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    Conditional Simulation of Nonstationary Fluctuating Wind Speeds for Long-Span Bridges

    Source: Journal of Engineering Mechanics:;2014:;Volume ( 140 ):;issue: 001
    Author:
    You-Lin
    ,
    Xu
    ,
    Liang
    ,
    Hu
    ,
    Ahsan
    ,
    Kareem
    DOI: 10.1061/(ASCE)EM.1943-7889.0000589
    Publisher: American Society of Civil Engineers
    Abstract: This paper presents a computationally efficient method for the conditional simulation of nonstationary fluctuating wind speeds for the buffeting analysis of long-span bridges. The fluctuating wind speeds, with part of their time histories measured at some points, are regarded as a zero-mean nonstationary Gaussian vector process characterized by an evolutionary power spectral density (EPSD) matrix. The Kriging method is then applied to the random vector of the Fourier coefficients of the evolutionary vector process for conditional simulation. A mathematical proof of this conditional simulation is provided. A fast algorithm of the conditional simulation is further derived, by converting the Cholesky decomposition of a large size covariance matrix of the Fourier coefficients into the Cholesky decomposition of a series of small-size coherence matrices with much less computational time. The procedure for implementing the fast algorithm-based conditional simulation method is detailed. Finally, this method is applied for the conditional simulation of typhoon-induced nonstationary wind speed time histories for the buffeting analysis of Stonecutters Bridge in Hong Kong. The time domain buffeting responses of the bridge obtained using the conditionally simulated wind speed time histories indicate that the proposed simulation method is feasible and applicable.
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      Conditional Simulation of Nonstationary Fluctuating Wind Speeds for Long-Span Bridges

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    http://yetl.yabesh.ir/yetl1/handle/yetl/61080
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    contributor authorYou-Lin
    contributor authorXu
    contributor authorLiang
    contributor authorHu
    contributor authorAhsan
    contributor authorKareem
    date accessioned2017-05-08T21:44:12Z
    date available2017-05-08T21:44:12Z
    date copyrightJanuary 2014
    date issued2014
    identifier other%28asce%29em%2E1943-7889%2E0000598.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/61080
    description abstractThis paper presents a computationally efficient method for the conditional simulation of nonstationary fluctuating wind speeds for the buffeting analysis of long-span bridges. The fluctuating wind speeds, with part of their time histories measured at some points, are regarded as a zero-mean nonstationary Gaussian vector process characterized by an evolutionary power spectral density (EPSD) matrix. The Kriging method is then applied to the random vector of the Fourier coefficients of the evolutionary vector process for conditional simulation. A mathematical proof of this conditional simulation is provided. A fast algorithm of the conditional simulation is further derived, by converting the Cholesky decomposition of a large size covariance matrix of the Fourier coefficients into the Cholesky decomposition of a series of small-size coherence matrices with much less computational time. The procedure for implementing the fast algorithm-based conditional simulation method is detailed. Finally, this method is applied for the conditional simulation of typhoon-induced nonstationary wind speed time histories for the buffeting analysis of Stonecutters Bridge in Hong Kong. The time domain buffeting responses of the bridge obtained using the conditionally simulated wind speed time histories indicate that the proposed simulation method is feasible and applicable.
    publisherAmerican Society of Civil Engineers
    titleConditional Simulation of Nonstationary Fluctuating Wind Speeds for Long-Span Bridges
    typeJournal Paper
    journal volume140
    journal issue1
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/(ASCE)EM.1943-7889.0000589
    treeJournal of Engineering Mechanics:;2014:;Volume ( 140 ):;issue: 001
    contenttypeFulltext
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