Probabilistic resilience quantification and visualization building performance to hurricane wind speeds

PROBABILISTIC RESILIENCE QUANTIFICATION AND VISUALIZATION BUILDING PERFORMANCE TO HURRICANE WIND SPEEDS Berna Eren Tokgoz Old Dominion University, 2012 Director: Dr. Adrian V. Gheorghe Natural and manmade disasters are unpredictable and unavoidable in today's world. Their frequency of occurrence and damages keep increasing. Due to the efforts to reduce negative consequences from such disasters, the concept of resilience has gained so much popularity in disaster management area especially after disasters like the September 11 attacks and Hurricane Katrina. Complex systems of today are under operational risks because of increasing threats and their high level of vulnerability. Hence, such systems need to adapt the concept of resilience for continuous operations. Resilience is a proactive concept which should incorporate both pre-event (preparedness and mitigation) and post-event (response and recovery) activities. As a new concept, resilience engineering is really about monitoring threats to a system and taking necessary actions to reduce the probability of failure of the system. Particularly, quantitative approaches for measuring resilience need to be developed to compare different mitigation strategies, to come up with the most appropriate one, and to provide better support and decision making. In order to achieve this goal, a methodology for quantification of resilience of different building types against different categories of hurricane is proposed. The formulation presented in this dissertation for resilience quantification is based on several parameters such as structural loss ratios and conditional probabilities of exceedance for damage states, estimated and actual recovery times, and wind speed probability. The proposed formulation is applicable to a community consisting of buildings with different types besides being applicable to individual building types. Numerical results for Monte Carlo and sensitivity analyses for resilience of various building types against Category 1,2 and 3 hurricanes are presented. A dashboard representation consisting of green, yellow and red zones is defined, and histograms are presented to demonstrate into which zone the resilience of each building type falls. Resilience of different building types is compared based on the numerical results. In addition, sensitivities of the resilience of various building types to different parameters are evaluated. Moreover, resilience values are computed before and after various mitigation actions are taken. These resilience values are compared to assess the effectiveness of the mitigation actions. The proposed formulation can be used to determine resilience values and compare resilience of different building types or communities against a specific hurricane category.

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