Probabilistic Resilience-Guided Infrastructure Risk Management

Abstract

The increased frequency and magnitude of natural and anthropogenic hazard events that affected infrastructure systems over the past two decades have highlighted the need for more effective risk management strategies. Such strategies are expected to not only manage the immediate disruption to system’s functionality following hazard realization, but to also mitigate the latter’s extended-term consequences (e.g., recovery cost and restoration time), which would otherwise be disastrous. To yield realistic managerial insights, such resilience-guided risk management necessitates accounting for the different sources of uncertainties associated with both the hazard quantification and the response of the infrastructure being considered. Through considering such uncertainties, the probabilistic resilience quantification framework developed in this study is expected to provide valuable managerial insights to guide resource allocations for both pre- and posthazard realization. The applicability of the framework is demonstrated on a simplified system subjected to different anthropogenic hazard scenarios. Beyond the presented case study, the developed framework lays the foundation for adopting probabilistic resilience quantification to guide the next-generation risk management processes of infrastructure systems under different forms of natural and anthropogenic hazards.