Seismic resilience assessment of buildings: A simplified methodological approach through conventional seismic risk assessment

Abstract

A simplified methodology to evaluate seismic resilience of buildings through a probabilistic risk assessment is proposed. The methodology uses the results from the conventional seismic risk assessment with the inclusion of social and economic aspects. The seismic resilience assessment process considers the workforce population, repair time, direct and indirect losses. They can be applied within the damage definition stage with the aim of the vulnerability functions for a specific building typology, and loss estimation stage of the probabilistic risk assessment. For the case of the definition of vulnerability functions a previous methodological approach is used with fewer modifications. In addition, a new risk figure called average annual repair time is introduced in the probabilistic risk assessment allowing to obtain the resilience index. Aspects such as expected repair time, quantities of crew members, business interruption losses, workforce population capacity and risk figures: average annual loss, probable maximum loss and average annual repair time are considered. Then, all those aspects are integrated within the exposure, damage, and loss estimation models with additional considerations to perform the calculation of the resilience. Finally, the results are represented by means of a unitless simplified resilience index allowing to be compared among different scenarios. The methodology is illustrated using two study cases. The first one represented its application at damage definition stage and is comprised by 3-, 6- and 9-story reinforced concrete moment resisting frame school buildings designed for special seismic code level. The second one covered the application at loss estimation stage and considers a fictitious portfolio of approximately 190,000 buildings composed by the previous three building typologies located along the whole country of Peru. The results show a highly sensitivity associated to workforce population, repair time, and indirect losses. Conclusions and possible applications related to Disaster Risk Reduction are summarized.