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

IF 5.9 1区工程技术 Q1 ENGINEERING, MECHANICAL

Engineering Applications of Computational Fluid Mechanics Pub Date : 2024-01-23 DOI:10.1080/19942060.2024.2302906

Umair Sarwar, Ainul Akmar Mokhtar, Masdi Muhammad, Rano Khan Wassan, Afzal Ahmed Soomro, Majid Ali Wassan, Shuaib Kaka

引用次数: 0

Abstract

Pipelines are crucial for transporting energy sources, yet corrosion especially stress corrosion cracking (SCC) poses a complex and potentially catastrophic form of material degradation. Traditiona...

查看原文本刊更多论文

提高管道完整性：全面回顾用于应力腐蚀开裂预测的深度学习有限元分析

管道是运输能源的关键，但腐蚀尤其是应力腐蚀开裂（SCC）是一种复杂且可能造成灾难性后果的材料退化形式。传统上，应力腐蚀开裂（SCC）会导致管道...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Engineering Applications of Computational Fluid Mechanics ENGINEERING, MULTIDISCIPLINARY-ENGINEERING, MECHANICAL

CiteScore

10.60

自引率

14.80%

发文量

109

审稿时长

3.4 months

期刊介绍： The aim of Engineering Applications of Computational Fluid Mechanics is a continuous and timely dissemination of innovative, practical and industrial applications of computational techniques to solve the whole range of hitherto intractable fluid mechanics problems. The journal is a truly interdisciplinary forum and publishes original contributions on the latest advances in numerical methods in fluid mechanics and their applications to various engineering fields including aeronautic, civil, environmental, hydraulic and mechanical. The journal has a distinctive and balanced international contribution, with emphasis on papers addressing practical problem-solving by means of robust numerical techniques to generate precise flow prediction and optimum design, and those fostering the thorough understanding of the physics of fluid motion. It is an open access journal.