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    Knowledge-Enhanced Autoencoder with Koopman Theory for Dimension Reduction and its Application to Wind Pressure

    Source: Journal of Engineering Mechanics:;2026:;Volume ( 152 ):;issue: 007::page 04026030-1
    Author:
    Yu, Xinyang
    ,
    Wu, Teng
    DOI: 10.1061/JENMDT.EMENG-8636
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThe strongly nonlinear nature of Navier–Stokes equations governing bluff-body aerodynamics suggests that a significant amount of aerodynamic data is needed to accurately characterize the wind effects on civil structures. Since the aerodynamic data ...
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      Knowledge-Enhanced Autoencoder with Koopman Theory for Dimension Reduction and its Application to Wind Pressure

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4311353
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    contributor authorYu, Xinyang
    contributor authorWu, Teng
    date accessioned2026-08-20T10:51:13Z
    date available2026-08-20T10:51:13Z
    date copyright2026/05/13
    date issued2026
    identifier otherJENMDT.EMENG-8636.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311353
    description abstractAbstractThe strongly nonlinear nature of Navier–Stokes equations governing bluff-body aerodynamics suggests that a significant amount of aerodynamic data is needed to accurately characterize the wind effects on civil structures. Since the aerodynamic data ...
    publisherAmerican Society of Civil Engineers
    titleKnowledge-Enhanced Autoencoder with Koopman Theory for Dimension Reduction and its Application to Wind Pressure
    typeJournal Article
    journal volume152
    journal issue7
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/JENMDT.EMENG-8636
    journal fristpage04026030-1
    journal lastpage04026030-14
    page14
    treeJournal of Engineering Mechanics:;2026:;Volume ( 152 ):;issue: 007
    contenttypeFulltext
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