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Multivariable probabilistic seismic demand models for parametric fragility prediction of isolated bridges portfolios under pulse-like GMs

•A multivariable probabilistic seismic demand model (MV-PSDM) for friction isolation bearings is developed.•The impact of different parameters on the seismic demand, sensitivity and vulnerable range can be studied from MV-PSDM.•An efficient parametric fragility prediction method of friction isolatio...

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Published in:Engineering structures 2023-10, Vol.292, p.116517, Article 116517
Main Authors: Zhong, Jian, Zhu, Yuntao, Zheng, Xianglin, Han, Qiang
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Language:English
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creator Zhong, Jian
Zhu, Yuntao
Zheng, Xianglin
Han, Qiang
description •A multivariable probabilistic seismic demand model (MV-PSDM) for friction isolation bearings is developed.•The impact of different parameters on the seismic demand, sensitivity and vulnerable range can be studied from MV-PSDM.•An efficient parametric fragility prediction method of friction isolation bearing is proposed based on the MV-PSDM. The wide application of friction isolation bearings has led to a rapid increase in the number of frictional isolated bridges. Therefore, the traditional method of seismic fragility analysis based on nonlinear time-history analysis (NLTHA) may not suitable for bridge portfolios. For this purpose, this study developed a multivariable probabilistic seismic demand model (MV-PSDM) for friction isolation bearings conditioned on the earthquake parameters (peak pulse velocity, pulse period), bearing parameters (effective radius) and pier parameters (bending stiffness, pier numbers, pier height), in which a novel formula is adopted to calculate the seismic demand and the dispersion is also estimated. This MV-PSDM can be applied to investigate the influence of various parameters (earthquake parameters, friction bearing parameters, pier parameters) on the seismic demand, sensitivity and the vulnerable range of the bearing. Finally, an efficient parametric fragility prediction method for friction isolation bearing is proposed based on the MV-PSDM, and the flow chart is also provided. In this method, only earthquake parameters, bearing parameters and pier parameters are required to obtain the seismic fragility of friction isolation bearings, which avoids the FE modeling and NLTHA.
doi_str_mv 10.1016/j.engstruct.2023.116517
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The wide application of friction isolation bearings has led to a rapid increase in the number of frictional isolated bridges. Therefore, the traditional method of seismic fragility analysis based on nonlinear time-history analysis (NLTHA) may not suitable for bridge portfolios. For this purpose, this study developed a multivariable probabilistic seismic demand model (MV-PSDM) for friction isolation bearings conditioned on the earthquake parameters (peak pulse velocity, pulse period), bearing parameters (effective radius) and pier parameters (bending stiffness, pier numbers, pier height), in which a novel formula is adopted to calculate the seismic demand and the dispersion is also estimated. This MV-PSDM can be applied to investigate the influence of various parameters (earthquake parameters, friction bearing parameters, pier parameters) on the seismic demand, sensitivity and the vulnerable range of the bearing. Finally, an efficient parametric fragility prediction method for friction isolation bearing is proposed based on the MV-PSDM, and the flow chart is also provided. 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The wide application of friction isolation bearings has led to a rapid increase in the number of frictional isolated bridges. Therefore, the traditional method of seismic fragility analysis based on nonlinear time-history analysis (NLTHA) may not suitable for bridge portfolios. For this purpose, this study developed a multivariable probabilistic seismic demand model (MV-PSDM) for friction isolation bearings conditioned on the earthquake parameters (peak pulse velocity, pulse period), bearing parameters (effective radius) and pier parameters (bending stiffness, pier numbers, pier height), in which a novel formula is adopted to calculate the seismic demand and the dispersion is also estimated. This MV-PSDM can be applied to investigate the influence of various parameters (earthquake parameters, friction bearing parameters, pier parameters) on the seismic demand, sensitivity and the vulnerable range of the bearing. Finally, an efficient parametric fragility prediction method for friction isolation bearing is proposed based on the MV-PSDM, and the flow chart is also provided. 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The wide application of friction isolation bearings has led to a rapid increase in the number of frictional isolated bridges. Therefore, the traditional method of seismic fragility analysis based on nonlinear time-history analysis (NLTHA) may not suitable for bridge portfolios. For this purpose, this study developed a multivariable probabilistic seismic demand model (MV-PSDM) for friction isolation bearings conditioned on the earthquake parameters (peak pulse velocity, pulse period), bearing parameters (effective radius) and pier parameters (bending stiffness, pier numbers, pier height), in which a novel formula is adopted to calculate the seismic demand and the dispersion is also estimated. This MV-PSDM can be applied to investigate the influence of various parameters (earthquake parameters, friction bearing parameters, pier parameters) on the seismic demand, sensitivity and the vulnerable range of the bearing. Finally, an efficient parametric fragility prediction method for friction isolation bearing is proposed based on the MV-PSDM, and the flow chart is also provided. In this method, only earthquake parameters, bearing parameters and pier parameters are required to obtain the seismic fragility of friction isolation bearings, which avoids the FE modeling and NLTHA.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.engstruct.2023.116517</doi><orcidid>https://orcid.org/0000-0002-5998-250X</orcidid></addata></record>
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subjects Friction isolation bearing
Multivariable PSDM
Parametric fragility analysis
Pulse-like GMs
Structural and pulse parameters
title Multivariable probabilistic seismic demand models for parametric fragility prediction of isolated bridges portfolios under pulse-like GMs
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