A framework for the probabilistic quantification of the resilience of communities to hurricane winds

Enhancing community resilience against hurricanes, one of the costliest natural hazards to impact the United States over the past four decades, is an essential requirement for the nation's security and welfare. A fundamental step in this direction is to provide computational frameworks that are able to quantify the response of the community to the hazard immediately after its impact and during its recovery process. Existing frameworks focus on estimating damage and losses immediately subsequent to the hurricane impact through vulnerability models. This paper provides a framework that integrates damage estimated from vulnerability models with a probabilistic recovery model for quantifying community resilience against hurricanes. The framework is based on five resilience limit states that identify the required recovery activities for each building based on the amount of damage. A building-level recovery model, based on discrete functionality states, translates these limit states to a building-level recovery function. By aggregating building recovery functions, a community recovery function and resilience measure are obtained. The framework is embedded in a Monte Carlo simulation strategy for uncertainty propagation therefore enabling a fully probabilistic quantification of community resilience. The framework is illustrated with a case study consisting of a typical residential neighborhood in Miami, FL.