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    Stochastic Mainshock–Aftershock Simulation and Its Applications in Dynamic Reliability of Structural Systems via DPIM

    Source: Journal of Engineering Mechanics:;2023:;Volume ( 149 ):;issue: 001::page 04022096-1
    Author:
    Rui Pang
    ,
    Yang Zhou
    ,
    Guohai Chen
    ,
    Mingyuan Jing
    ,
    Dixiong Yang
    DOI: 10.1061/(ASCE)EM.1943-7889.0002176
    Publisher: American Society of Civil Engineers
    Abstract: A novel approach for nonlinear stochastic dynamic analysis is proposed and illustrated with nonlinear building structures subjected to mainshock–aftershock sequences. First, a stochastic seismic sequence model with stochastic parameters was established, and its generation method was derived based on the source–path–site mechanism. Then, the representative point sets of seismic parameters could be chosen based on generalized F-discrepancy, and the correlation between the mainshock and aftershock parameters could be determined by using Copula theory. Finally, the stochastic dynamic response was obtained by solving the probability density integral equation (PDIE). Furthermore, the first-passage dynamic reliability could be obtained by the direct probability integral method (DPIM) combined with the absorbing condition approach. This novel approach was used to obtain stochastic dynamic results for four structures subjected to stochastic seismic sequences, which were compared to those using Monte Carlo simulation (MCS) and probability density evolution method (PDEM) to demonstrate the proposed method’s correctness and efficiency. Additionally, the influence of aftershocks on nonlinear structures is explained from the perspective of probability for the first time.
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      Stochastic Mainshock–Aftershock Simulation and Its Applications in Dynamic Reliability of Structural Systems via DPIM

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4292656
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    • Journal of Engineering Mechanics

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    contributor authorRui Pang
    contributor authorYang Zhou
    contributor authorGuohai Chen
    contributor authorMingyuan Jing
    contributor authorDixiong Yang
    date accessioned2023-08-16T19:02:11Z
    date available2023-08-16T19:02:11Z
    date issued2023/01/01
    identifier other(ASCE)EM.1943-7889.0002176.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292656
    description abstractA novel approach for nonlinear stochastic dynamic analysis is proposed and illustrated with nonlinear building structures subjected to mainshock–aftershock sequences. First, a stochastic seismic sequence model with stochastic parameters was established, and its generation method was derived based on the source–path–site mechanism. Then, the representative point sets of seismic parameters could be chosen based on generalized F-discrepancy, and the correlation between the mainshock and aftershock parameters could be determined by using Copula theory. Finally, the stochastic dynamic response was obtained by solving the probability density integral equation (PDIE). Furthermore, the first-passage dynamic reliability could be obtained by the direct probability integral method (DPIM) combined with the absorbing condition approach. This novel approach was used to obtain stochastic dynamic results for four structures subjected to stochastic seismic sequences, which were compared to those using Monte Carlo simulation (MCS) and probability density evolution method (PDEM) to demonstrate the proposed method’s correctness and efficiency. Additionally, the influence of aftershocks on nonlinear structures is explained from the perspective of probability for the first time.
    publisherAmerican Society of Civil Engineers
    titleStochastic Mainshock–Aftershock Simulation and Its Applications in Dynamic Reliability of Structural Systems via DPIM
    typeJournal Article
    journal volume149
    journal issue1
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/(ASCE)EM.1943-7889.0002176
    journal fristpage04022096-1
    journal lastpage04022096-25
    page25
    treeJournal of Engineering Mechanics:;2023:;Volume ( 149 ):;issue: 001
    contenttypeFulltext
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