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As earthquakes continue to pose significant risks to the built environment, the concept of seismic resilience has gained attention as a means to evaluate how effectively buildings recover functionality after such disruptive events. This study aims to develop a quantitative assessment framework that evaluates the post-seismic resilience of buildings using Expected Annual Resilience (EAR). By introducing the Expected Annual Resilience as a core metric, the framework enables integrated evaluation of both the extent of functional loss and the capacity for recovery over time, based on seismic hazard probabilities. EAR is defined as a probabilistic metric that quantifies the expected level of building functionality maintained or recovered throughout a year, considering the annual probability and frequency of seismic events. It reflects both the extent of retained functionality and the capacity for recovery over time across various earthquake scenarios. To implement this concept, a quantitative assessment framework is developed by integrating seismic hazard models, post-seismic functionality curves, and recovery timelines. Applying the framework to school buildings is particularly significant, as schools are essential community infrastructure and are often used as shelters after earthquakes. A seismic hazard curve was developed based on more than 2,000 historical ground motion records observed across Korea. Using each school's fragility function and loss function, the retained functionality following seismic events was estimated, and corresponding EAR values were calculated. EAR were evaluated across three seismic hazard levels corresponding to different probability of exceedance scenarios, categorized as low, medium, and high hazard. The results indicate that buildings under moderate hazard conditions exhibited EAR values approximately 8.6% higher than those under slight hazard, and 4.1% higher than those under low hazard. These findings suggest that as seismic hazard levels increase, the expected annual resilience decreases, highlighting the metric’s sensitivity to varying hazard intensities. The proposed methodology may be helpful for many stakeholders and decision makers for pre- and post-earthquake assessments to quantify seismic performance.
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Chang et al. (2026) studied this question.
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