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Optimized seismic hazard and structural vulnerability model considering macroseismic intensity measures

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  • Li, Si-Qi
  • Gardoni, Paolo

Abstract

Macroseismic intensity measures are fundamental quantitative indicators for evaluating the vulnerability and resilience of regional building clusters. The vulnerability model of building portfolios established can provide a noteworthy reference for the development of large-scale regional earthquake risk distributions. However, there are differences in the quantitative scales of the macroseismic intensity standards used in multiple regions. The positive effects of instrument intensity and probabilistic seismic hazard theory on the vulnerability assessment of regional buildings are rarely considered, resulting in significant differences in their assessment results. This paper comprehensively considers the impact of instrument intensity and seismic hazard models on traditional macroseismic intensity. An updated macroseismic intensity measure (UCMS-20) is proposed for evaluating regional buildings, which is combined with the latest version of China's seismic intensity standards. The actual seismic damage sample dataset (31,649 buildings) of four types of building clusters in three typical earthquakes in China (Wenchuan 2008, Yushu 2010, and Jiuzhaigou 2017) has been expanded and updated. Using the UCMS-20, the European Macroseismic Scale (EMS-98), the Modified Mercalli intensity (MMI), and the Medvedev, Sponheuer, and Karnik Scale (MSK-64), vulnerability assessments are conducted on the extended empirical structural seismic damage dataset, and an empirical disaster matrix model considering updating damage states is established. A nonlinear vulnerability prediction model considering updated macrointensity measures is proposed, and the optimized model is validated and compared against the developed multiscale empirical structure dataset. The multiscale vulnerability index calculation model is improved, and novel optimization curves, point clouds, and matrix probability risk models are established, considering the expansion of empirical structural vulnerability databases.

Suggested Citation

  • Li, Si-Qi & Gardoni, Paolo, 2024. "Optimized seismic hazard and structural vulnerability model considering macroseismic intensity measures," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
  • Handle: RePEc:eee:reensy:v:252:y:2024:i:c:s0951832024005325
    DOI: 10.1016/j.ress.2024.110460
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    References listed on IDEAS

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    1. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2023. "Multi-unit seismic probabilistic risk assessment: A Bayesian network perspective," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    2. Li, Chao & Diao, Yucheng & Li, Hong-Nan & Pan, Haiyang & Ma, Ruisheng & Han, Qiang & Xing, Yihan, 2023. "Seismic performance assessment of a sea-crossing cable-stayed bridge system considering soil spatial variability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    3. Pei, Shunshun & Zhai, Changhai & Hu, Jie, 2024. "Surrogate model-assisted seismic resilience assessment of the interdependent transportation and healthcare system considering a two-stage recovery strategy," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    4. Maosheng Gong & Shibin Lin & Jingjiang Sun & Shanyou Li & Junwu Dai & Lili Xie, 2015. "Seismic intensity map and typical structural damage of 2010 Ms 7.1 Yushu earthquake in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 847-866, June.
    5. Xu, Yanwen & Kohtz, Sara & Boakye, Jessica & Gardoni, Paolo & Wang, Pingfeng, 2023. "Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    6. Vishwanath, B Sharanbaswa & Banerjee, Swagata, 2023. "Considering uncertainty in corrosion process to estimate life-cycle seismic vulnerability and risk of aging bridge piers," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    7. Du, Ao & Wang, Xiaowei & Xie, Yazhou & Dong, You, 2023. "Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs – An earthquake engineering perspective," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
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