A full-probabilistic cloud analysis for structural seismic fragility via decoupled M-PDEM

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Autoren

Externe Organisationen

  • Tongji University
  • Southeast University (SEU)
  • Hohai University
  • The University of Liverpool
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OriginalspracheEnglisch
Seiten (von - bis)1863-1881
Seitenumfang19
FachzeitschriftEarthquake Engineering and Structural Dynamics
Jahrgang53
Ausgabenummer5
PublikationsstatusVeröffentlicht - 14 März 2024

Abstract

Performance-based earthquake engineering (PBEE) is essential for ensuring engineering safety. Conducting seismic fragility analysis within this framework is imperative. Existing methods for seismic fragility analysis often rely heavily on double loop reanalysis and empirical data fitting, leading to challenges in obtaining high-precision results with a limited number of representative structural analysis instances. In this context, a new methodology for seismic fragility based on a full-probabilistic cloud analysis is proposed via the decoupled multi-probability density evolution method (M-PDEM). In the proposed method, the assumption of a log-normal distribution is not required. According to the random event description of the principle of preservation of probability, the transient probability density functions (PDFs) of intensity measure (IM) and engineering demand parameter (EDP), as key response quantities of the seismic-structural system, are governed by one-dimensional Li-Chen equations, where the physics-driven forces are determined by representative analysis data of the stochastic dynamic system. By generating ground motions based on representative points of basic random variables and performing structural dynamic analysis, the decoupled M-PDEM is employed to solve the one-dimensional Li-Chen equations. This yields the joint PDF of IM and EDP, as well as the conditional PDF of EDP given IM, resulting in seismic fragility analysis outcomes. The numerical implementation procedure is elaborated in detail, and validation is performed using a six-story nonlinear reinforced concrete (RC) frame subjected to non-stationary stochastic ground motions. Comparative analysis against Monte Carlo simulation (MCS) and traditional cloud analysis based on least squares regression (LSR) reveals that the proposed method achieves higher computational precision at comparable structural analysis costs. By directly solving the physics-driven Li-Chen equations, the method provides the full-probabilistic joint information of IM and EDP required for cloud analysis, surpassing the accuracy achieved by traditional methods based on statistical moment fitting and empirical distribution assumptions.

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A full-probabilistic cloud analysis for structural seismic fragility via decoupled M-PDEM. / Lyu, Meng Ze; Feng, De Cheng; Cao, Xu Yang et al.
in: Earthquake Engineering and Structural Dynamics, Jahrgang 53, Nr. 5, 14.03.2024, S. 1863-1881.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Lyu, Meng Ze ; Feng, De Cheng ; Cao, Xu Yang et al. / A full-probabilistic cloud analysis for structural seismic fragility via decoupled M-PDEM. in: Earthquake Engineering and Structural Dynamics. 2024 ; Jahrgang 53, Nr. 5. S. 1863-1881.
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title = "A full-probabilistic cloud analysis for structural seismic fragility via decoupled M-PDEM",
abstract = "Performance-based earthquake engineering (PBEE) is essential for ensuring engineering safety. Conducting seismic fragility analysis within this framework is imperative. Existing methods for seismic fragility analysis often rely heavily on double loop reanalysis and empirical data fitting, leading to challenges in obtaining high-precision results with a limited number of representative structural analysis instances. In this context, a new methodology for seismic fragility based on a full-probabilistic cloud analysis is proposed via the decoupled multi-probability density evolution method (M-PDEM). In the proposed method, the assumption of a log-normal distribution is not required. According to the random event description of the principle of preservation of probability, the transient probability density functions (PDFs) of intensity measure (IM) and engineering demand parameter (EDP), as key response quantities of the seismic-structural system, are governed by one-dimensional Li-Chen equations, where the physics-driven forces are determined by representative analysis data of the stochastic dynamic system. By generating ground motions based on representative points of basic random variables and performing structural dynamic analysis, the decoupled M-PDEM is employed to solve the one-dimensional Li-Chen equations. This yields the joint PDF of IM and EDP, as well as the conditional PDF of EDP given IM, resulting in seismic fragility analysis outcomes. The numerical implementation procedure is elaborated in detail, and validation is performed using a six-story nonlinear reinforced concrete (RC) frame subjected to non-stationary stochastic ground motions. Comparative analysis against Monte Carlo simulation (MCS) and traditional cloud analysis based on least squares regression (LSR) reveals that the proposed method achieves higher computational precision at comparable structural analysis costs. By directly solving the physics-driven Li-Chen equations, the method provides the full-probabilistic joint information of IM and EDP required for cloud analysis, surpassing the accuracy achieved by traditional methods based on statistical moment fitting and empirical distribution assumptions.",
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note = "Funding Information: Financial supports from the Project of National Key Research and Development Program of China (Grant No. 2022YFC3803004), the National Natural Science Foundation of China (Grant No. 12302037), China Postdoctoral Science Foundation (Grant No. 2023M732669), Shanghai Post‐Doctoral Excellence Program (Grant No. 2022558), and the Natural Science Foundation of Jiangsu Province (Grant No. BK20220984) are highly appreciated. Prof. Jian‐Bing Chen from Tongji University is gratefully appreciated for his constructive comments and encouragement. ",
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Download

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AU - Lyu, Meng Ze

AU - Feng, De Cheng

AU - Cao, Xu Yang

AU - Beer, Michael

N1 - Funding Information: Financial supports from the Project of National Key Research and Development Program of China (Grant No. 2022YFC3803004), the National Natural Science Foundation of China (Grant No. 12302037), China Postdoctoral Science Foundation (Grant No. 2023M732669), Shanghai Post‐Doctoral Excellence Program (Grant No. 2022558), and the Natural Science Foundation of Jiangsu Province (Grant No. BK20220984) are highly appreciated. Prof. Jian‐Bing Chen from Tongji University is gratefully appreciated for his constructive comments and encouragement.

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Y1 - 2024/3/14

N2 - Performance-based earthquake engineering (PBEE) is essential for ensuring engineering safety. Conducting seismic fragility analysis within this framework is imperative. Existing methods for seismic fragility analysis often rely heavily on double loop reanalysis and empirical data fitting, leading to challenges in obtaining high-precision results with a limited number of representative structural analysis instances. In this context, a new methodology for seismic fragility based on a full-probabilistic cloud analysis is proposed via the decoupled multi-probability density evolution method (M-PDEM). In the proposed method, the assumption of a log-normal distribution is not required. According to the random event description of the principle of preservation of probability, the transient probability density functions (PDFs) of intensity measure (IM) and engineering demand parameter (EDP), as key response quantities of the seismic-structural system, are governed by one-dimensional Li-Chen equations, where the physics-driven forces are determined by representative analysis data of the stochastic dynamic system. By generating ground motions based on representative points of basic random variables and performing structural dynamic analysis, the decoupled M-PDEM is employed to solve the one-dimensional Li-Chen equations. This yields the joint PDF of IM and EDP, as well as the conditional PDF of EDP given IM, resulting in seismic fragility analysis outcomes. The numerical implementation procedure is elaborated in detail, and validation is performed using a six-story nonlinear reinforced concrete (RC) frame subjected to non-stationary stochastic ground motions. Comparative analysis against Monte Carlo simulation (MCS) and traditional cloud analysis based on least squares regression (LSR) reveals that the proposed method achieves higher computational precision at comparable structural analysis costs. By directly solving the physics-driven Li-Chen equations, the method provides the full-probabilistic joint information of IM and EDP required for cloud analysis, surpassing the accuracy achieved by traditional methods based on statistical moment fitting and empirical distribution assumptions.

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