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Author:

Gao, X. (Gao, X..) | Li, J. (Li, J..) | Qiu, C. (Qiu, C..) | Hou, H. (Hou, H..) | Chen, C. (Chen, C..)

Indexed by:

EI Scopus SCIE

Abstract:

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 SMA-based SC-CBF but its influence is less significant than that caused by ground motion uncertainty for the braced frame investigated in this study. © 2023 Institution of Structural Engineers

Keyword:

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

Author Community:

  • [ 1 ] [Gao X.]Department of Architecture, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
  • [ 2 ] [Li J.]School of Civil Engineering, Shandong University, Shandong, Jinan, China
  • [ 3 ] [Qiu C.]Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, Beijing, 100124, China
  • [ 4 ] [Hou H.]School of Civil Engineering, Shandong University, Shandong, Jinan, China
  • [ 5 ] [Chen C.]School of Engineering, San Francisco State University, San Francisco, CA, United States

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Source :

Structures

ISSN: 2352-0124

Year: 2023

Volume: 56

4 . 1 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 7

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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