Risk and resilience assessment of complex infrastructure networks – a system-of-systems approach to rail networks
Keywords: System-of-systems
Risk
Complex networks
Interdependencies
Critical infrastructure systems
Resilience
Rail networks

The railway is an important critical national infrastructure network in many western countries and by its nature is exposed to diverse threats ranging from extreme weather and climate change risks, man-made and malevolent activities. The complex nature of the interdependencies across the respective systems that make up a typical rail network can result in the propagation of network failures with serious consequences for the movement of trains, passengers, goods and services. Recent disruption events have shown how rapid and widescale the impact of failures can be on complex interdependent rail networks, and with the projection of increased risk from extreme weather and climate change events, there is a need for robust methodologies that can address this growing complexity with applicability to real-world networks.
The aim of this thesis is therefore to develop models and methodologies for analysing the risk and resilience of large scale interdependent rail infrastructure networks. It introduces multi-scale, system-of-systems based methodologies and applied analysis that provides important new insights into interdependent infrastructure network risk and resilience at national scale using real-world case studies. The thesis comprises three parts. First, a theoretical network-based model of the multi-track layout is built to replicate the actual operational functionality of the rail network which is tested using a real-world national timetable dataset for Great Britain. This model is calibrated using an empirical dataset of journey disruptions to arrive at a robust journey disruption network model. Next, by adopting a complex network-based modelling approach, real-world asset data is integrated from the respective systems of the national rail network in Great Britain to represent the physical interconnectivity that exists within and between its interdependent infrastructure systems. The coupling of both models give rise to an integrated infrastructure network model which is used to simulate scenarios of risk to the traction power network and resilience modelling. Lastly, the impact of extreme weather risks is studied with the development of a flood risk methodology which is tested by carrying out a comprehensive risk assessment of the national rail network in Great Britain. The criticality of individual assets is calculated by summing the direct impacts, with the indirect impacts measured in terms of train and passenger disruptions.
The development of robust methodologies and research models that represent the actual physical, geographic and functional interdependencies across rail networks using real-world asset datasets allows for the testing of multiple scenarios of risk and resilience which can be used to support robust decision making in complex networks. This research therefore presents new theoretical insights and practical methodologies with direct applicability to academia, infrastructure managers, policy and decision makers across Great Britain and beyond.