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Probabilistic seismic risk assessment framework: case study Adapazari, Turkey

Autor(en):
ORCID


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Bulletin of Earthquake Engineering, , n. 7, v. 21
Seite(n): 3133-3162
DOI: 10.1007/s10518-023-01674-2
Abstrakt:

While earthquakes can have a devastating impact on the economic growth and social welfare of earthquake prone regions, probabilistic seismic risk assessment can be employed to assess and mitigate such risks from future destructive events. In a previous study (Sianko et al. in Bull Earthq Eng 18:2523–2555, 2020), a probabilistic seismic hazard analysis (PSHA) tool based on the Monte-Carlo approach, was developed to predict the seismic hazard for high seismicity areas. In this study, a seismic risk assessment framework is developed incorporating the previously developed PSHA tool, with vulnerability functions based on various damage criteria, exposures and casualty models. Epistemic uncertainty is addressed using logic trees and distribution functions. The developed seismic risk assessment framework can estimate human and economic losses for particular return periods using an event-based stochastic procedure. The framework is applied to a case study area, the city of Adapazari in Turkey. Seismic risk assessment is carried out for different return periods to identify the most vulnerable areas of the city. The verification of the developed seismic risk framework is performed by comparing the predicted seismic losses to those observed during the 1999 Kocaeli earthquake that severely affected the city of Adapazari. The results of the study indicate that while overall predictions for extensive and complete damage states demonstrate strong correlation with the observed data, accurate risk predictions at the district level are not achievable without microzonation studies.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1007/s10518-023-01674-2.
  • Über diese
    Datenseite
  • Reference-ID
    10725507
  • Veröffentlicht am:
    30.05.2023
  • Geändert am:
    30.05.2023
 
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