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作者:

Gao, Xiaoshu (Gao, Xiaoshu.) | Li, Jinpeng (Li, Jinpeng.) | Qiu, Canxing (Qiu, Canxing.) | Hou, Hetao (Hou, Hetao.) | Chen, Cheng (Chen, Cheng.)

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EI Scopus SCIE

摘要:

Shape memory alloys (SMAs) combine super-elasticity and energy dissipation capacity therefore is favored in seismic hazard mitigation. Simplifications are necessary to incorporate acquired material properties through material testing for dynamic analysis. This study presents a methodology to integrate SMA material testing, model inference, and probabilistic seismic analysis for uncertainty quantification of SMA model uncertainty on SMA based structures. The proposed methodology is applied to a SMA-based self-centering concentrically braced frame (SC-CBF). The posterior distribution of SMA modeling parameters is first obtained through the MCMC algorithm. Considering computational cost of MCMC algorithm, linear moments method is introduced to sample SMA modeling parameters. Extensive time-history analysis is then performed to quantify the effect of SMA modelling uncertainty and ground motions on the performance of SC-CBF. Significant response changes can be observed in SC-CBF due to the effect of uncertainty, which inevitably affect the reliability assessment of the structure. These analysis results also show that modeling uncertainty will affect seismic performance of SMAbased SC-CBF but its influence is less significant than that caused by ground motion uncertainty for the braced frame investigated in this study.

关键词:

Monte Carlo method (MCMC) Shape memory alloys (SMAs) Markov Chain Self-centering concentrically braced frame (SC-CBF) Linear Moments (L-moments) Uncertainty analysis

作者机构:

  • [ 1 ] [Gao, Xiaoshu]Univ Tokyo, Dept Architecture, 7-3-1 Hongo,Bunkyo Ku, Tokyo 1138656, Japan
  • [ 2 ] [Li, Jinpeng]Shandong Univ, Sch Civil Engn, Jinan, Shandong, Peoples R China
  • [ 3 ] [Hou, Hetao]Shandong Univ, Sch Civil Engn, Jinan, Shandong, Peoples R China
  • [ 4 ] [Qiu, Canxing]Beijing Univ Technol, Key Lab Urban Secur & Disaster Engn, Minist Educ, Beijing 100124, Peoples R China
  • [ 5 ] [Chen, Cheng]San Francisco State Univ, Sch Engn, San Francisco, CA 94132 USA

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来源 :

STRUCTURES

ISSN: 2352-0124

年份: 2023

卷: 56

4 . 1 0 0

JCR@2022

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