Please use this identifier to cite or link to this item: http://theses-test.ncl.ac.uk:8080/jspui/handle/10443.1/3753
Title: Robustness of hierarchical spatial critical infrastructure networks
Authors: Robson, Craig
Issue Date: 2017
Publisher: Newcastle University
Abstract: The economic state and wellbeing of a nation is dependent upon the critical infrastructure networks that deliver resources, goods and services. However, these are increasingly exposed to a number of hazards, both natural and man-made, which threaten to disrupt their ability to function. It is essential that in order to develop long-term strategic plans of infrastructure provision we are able to understand their current robustness to such hazards. The robustness of critical infrastructure networks has typically been investigated from a topological perspective as a means of simplifying the complexities associated with their analysis. Such work has led to many studies suggesting critical infrastructures exhibit a topological structure, from random to exponential degree distributions. However, often such analysis ignores the explicit spatial characteristics of the node and edge assets. Furthermore, the very nature of topological analysis means that flows/movements that take place over such networks cannot be considered. This work addresses these weaknesses by extending traditional topological analysis to consider emergent properties critical infrastructure networks exhibit when considering higher-order connectivity and flows. An analysis of a suite of synthetic networks with a spectrum of topologies alongside real infrastructure spatial networks, in terms of their basic topology and high-order connectivity, shows that a number of critical infrastructure networks seem to be better characterised as hierarchical networks. Subsequent failure modelling reveals that such hierarchical networks responded in a dramatically different manner to perturbations; complete failure occurring approximately 19 and 34 percent sooner for random and targeted failures compared to random networks. Such poor robustness is further exacerbated when flow simulation modelling over the resulting hierarchical networks is undertaken, revealing particular sensitivity to cascading failures from spatial hazards. In light of these results, it is suggested that it is essential to improve the robustness of critical infrastructure networks that exhibit a hierarchical spatial organisation.
Description: PhD Thesis
URI: http://hdl.handle.net/10443/3753
Appears in Collections:School of Civil Engineering and Geosciences

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