Machine learning methods for predicting residual strength in corroded oil and gas steel pipes

Abstract This review examines machine learning approaches for predicting pipeline residual strength, which is crucial for assessing operational lifespan and safety in industrial applications. We analyze various machine learning models, data preprocessing methods, and evaluation metrics used in exist...

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Bibliographic Details
Main Authors: Qiankun Wang, Hongfang Lu
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:npj Materials Degradation
Online Access:https://doi.org/10.1038/s41529-025-00573-y
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