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dc.contributor.authorVerdín Martinez, Adrián
dc.contributor.authorSosa Hernandez, Eliceo
dc.contributor.authorAlamilla Lopez, Jorge Luis
dc.contributor.authorLiu, Hongbo
dc.date.accessioned2026-08-20T12:06:14Z
dc.date.available2026-08-20T12:06:14Z
dc.date.copyright2026/02/26
dc.date.issued2026
dc.identifier.otherJPSEA2.PSENG-1938.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313101
dc.description.abstractAbstractA scheme based on two historical in-line inspection data sets was developed to estimate the evolution of pitting depth caused by internal corrosion in pipelines. This process involved carefully aligning inspection pitting data and modeling pitting ...Practical ApplicationsPipelines serve as the backbone of energy transportation, but internal corrosion can weaken the steel, leading to costly failures. This study presents a practical method for predicting and managing internal corrosion by combining ...
dc.publisherAmerican Society of Civil Engineers
dc.titlePipeline Corrosion Pits Growth Prediction with Probabilistic Model and Artificial Neural Network
dc.typeJournal Article
dc.journal.volume17
dc.journal.issue2
dc.journal.titleJournal of Pipeline Systems Engineering and Practice
dc.identifier.doi10.1061/JPSEA2.PSENG-1938
dc.journal.fristpage04026018-1
dc.journal.lastpage04026018-9
dc.page9
dc.treeJournal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002
dc.contenttypeFulltext


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