Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022 |
| Editors | Michael Beer, Enrico Zio, Kok-Kwang Phoon, Bilal M. Ayyub |
| Pages | 265-270 |
| Number of pages | 6 |
| Publication status | Published - 2024 |
| Event | 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022 - Hannover, Germany Duration: 4 Sept 2022 → 7 Sept 2022 |
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
ASJC Scopus subject areas
- Decision Sciences(all)
- Management Science and Operations Research
- Engineering(all)
- Safety, Risk, Reliability and Quality
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Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022. ed. / Michael Beer; Enrico Zio; Kok-Kwang Phoon; Bilal M. Ayyub. 2024. p. 265-270.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Assessing updated seismic performance of existing structures by stochastic model updating
AU - Kitahara, M.
AU - Bi, S.
AU - Broggi, M.
AU - Beer, M.
N1 - Publisher Copyright: © 2022 ISRERM Organizers. Published by Research Publishing, Singapore.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Bhattacharyya distance
KW - deterioration
KW - seismic-isolated bridges
KW - stochastic model updating
KW - subset simulation
UR - http://www.scopus.com/inward/record.url?scp=85202068668&partnerID=8YFLogxK
U2 - 10.3850/978-981-18-5184-1_MS-09-086-cd
DO - 10.3850/978-981-18-5184-1_MS-09-086-cd
M3 - Conference contribution
AN - SCOPUS:85202068668
SN - 9789811851841
SP - 265
EP - 270
BT - Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022
A2 - Beer, Michael
A2 - Zio, Enrico
A2 - Phoon, Kok-Kwang
A2 - Ayyub, Bilal M.
T2 - 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022
Y2 - 4 September 2022 through 7 September 2022
ER -