Seismic damage assessment based on regional synthetic ground motion dataset: a case study for Erzincan, Turkey

2018-07-01
Estimation of seismic losses is a fundamental step in risk mitigation in urban regions. Structural damage patterns depend on the regional seismic properties and the local building vulnerability. In this study, a framework for seismic damage estimation is proposed where the local building fragilities are modeled based on a set of simulated ground motions in the region of interest. For this purpose, first, ground motion records are simulated for a set of scenario events using stochastic finite-fault methodology. Then, existing building stock is classified into specific building types represented with equivalent single-degree-of-freedom models. The response statistics of these models are evaluated through nonlinear time history analysis with the simulated ground motions. Fragility curves for the classified structural types are derived and discussed. The study area is Erzincan (Turkey), which is located on a pull-apart basin underlain by soft sediments in the conjunction of three active faults as right-lateral North Anatolian Fault, left-lateral North East Anatolian Fault, and left-lateral Ovacik Fault. Erzincan city center experienced devastating earthquakes in the past including the December 27, 1939 (Ms = 8.0) and the March 13, 1992 (Mw = 6.6) events. The application of the proposed method is performed to estimate the spatial distribution of the damage after the 1992 event. The estimated results are compared against the corresponding observed damage levels yielding a reasonable match in between. After the validation exercise, a potential scenario event of Mw = 7.0 is simulated in the study region. The corresponding damage distribution indicates a significant risk within the urban area.

Citation Formats
S. Karim Zadeh Naghshineh, A. Askan Gündoğan, M. A. Erberik, and A. Yakut, “Seismic damage assessment based on regional synthetic ground motion dataset: a case study for Erzincan, Turkey,” NATURAL HAZARDS, vol. 92, pp. 1371–1397, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39751.