Resilience of Civil Infrastructure by Optimal Risk Mitigation

This paper puts forward a framework for optimal mitigation of regional risk to enhance the resilience of civil infrastructure. To meet this objective, probabilistic models, methods, and software are developed and applied. The work is conducted within a new reliability-based approach, in which reliability methods compute risk. This contrasts several contemporary approaches for risk analysis. Risk, in this context, denotes the probability of exceeding monetary loss. Evaluating such probabilities requires probabilistic models for hazards, response, damage, and loss. This motivates the following contributions in this paper. First, a new computer program is developed that is tailored to conduct reliability analysis with many interconnected probabilistic models. It orchestrates the interaction of models through an object-oriented architecture. Second, a library of probabilistic models for regional seismic risk analysis are developed. The library includes new models for earthquake location and magnitude and building response, damage, and loss. Third, probabilistic methods for multi-hazard risk analysis are developed and applied in a large-scale regional analysis. The results are cost exceedance probabilities and insights into the seismic risk of the region. Finally, sensitivity measures are developed to identify the buildings whose retrofit yields the most reduction in regional risk, i.e., the most resilience of the region.