Thesis Type: Post Graduate
Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Civil Engineering, Turkey
Approval Date: 2011
Student: ELİF MÜGE ÜN
Co-Consultant: AYŞEGÜL ASKAN GÜNDOĞAN, MURAT ALTUĞ ERBERİKAbstract:
Future seismic losses including the physical, economic and social ones as well as casualties concern a wide range of authorities varying from geophysical and earthquake engineers, physical and economic planners to insurance companies. As its many components involve inherent uncertainties, a probabilistic approach is required to estimate seismic losses. This study aims to propose a probabilistic method for estimating seismic losses, and to predict the potential seismic loss for the residential buildings for a selected district in Bursa, which is a highly industrialized city in Northwestern Turkey. To verify the methodology against a past large event, loss estimations are initially performed for a district in Düzce, and the method is calibrated with loss data from the 12 November 1999 Düzce Earthquake. The main components of the proposed loss model are seismic hazard, building vulnerability functions and loss as a function of damage states of buildings. To quantify the regional hazard, a probabilistic seismic hazard assessment approach is adopted. For different types of building structures, probability of exceeding predefined damage states for a given hazard level is determined using appropriate fragility curve sets. The casualty model for a given damage level considers the occupancy type, population of the building, occupancy at the time of earthquake occurrence, number of trapped occupants in the collapse, injury distribution at collapse and mortality post collapse. Economic loss is calculated by multiplying mean damage ratio with the total cost of initial construction. The proposed loss model combines these input components within a conditional probability approach. The results are expressed in terms of expected loss and losses caused by events with different return periods.