Leak detection and localization techniques in oil and gas pipeline: A bibliometric and systematic review

Engineering Failure Analysis, Год журнала: 2023, Номер 146, С. 107060 - 107060

Опубликована: Янв. 14, 2023

Язык: Английский

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Evolution of corrosion prediction models for oil and gas pipelines: From empirical-driven to data-driven

Engineering Failure Analysis, Год журнала: 2023, Номер 146, С. 107097 - 107097

Опубликована: Фев. 2, 2023

Язык: Английский

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Emerging AI technologies for corrosion monitoring in oil and gas industry: A comprehensive review

Engineering Failure Analysis, Год журнала: 2023, Номер 155, С. 107735 - 107735

Опубликована: Окт. 18, 2023

Язык: Английский

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Hydrogen embrittlement and hydrogen-induced crack initiation in additively manufactured metals: A critical review on mechanical and cyclic loading

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 58, С. 1214 - 1239

Опубликована: Фев. 1, 2024

Язык: Английский

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Review of the hydrogen embrittlement and interactions between hydrogen and microstructural interfaces in metallic alloys: Grain boundary, twin boundary, and nano-precipitate

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 72, С. 74 - 109

Опубликована: Май 28, 2024

Язык: Английский

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A review on hydrogen blending in gas network: Insight into safety, corrosion, embrittlement, coatings and liners, and bibliometric analysis

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 60, С. 867 - 889

Опубликована: Фев. 23, 2024

Язык: Английский

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Review of Prediction of Stress Corrosion Cracking in Gas Pipelines Using Machine Learning

Machines, Год журнала: 2024, Номер 12(1), С. 42 - 42

Опубликована: Янв. 8, 2024

Pipeline integrity and safety depend on the detection prediction of stress corrosion cracking (SCC) other defects. In oil gas pipeline systems, a variety corrosion-monitoring techniques are used. The observed data exhibit characteristics nonlinearity, multidimensionality, noise. Hence, data-driven modeling have been widely utilized. To accomplish intelligent enhance control, machine learning (ML)-based approaches developed. Some published papers related to SCC discussed ML their applications, but none works has shown real ability detect or predict in energy pipelines, though fewer researchers tested models prove them under controlled environments laboratories, which is completely different from work field. Looking at current research status, authors believe that there need explore best technologies identify clear gaps; critical review is, therefore, required. objective this study assess status learning’s applications detection, gaps, indicate future directions scientific application point view. This will highlight limitations challenges employing for also discuss importance incorporating domain knowledge expert inputs accuracy reliability predictions. Finally, framework proposed demonstrate process condition assessments pipelines.

Язык: Английский

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The research progress and prospect of data mining methods on corrosion prediction of oil and gas pipelines

Engineering Failure Analysis, Год журнала: 2022, Номер 144, С. 106951 - 106951

Опубликована: Ноя. 24, 2022

Язык: Английский

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A synergistic anti-corrosion system based on durable superhydrophobic F-SiO₂/epoxy coatings and self-powered cathodic protection

Journal of Materials Chemistry A, Год журнала: 2022, Номер 10(36), С. 18616 - 18625

Опубликована: Янв. 1, 2022

This work demonstrates a cost-effective and large-scale strategy for preparing superhydrophobic F-SiO 2 /epoxy resin coating based self-powered synergistic anti-corrosion system effectively protecting metals from corrosion.

Язык: Английский

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Development of the automated temperature control system of the main gas pipeline

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Фев. 22, 2023

This article presents the results of a numerical experiment and an analysis temperature fields (coolers for gas) using cooling elements in case study gas pipeline. An demonstrated several principles formation field, which indicates need to maintain relative pumping. The essence was install unlimited number on purpose this determine at what distance it is possible optimal pumping regime, regarding synthesis control law determination location assessment error depending elements. developed technique allows evaluation system's regulation error.

Язык: Английский

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