Topological Determinants of Resilience in Urban Rail Networks Facing Multi-Hazard Disruptions

TL;DR

This paper analyzes the resilience of nine major urban rail networks against multi-hazard disruptions using topological parameters, revealing key network attributes that influence failure and recovery processes.

Contribution

It introduces a quantitative topological approach to evaluate urban rail network resilience, highlighting the roles of specific network metrics and node importance in failure and recovery.

Findings

Domirank centrality outperforms other measures in resilience assessment

Larger networks are more vulnerable but recover faster due to redundancy

Average degree and path length significantly impact recovery effectiveness

Abstract

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.