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    Data-Driven Identification of Variational Equations for Vortex-Induced Vibration Systems

    Source: Journal of Applied Mechanics:;2025:;volume( 092 ):;issue: 004::page 41001-1
    Author:
    Lu, Kang
    ,
    Zeng, Zheng
    ,
    Xiong, Xiong
    ,
    Wang, Xuefeng
    ,
    Gu, Xudong
    ,
    Hu, Rongchun
    ,
    Deng, Zichen
    DOI: 10.1115/1.4067572
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this study, a data-driven approach using the embedded variational principle is used to identify the variational equations of vortex-induced vibration fluid–structure interaction systems, in particular the coupling term and the aerodynamic damping term. Under the data-driven paradigm, variational equation identification is primarily accomplished through five steps: collecting discrete data, setting variational functions, building the product function, solving linear equations, and evaluating errors. The explicit variational equations of the system are eventually determined automatically from the excitation and response. Gaussian white noise is added to the excitation to evaluate the method's noise robustness. The findings demonstrate that numerical estimation which stays away from higher-order derivatives significantly enhances the variational law identification's noise robustness by taking advantage of the variational law's lower-order time derivatives. Furthermore, the arbitrariness of the variational setting inherent in the variational law significantly improves the effectiveness of data utilization and lowers the necessary data volume. In addition, a system of linear equations is solved by identifying connected nonlinear equations, which significantly increases modeling efficiency. The basis for engineering modeling, optimization, and control of intricate fluid–structure interaction systems are provided by these benefits.
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      Data-Driven Identification of Variational Equations for Vortex-Induced Vibration Systems

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4305228
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    contributor authorLu, Kang
    contributor authorZeng, Zheng
    contributor authorXiong, Xiong
    contributor authorWang, Xuefeng
    contributor authorGu, Xudong
    contributor authorHu, Rongchun
    contributor authorDeng, Zichen
    date accessioned2025-04-21T09:58:32Z
    date available2025-04-21T09:58:32Z
    date copyright1/24/2025 12:00:00 AM
    date issued2025
    identifier issn0021-8936
    identifier otherjam_92_4_041001.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4305228
    description abstractIn this study, a data-driven approach using the embedded variational principle is used to identify the variational equations of vortex-induced vibration fluid–structure interaction systems, in particular the coupling term and the aerodynamic damping term. Under the data-driven paradigm, variational equation identification is primarily accomplished through five steps: collecting discrete data, setting variational functions, building the product function, solving linear equations, and evaluating errors. The explicit variational equations of the system are eventually determined automatically from the excitation and response. Gaussian white noise is added to the excitation to evaluate the method's noise robustness. The findings demonstrate that numerical estimation which stays away from higher-order derivatives significantly enhances the variational law identification's noise robustness by taking advantage of the variational law's lower-order time derivatives. Furthermore, the arbitrariness of the variational setting inherent in the variational law significantly improves the effectiveness of data utilization and lowers the necessary data volume. In addition, a system of linear equations is solved by identifying connected nonlinear equations, which significantly increases modeling efficiency. The basis for engineering modeling, optimization, and control of intricate fluid–structure interaction systems are provided by these benefits.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleData-Driven Identification of Variational Equations for Vortex-Induced Vibration Systems
    typeJournal Paper
    journal volume92
    journal issue4
    journal titleJournal of Applied Mechanics
    identifier doi10.1115/1.4067572
    journal fristpage41001-1
    journal lastpage41001-13
    page13
    treeJournal of Applied Mechanics:;2025:;volume( 092 ):;issue: 004
    contenttypeFulltext
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