  This study examines the failure and recovery, two key components of
resilience of nine major urban rail networks - Washington DC, Boston, Chicago,
Delhi, Tokyo, Paris, Shanghai, London, and New York - against multi-hazard
scenarios utilizing a quantitative approach focused on topological parameters
to evaluate network resilience. Employing percolation-based network dismantling
approach like Sequential Removal of Nodes and Giant Connected Component
analysis, alongside random, centrality-based targeted attacks and flooding
failure, findings reveal Domirank centrality's superior resilience in
disruption and recovery phases. Kendall's tau coefficient's application further
elucidates the relationships between network properties and resilience,
underscoring larger networks' vulnerability yet faster recovery due to inherent
redundancy and connectivity. Key attributes like average degree and path length
consistently influence recovery effectiveness, while the clustering
coefficient's positive correlation with recovery highlights the benefits of
local interconnectivity. This analysis emphasizes the critical role of select
nodes and the importance of balancing network design for enhanced resilience,
offering insights for future urban rail system planning against multi-hazard
threats.
