Several resilience agencies (e.g. SPUR) had published “current” and “target” resilience performance of key urban infrastructure after an earthquake. The resilience performance explicitly considers the two dimensions of the recovery process: functionality and time after the earthquake. Previous regional risk estimation techniques built initial robust methodologies for assessing expected values of earthquake consequences. However, currently, there is no systematic methodology for probabilistic quantification of regional resilience performance objectives that integrates new advances in earthquake engineering (e.g., spatially correlated ground motion modeling) and network analysis, which enables the modeling of key urban system dependencies.
This research proposes a framework that uses a probabilistic approach to measure “current” resilience performance and assesses the likelihood of reaching community scale Resilience Performance Objectives (RPO). The framework utilizes and draws inspiration from the modular approach of Performance Based Earthquake Engineering (PBEE) and explicitly incorporates network analysis of interdependent urban systems. This work provides a way to unify current resilience, risk and network research, with a goal of helping decision makers measure resilience performance.