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    ANN and XFEM-Driven Predictive Framework for Axial Crack Failure in Pipelines: Advancing beyond CorLAS

    Source: Journal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002::page 04026011-1
    Author:
    Zhang, Xinfang
    ,
    Li, Yong
    ,
    Yoosef-Ghodsi, Nader
    ,
    Leung, Juliana Y.
    ,
    Adeeb, Samer
    DOI: 10.1061/JPSEA2.PSENG-1849
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThe CorLAS model is widely used in the pipeline industry for predicting the failure pressure of pipelines with axial surface cracks, primarily due to its low computational and moderate prediction accuracy compared to other alternative models. ...
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      ANN and XFEM-Driven Predictive Framework for Axial Crack Failure in Pipelines: Advancing beyond CorLAS

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4313069
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    contributor authorZhang, Xinfang
    contributor authorLi, Yong
    contributor authorYoosef-Ghodsi, Nader
    contributor authorLeung, Juliana Y.
    contributor authorAdeeb, Samer
    date accessioned2026-08-20T12:04:49Z
    date available2026-08-20T12:04:49Z
    date copyright2026/01/22
    date issued2026
    identifier otherJPSEA2.PSENG-1849.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313069
    description abstractAbstractThe CorLAS model is widely used in the pipeline industry for predicting the failure pressure of pipelines with axial surface cracks, primarily due to its low computational and moderate prediction accuracy compared to other alternative models. ...
    publisherAmerican Society of Civil Engineers
    titleANN and XFEM-Driven Predictive Framework for Axial Crack Failure in Pipelines: Advancing beyond CorLAS
    typeJournal Article
    journal volume17
    journal issue2
    journal titleJournal of Pipeline Systems Engineering and Practice
    identifier doi10.1061/JPSEA2.PSENG-1849
    journal fristpage04026011-1
    journal lastpage04026011-11
    page11
    treeJournal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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