This PhD project will be delivered through the completion of five objectives and will answer six research questions:
1. Review existing network analysis / reliability / damage models that have been used to analyse infrastructure systems
Method: This objective focuses on a review of current literature to identify models used to analyse infrastructure systems, including physically-based models (modelling the flow of services in the systems) and hazard/damage models (simulating disaster scenarios). This objective will also review the literature regarding the more recent analysis of infrastructure systems using the application of network graph theory.
Output: A literature review detailing the traditional and new methods / models used to analyse infrastructure systems.
Research Questions:
i. What are the potential threats to the infrastructure systems?
ii. What classifies a network as resilient or vulnerable to a hazard scenario?
2. Collection of real world infrastructure data set(s), which will be catalogued into classes to enable their underlying properties to be described and synthetic analogies for these real world system(s) to be formed
Method: It has already been discussed that many real world networks potentially form specific network architectures (i.e. classes of network). Understanding the rules that result in these network classes facilitates the ability to generate synthetic networks that can be used as proxies for real world infrastructure systems. These artificial networks display all the characteristics of their real world counterparts and so can be used to generate results for a wider range of systems (e.g. different size systems, generic systems that there is no obtainable data for, future systems that do not yet exist, and whole infrastructure groups) compared to using data for a relatively small number of real world systems. These synthetic networks can also be used to determine if a hazard tolerance displayed by a real world network is unique to that system, or is characteristic of its network class. One suitable real world example will be identified and data regarding this system will be obtained and used as a basis for forming the synthetic networks. Data regarding the spatial location of components in the real world network will also be gathered and replicated in the synthetic networks.
For many infrastructure networks it is their ability to transfer service around the network that is considered to be important. Therefore, to enable the flow of service around infrastructure networks to be analysed, this objective will also employ a simple physically-based flow model to simulate the physical processes in infrastructure systems, which govern the flow of service around the systems.
Output: Generation of synthetic networks that can serve as proxies for real- world infrastructure systems, accounting for both the network architecture (class) of the system and its spatial locations and also the development of a flow model.
Research Questions:
iii. How does the inclusion of a spatial component affect the algorithm used to generate the synthetic networks, if at all?
3. Simulation of ‘disasters’ to the real and synthetic infrastructure systems (enabling the quantification of resilience)
Method: To quantify the inherent resilience of each class of network (and to identify fragile network architectures) to different types of disasters, hazard and damage models will be developed and applied to the real and synthetic infrastructure systems. The deterioration of the systems will be monitored using network theory measures and the resilience of the network quantified using these measures. To enable the identification of specific nodes and/or links that cause a disproportionate effect when removed from the system, the network models will be combined with the reduced complexity flow model (developed in Objective 2) and physically-based measures will be compared with measures from graph theory. The comparison between these two sets of measures should establish vulnerability markers (defined as nodes and/or links that when removed from the network have the greatest impact, e.g. those nodes whose removal causes the most disruption to the flow of service). Output: Quantification of the resilience of the synthetic and real infrastructure systems and the identification of fragile network architectures and specific vulnerable nodes and/or links in these systems.
Research Questions:
iv. Does the inclusion of a spatial component into the analysis alter the hazard tolerance of the network class, compared to using a purely topological model?
4. Evaluate methods to reduce the vulnerability of networks to disasters
Method: Quantifying the resilience of the real and synthetic infrastructure networks (Objective 3) will identify the inherent tolerance to hazard to each type of disaster considered (e.g. random hazard, spatial hazard and targeted attack). To identify the reasoning behind any vulnerability displayed by these networks, a range of synthetic networks with inherently robust network
architectures (to different hazards) and different spatial locations of components will be formed. These networks will be subjected to the same hazards and their resilience quantified using the same network measures as previously used. Comparison between this range of synthetic networks and those analysed in Objective 3 should explain the reason for any vulnerabilities shown. From these results methods to increase the resilience of the real world network will be formed and evaluated. Possible methods could include either permanently or adaptively ‘rewiring’ the network in the event of a hazard and solutions that change as little of the network structure as possible are preferred, as they are more likely to be economically viable.
Output: Identification of inherently robust classes and spatial configurations of systems and methods to modify inherently vulnerable real-world networks to increase their resilience.
Research Questions:
v. What is the best measure for identifying specific vulnerable nodes and/or links in a network?
vi. What is the best method at reducing any inherent vulnerability in a real world infrastructure system?
5. Recommendations to crisis managers and infrastructure planners
Method/Output: The findings of this project will be summarised and will aim to inform both crisis managers (how they can best cope with damaged infrastructure in the aftermath of a disaster) and infrastructure planners (showing the best methods to modify their systems so they are better prepared for disasters). The summary will detail which network classes are inherently resilient / vulnerable to different types of disasters. For those that are inherently vulnerable methods to increase their resilience will be indicated.