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A network-based framework for assessing infrastructure resilience: a case study of the London metro system
Author(s) -
Shauhrat S. Chopra,
Trent Dillon,
Melissa M. Bilec,
Vikas Khanna
Publication year - 2016
Publication title -
journal of the royal society interface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.655
H-Index - 139
eISSN - 1742-5689
pISSN - 1742-5662
DOI - 10.1098/rsif.2016.0113
Subject(s) - resilience (materials science) , interdependence , critical infrastructure , computer science , complex network , network topology , flow network , heuristic , natural disaster , risk analysis (engineering) , computer security , transport engineering , business , engineering , computer network , geography , mathematical optimization , physics , mathematics , artificial intelligence , world wide web , political science , meteorology , law , thermodynamics
Modern society is increasingly dependent on the stability of a complex system of interdependent infrastructure sectors. It is imperative to build resilience of large-scale infrastructures like metro systems for addressing the threat of natural disasters and man-made attacks in urban areas. Analysis is needed to ensure that these systems are capable of withstanding and containing unexpected perturbations, and develop heuristic strategies for guiding the design of more resilient networks in the future. We present a comprehensive, multi-pronged framework that analyses information on network topology, spatial organization and passenger flow to understand the resilience of the London metro system. Topology of the London metro system is not fault tolerant in terms of maintaining connectivity at the periphery of the network since it does not exhibit small-world properties. The passenger strength distribution follows a power law, suggesting that while the London metro system is robust to random failures, it is vulnerable to disruptions on a few critical stations. The analysis further identifies particular sources of structural and functional vulnerabilities that need to be mitigated for improving the resilience of the London metro network. The insights from our framework provide useful strategies to build resilience for both existing and upcoming metro systems.

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