Topological Analytics for Vulnerability Enhancement and Recovery Strategy after Disruptions of Rail Networks in the United States

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Rail networks are real-life examples of complex networks and critical logistic and economic contributors to the wellbeing of society. Natural or human-caused hazards leading to the disruptions of rail network’s components can cause severe consequences including significant economic impacts. Therefore, analyzing rail networks and further reducing the impacts of potential disruptions are critical in order to manage risks to the performance of rail networks. Based on existing research on rail networks, this thesis proposes a methodology to analyze the rail networks with a large number of nodes, links, and complex connectivity from topological perspectives. Additionally, topology enhancement prior to failures and recovery strategies post to failures are used to reduce the impacts of potential failures based on vulnerability and resilience assessments. The analysis results of two case studies, the Amtrak and Class I rail networks, indicate that the proposed methodology is well suited to analyze and enhance the topology, vulnerability, and resilience of complex rail networks effectively and efficiently.