Bayesian Framework for Updating Seismic Loss Functions with Limited Observational Data in Low-to-Moderate Seismicity Regions

Insub Choi; Jun Hee Kim; Won Hee Kang; Youngsuk Kim

doi:10.1080/13632469.2021.1987356

Bayesian Framework for Updating Seismic Loss Functions with Limited Observational Data in Low-to-Moderate Seismicity Regions

Insub Choi, Jun Hee Kim, Won Hee Kang, Youngsuk Kim

Department of Architecture and Architectural Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In low-to-moderate seismicity regions, seismic loss functions (SLFs) are barely established due to limited observational data, making it difficult to derive decision-making on disaster prevention and management. Herein, a Bayesian framework is developed to update the SLFs with limited observational data. The proposed point-based Bayesian method updates local probability density function parameters for damage ratios at each seismic intensity, which helps to avoid an unrealistic underestimation of damage ratios in the low-to-moderate range of seismic intensities. The feasibility of the developed framework in a low-to-moderate seismicity region is verified by the comparison between the updated SLF and post-event data.

Original language	English
Pages (from-to)	8205-8228
Number of pages	24
Journal	Journal of Earthquake Engineering
Volume	26
Issue number	16
DOIs	https://doi.org/10.1080/13632469.2021.1987356
Publication status	Published - 2022

Bibliographical note

Funding Information:
This research was supported by a grant (NRF-2021R1A2C2007064) from the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Science and ICT (MSIT) and by the Yonsei University Research Fund (Post Doc. Researcher Supporting Program) of 2020 (2020-12-0144). This research was supported by a grant (NRF-2021R1A2C2007064) from the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Science and ICT (MSIT) and by the Yonsei University Research Fund (Post Doc. Researcher Supporting Program) of 2020 (2020-12-0144).

Funding Information:
This research was supported by a grant (NRF-2021R1A2C2007064) from the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Science and ICT (MSIT) and by the Yonsei University Research Fund (Post Doc. Researcher Supporting Program) of 2020 (2020-12-0144).

Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.

All Science Journal Classification (ASJC) codes

Civil and Structural Engineering
Building and Construction
Geotechnical Engineering and Engineering Geology

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10.1080/13632469.2021.1987356

Cite this

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title = "Bayesian Framework for Updating Seismic Loss Functions with Limited Observational Data in Low-to-Moderate Seismicity Regions",

abstract = "In low-to-moderate seismicity regions, seismic loss functions (SLFs) are barely established due to limited observational data, making it difficult to derive decision-making on disaster prevention and management. Herein, a Bayesian framework is developed to update the SLFs with limited observational data. The proposed point-based Bayesian method updates local probability density function parameters for damage ratios at each seismic intensity, which helps to avoid an unrealistic underestimation of damage ratios in the low-to-moderate range of seismic intensities. The feasibility of the developed framework in a low-to-moderate seismicity region is verified by the comparison between the updated SLF and post-event data.",

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note = "Funding Information: This research was supported by a grant (NRF-2021R1A2C2007064) from the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Science and ICT (MSIT) and by the Yonsei University Research Fund (Post Doc. Researcher Supporting Program) of 2020 (2020-12-0144). This research was supported by a grant (NRF-2021R1A2C2007064) from the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Science and ICT (MSIT) and by the Yonsei University Research Fund (Post Doc. Researcher Supporting Program) of 2020 (2020-12-0144). Funding Information: This research was supported by a grant (NRF-2021R1A2C2007064) from the National Research Foundation of Korea (NRF) funded by the Korean Ministry of Science and ICT (MSIT) and by the Yonsei University Research Fund (Post Doc. Researcher Supporting Program) of 2020 (2020-12-0144). Publisher Copyright: {\textcopyright} 2021 Taylor & Francis Group, LLC.",

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Bayesian Framework for Updating Seismic Loss Functions with Limited Observational Data in Low-to-Moderate Seismicity Regions

Abstract

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