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    Multisource Feature Aggregation Approach for Predicting Extreme Pitting Depth Distributions of In Situ Bridge Cable Wires

    Source: Journal of Bridge Engineering:;2026:;Volume ( 031 ):;issue: 008::page 04026037-1
    Author:
    Zhang, He
    ,
    Xin, Yuchen
    ,
    Yao, Linjie
    ,
    Zheng, Xianglong
    ,
    Zhang, Zhicheng
    DOI: 10.1061/JBENF2.BEENG-8078
    Publisher: American Society of Civil Engineers
    Abstract: Abstract Extreme pitting depths in bridge cable steel wires serve as fatigue crack initiation sites, making accurate assessment crucial for failure risk prediction. Existing methods require rust removal and cable disassembly, which not only disrupts ...
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      Multisource Feature Aggregation Approach for Predicting Extreme Pitting Depth Distributions of In Situ Bridge Cable Wires

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314350
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    contributor authorZhang, He
    contributor authorXin, Yuchen
    contributor authorYao, Linjie
    contributor authorZheng, Xianglong
    contributor authorZhang, Zhicheng
    date accessioned2026-08-20T21:22:15Z
    date available2026-08-20T21:22:15Z
    date copyright2026/05/21
    date issued2026
    identifier otherJBENF2.BEENG-8078.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314350
    description abstractAbstract Extreme pitting depths in bridge cable steel wires serve as fatigue crack initiation sites, making accurate assessment crucial for failure risk prediction. Existing methods require rust removal and cable disassembly, which not only disrupts ...
    publisherAmerican Society of Civil Engineers
    titleMultisource Feature Aggregation Approach for Predicting Extreme Pitting Depth Distributions of In Situ Bridge Cable Wires
    typeJournal Article
    journal volume31
    journal issue8
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/JBENF2.BEENG-8078
    journal fristpage04026037-1
    journal lastpage04026037-18
    page18
    treeJournal of Bridge Engineering:;2026:;Volume ( 031 ):;issue: 008
    contenttypeFulltext
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