Resilience of Urban Rail Transit Networks under Compound Natural and Opportunistic Failures

Critical infrastructure systems are increasingly at risk of failure due to extreme weather, exacerbated by climate change, and cyber-physical attack, due to reliance on digital information technology. When assessing the state of current infrastructure systems, and when planning new infrastructures, considerations of operational efficiency and resource constraints must be balanced with resilience. A resilient infrastructure design paradigm must account for low-probability, high-impact “grey swan” hazards, and resilience must be structurally embedded by design. This work extends the state-of-the-art in quantification of infrastructure resilience with compound natural-human hazard scenarios and focuses on urban rail transit networks as a proof-of-concept infrastructure system. With new and existing rail projects receiving funding opportunities, an imperative emerges to develop methodological frameworks which can address uncertainty and build resilience into design decisions in addition to operational efficiency. The contributions of this paper are threefold: (1) developing an analytical modeling framework for the simulation of compound failure and recovery in spatially-constrained rail transit networks leveraging system-level awareness; (2) characterizing the dynamics of an urban rail transit network by constructing resilience curves using the largest connected component of the network as a proxy measure for system functionality; and (3) leveraging network science and engineering principles to generate decision-support insights under uncertainty.