Assessing updated seismic performance of existing structures by stochastic model updating

authored by: M. Kitahara, S. Bi, M. Broggi, M. Beer
Abstract: Assessing seismic performance of existing structures after strong earthquake events is essential to identify potentially unsafe structures and to schedule repairs or retrofitting. For this purpose, a well calibrated model of the structure of interest should be established based on a very limited number of seismic response data, by considering not only epistemic uncertainty due to lack of knowledge on actual mechanical properties of the structure but also aleatory uncertainty due to the manufacturing process and aging deterioration. In this work, a Bayesian model updating framework is proposed, where uncertainty characteristics of model predictions and observed data, both described in time domain, are quantified by the Bhattacharyya distance-based metric. This framework is employed for calibrating the probability distribution of stiffness parameters of a seismic-isolated bridge pier model by only five observed data reflecting aging condition of the isolators. The calibrated model is then employed to perform a seismic reliability analysis and is revealed that the failure probability of the target structure is increased due to aging of the isolators compared with the health condition, demonstrating that the proposed model updating procedure enables to quantitatively assess the seismic performance of the aging isolated bridges.
Organisation(s): Institute for Risk and Reliability
External Organisation(s): Beijing Institute of Technology
University of Liverpool
Tongji University
Type: Conference contribution
Pages: 265-270
No. of pages: 6
Publication date: 2024
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: Management Science and Operations Research, Safety, Risk, Reliability and Quality
Electronic version(s): https://doi.org/10.3850/978-981-18-5184-1_MS-09-086-cd (Access: Closed)

BibTeX

@inproceedings{e0a61411c3c740a2ae35ee91111b2cf8,
title = "Assessing updated seismic performance of existing structures by stochastic model updating",
abstract = "Assessing seismic performance of existing structures after strong earthquake events is essential to identify potentially unsafe structures and to schedule repairs or retrofitting. For this purpose, a well calibrated model of the structure of interest should be established based on a very limited number of seismic response data, by considering not only epistemic uncertainty due to lack of knowledge on actual mechanical properties of the structure but also aleatory uncertainty due to the manufacturing process and aging deterioration. In this work, a Bayesian model updating framework is proposed, where uncertainty characteristics of model predictions and observed data, both described in time domain, are quantified by the Bhattacharyya distance-based metric. This framework is employed for calibrating the probability distribution of stiffness parameters of a seismic-isolated bridge pier model by only five observed data reflecting aging condition of the isolators. The calibrated model is then employed to perform a seismic reliability analysis and is revealed that the failure probability of the target structure is increased due to aging of the isolators compared with the health condition, demonstrating that the proposed model updating procedure enables to quantitatively assess the seismic performance of the aging isolated bridges.",
keywords = "Bhattacharyya distance, deterioration, seismic-isolated bridges, stochastic model updating, subset simulation",
author = "M. Kitahara and S. Bi and M. Broggi and M. Beer",
note = "Publisher Copyright: {\textcopyright} 2022 ISRERM Organizers. Published by Research Publishing, Singapore.; 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022 ; Conference date: 04-09-2022 Through 07-09-2022",
year = "2024",
doi = "10.3850/978-981-18-5184-1_MS-09-086-cd",
language = "English",
isbn = "9789811851841",
pages = "265--270",
editor = "Michael Beer and Enrico Zio and Kok-Kwang Phoon and Ayyub, {Bilal M.}",
booktitle = "Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022",
publisher = "Research Publishing Services, Singapore",
}