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Probabilistic earthquake risk consideration of existing precast industrial buildings through loss curves

  • Ali Yesilyurt (Disaster Management Institute, Istanbul Technical University) ;
  • Seyhan O. Akcan (Department of Civil Engineering, Bogazici University) ;
  • Oguzhan Cetindemir (Department of Civil Engineering, Gebze Technical University) ;
  • A. Can Zulfikar (Disaster Management Institute, Istanbul Technical University)
  • 투고 : 2023.09.15
  • 심사 : 2024.05.27
  • 발행 : 2024.06.25

초록

In this study, the earthquake risk assessment of single-story RC precast buildings in Turkey was carried out using loss curves. In this regard, Kocaeli, a seismically active city in the Marmara region, and this building class, which is preferred intensively, were considered. Quality and period parameters were defined based on structural and geometric properties. Depending on these parameters, nine main sub-classes were defined to represent the building stock in the region. First, considering the mean fragility curves and four different central damage ratio models, vulnerability curves for each sub-class were computed as a function of spectral acceleration. Then, probabilistic seismic hazard analyses were performed for stiff and soft soil conditions for different earthquake probabilities of exceedance in 50 years. In the last step, 90 loss curves were derived based on vulnerability and hazard results. Within the scope of the study, the comparative parametric evaluations for three different earthquake intensity levels showed that the structural damage ratio values for nine sub-classes changed significantly. In addition, the quality parameter was found to be more effective on a structure's damage state than the period parameter. It is evident that since loss curves allow direct loss ratio calculation for any hazard level without needing seismic hazard and damage analysis, they are considered essential tools in rapid earthquake risk estimation and mitigation initiatives.

키워드

과제정보

The research described in this paper was financially supported by the Scientific Research Projects Department of Istanbul Technical University under Project No. MAB-2023-44591.

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