utilized for SCC prediction, but it suffers f...

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Bibliografiske detaljer

Principais autores:	Umair Sarwar, Ainul Akmar Mokhtar, Masdi Muhammad, Rano Khan Wassan, Afzal Ahmed Soomro, Majid Ali Wassan, Shuaib Kaka
Format:	Artigo
Sprog:	Inglês
Udgivet:	Taylor & Francis Group 2024-12-01
Serier:	Engineering Applications of Computational Fluid Mechanics
Fag:	Oil and gas steel pipeline finite element analysis stress corrosion cracking prediction deep learning
Online adgang:	https://www.tandfonline.com/doi/10.1080/19942060.2024.2302906
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