Keywords: building resilience, HAZUS, hurricanes, probabilistic resilience, natural disasters, critical infrastructures, critical infrastructure resilience, disaster risk, disaster mitigation strategies, decision making, resilience quantification, building types, hurricane winds, Monte Carlo analysis, residential buildings, damage simulation
Probabilistic resilience for building systems exposed to natural disasters
Resilience engineering requires understanding a system's capability to anticipate and absorb threats, take actions to reduce their adverse consequences, and develop response and recovery actions for the system to resume its normal operation quickly. A resilience quantification approach is very helpful in disaster risk research for comparing different mitigation strategies, selecting the most appropriate one, and providing better support in decision–making. Authors recently developed a resilience quantification methodology. This paper demonstrates the implementation of the methodology to different building types exposed to hurricane winds. Monte Carlo analyses were performed to compute resilience of various building types against Categories 1, 2, and 3 hurricanes. Resilience was evaluated, presented in a dashboard representation and compared for residential buildings that are identical except for one feature. Resilience was computed for three different mitigation actions. Resilience comparison was done to evaluate the effectiveness of these mitigation actions. A combined recovery function was also introduced.