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

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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Bibliographic Details
Main Authors: Umair Sarwar, Ainul Akmar Mokhtar, Masdi Muhammad, Rano Khan Wassan, Afzal Ahmed Soomro, Majid Ali Wassan, Shuaib Kaka
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
Oil and gas
steel pipeline
finite element analysis
stress corrosion cracking prediction
deep learning
Online Access:https://www.tandfonline.com/doi/10.1080/19942060.2024.2302906

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