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    Modularized Physics-Driven Dynamic Response Prediction of Long-Span Bridge and Traffic System Subjected to Stochastic Loads Based on Neural Operators

    Source: Journal of Bridge Engineering:;2025:;Volume ( 030 ):;issue: 010::page 04025065-1
    Author:
    Liu, Yuchen
    ,
    Chen, Suren
    ,
    Han, Yan
    ,
    Xiong, Ziluo
    DOI: 10.1061/JBENF2.BEENG-7551
    Publisher: American Society of Civil Engineers
    Abstract: Abstract The rapid and reliable prediction of dynamic responses in long-span bridges (LSBs) and traffic systems considering dynamic interactions under stochastic loads is crucial for understanding the operational risk for LSBs (e.g., structural safety ...
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      Modularized Physics-Driven Dynamic Response Prediction of Long-Span Bridge and Traffic System Subjected to Stochastic Loads Based on Neural Operators

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314300
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    • Journal of Bridge Engineering

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    contributor authorLiu, Yuchen
    contributor authorChen, Suren
    contributor authorHan, Yan
    contributor authorXiong, Ziluo
    date accessioned2026-08-20T21:19:56Z
    date available2026-08-20T21:19:56Z
    date copyright2025/08/05
    date issued2025
    identifier otherJBENF2.BEENG-7551.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314300
    description abstractAbstract The rapid and reliable prediction of dynamic responses in long-span bridges (LSBs) and traffic systems considering dynamic interactions under stochastic loads is crucial for understanding the operational risk for LSBs (e.g., structural safety ...
    publisherAmerican Society of Civil Engineers
    titleModularized Physics-Driven Dynamic Response Prediction of Long-Span Bridge and Traffic System Subjected to Stochastic Loads Based on Neural Operators
    typeJournal Article
    journal volume30
    journal issue10
    journal titleJournal of Bridge Engineering
    identifier doi10.1061/JBENF2.BEENG-7551
    journal fristpage04025065-1
    journal lastpage04025065-14
    page14
    treeJournal of Bridge Engineering:;2025:;Volume ( 030 ):;issue: 010
    contenttypeFulltext
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