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Estimation of burst pressure of pipelines with interacting corrosion clusters based on machine learning models

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dc.contributor.authorMensah, Abraham
dc.contributor.authorSriramula, Srinivas
dc.contributor.institutionUniversity of Aberdeen.National Decommissioning Centreen
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.date.accessioned2023-10-17T10:37:02Z
dc.date.available2023-10-17T10:37:02Z
dc.date.issued2023-10
dc.descriptionAcknowledgments The first author would like to thank the Ghana National Petroleum Corporation (GNPC) Foundation for funding the PhD studies at the University of Aberdeen. The first author also acknowledges the research support from Net Zero Technology Centre and University of Aberdeen through their partnership in the UK National Decommissioning Centre.en
dc.description.statusPeer revieweden
dc.format.extent14
dc.format.extent4676205
dc.identifier281346159
dc.identifier5ed7f010-becb-49d0-9b7c-f09dd4f1df53
dc.identifier85171870063
dc.identifier.citationMensah, A & Sriramula, S 2023, 'Estimation of burst pressure of pipelines with interacting corrosion clusters based on machine learning models', Journal of Loss Prevention in the Process Industries, vol. 85, 105176. https://doi.org/10.1016/j.jlp.2023.105176en
dc.identifier.doi10.1016/j.jlp.2023.105176
dc.identifier.issn0950-4230
dc.identifier.otherORCID: /0000-0001-6158-8686/work/145112902
dc.identifier.urihttps://hdl.handle.net/2164/21928
dc.identifier.vol85en
dc.language.isoeng
dc.relation.ispartofJournal of Loss Prevention in the Process Industriesen
dc.subjectpipeline burst pressureen
dc.subjectinteracting corrosion clustersen
dc.subjectimproved corrosion defect shapesen
dc.subjectfinite element methodsen
dc.subjectsupervised machine learningen
dc.subjectTA Engineering (General). Civil engineering (General)en
dc.subject.lccTAen
dc.titleEstimation of burst pressure of pipelines with interacting corrosion clusters based on machine learning modelsen
dc.typeJournal articleen

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