Simulation and Criticality Assessment of Urban Rail and Interdependent Infrastructure Networks

Abstract

The role of urban infrastructure is becoming increasingly interdependent, resulting in new sources of vulnerability. Infrastructural asset failure can propagate between rail transportation and other infrastructure networks. There remains a lack of academic research focusing on the dynamic simulation of city-wide infrastructure using real-life data to quantify and cross-compare the criticality of assets. This paper aims to bridge this gap by developing a modeling methodology for interdependent urban infrastructure using complex network theory, which serves as a basis for investigating asset criticality and failure propagation. This modeling framework comprises the distribution of resource supply and demand, the topological representation and skeletonization of the infrastructure network, as well as modeling the propagation of asset failures. The framework is thereafter applied to a case study of Greater London's rail transportation exposure to failures from electricity infrastructure, selected as a representative example of interdependent infrastructure within a large-scale urban metropolitan area. Two time-based criticality metrics are also proposed to measure the topological extent of infrastructural failures and economic impacts resulting from the failure propagation of given initial failure scenarios. The results of the case study demonstrate that these proposed criticality metrics are effective in capturing the dynamics of failure propagation, and that topological metrics in criticality assessment do not always reflect the resulting economic damages of infrastructural failures.