<p>Seismic risk assessment is a probabilistic approach that evaluates the likelihood of earthquake occurrence, structural response, expected damage levels, economic losses, and potential casualties by incorporating the inherent uncertainties associated with seismic hazards and urban building characteristics. The primary objective of this study is to quantify and spatially characterize the distribution of damage states at the urban scale. Buildings were classified according to their structural system, age, and number of stories. The structures were initially modeled, analyzed, and designed in ETABS, and the beam and column section properties were extracted for each structural type. Finite element models were subsequently developed in OpenSees, and Incremental Dynamic Analysis, IDA, was performed to evaluate the seismic performance of building groups and large-scale seismic risk. The application of this approach to urban-scale seismic risk evaluation distinguishes this research from similar previous investigations. Given the considerable number of models, the extensive dataset, and the necessity for updating results under varying input conditions, a Bayesian Probabilistic Network was employed. In addition, GIS-based mapping was used to present the findings, including the exceedance probabilities of different damage states and the spatial distribution of collapse probability. The outcomes of this study identify areas that may exhibit relatively higher seismic vulnerability, emphasizing the potential need for targeted retrofitting strategies or, enhanced preparedness for post-earthquake emergency response and rescue operations.</p>

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A large-scale seismic risk assessment framework using enhanced FEMA P-58 and Bayesian network inference: a case study of District 2, Tehran

  • Reza Hajirostami,
  • Mehdi Banazadeh

摘要

Seismic risk assessment is a probabilistic approach that evaluates the likelihood of earthquake occurrence, structural response, expected damage levels, economic losses, and potential casualties by incorporating the inherent uncertainties associated with seismic hazards and urban building characteristics. The primary objective of this study is to quantify and spatially characterize the distribution of damage states at the urban scale. Buildings were classified according to their structural system, age, and number of stories. The structures were initially modeled, analyzed, and designed in ETABS, and the beam and column section properties were extracted for each structural type. Finite element models were subsequently developed in OpenSees, and Incremental Dynamic Analysis, IDA, was performed to evaluate the seismic performance of building groups and large-scale seismic risk. The application of this approach to urban-scale seismic risk evaluation distinguishes this research from similar previous investigations. Given the considerable number of models, the extensive dataset, and the necessity for updating results under varying input conditions, a Bayesian Probabilistic Network was employed. In addition, GIS-based mapping was used to present the findings, including the exceedance probabilities of different damage states and the spatial distribution of collapse probability. The outcomes of this study identify areas that may exhibit relatively higher seismic vulnerability, emphasizing the potential need for targeted retrofitting strategies or, enhanced preparedness for post-earthquake emergency response and rescue operations.