Development of a decision support system through modelling of critical infrastructure interdependencies : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Critical Infrastructure (CI) networks provide functional services to support the wellbeing of a community. Although it is possible to obtain detailed information about individual CI and their components, the interdependencies between different CI networks are often implicit, hidden or not well understood by experts. In the event of a hazard, failures of one or more CI networks and their components can disrupt the functionality and consequently affect the supply of services. Understanding the extent of disruption and quantification of the resulting consequences is important to assist various stakeholders' decision-making processes to complete their tasks successfully. A comprehensive review of the literature shows that a Decision Support System (DSS) integrated with appropriate modelling and simulation techniques is a useful tool for CI network providers and relevant emergency management personnel to understand the network recovery process of a region following a hazard event. However, the majority of existing DSSs focus on risk assessment or stakeholders' involvement without addressing the overall CI interdependency modelling process. Furthermore, these DSSs are primarily developed for data visualization or CI representation but not specifically to help decision-makers by providing them with a variety of customizable decision options that are practically viable. To address these limitations, a Knowledge-centred Decision Support System (KCDSS) has been developed in this study with the following aims: 1) To develop a computer-based DSS using efficient CI network recovery modelling algorithms, 2) To create a knowledge-base of various recovery options relevant to specific CI damage scenarios so that the decision-makers can test and verify several ‘what-if’ scenarios using a variety of control variables, and 3) To bridge the gap between hazard and socio-economic modelling tools through a multidisciplinary and integrated natural hazard impact assessment. Driven by the design science research strategy, this study proposes an integrated impact assessment framework using an iterative design process as its first research outcome. This framework has been developed as a conceptual artefact using a topology network-based approach by adopting the shortest path tree method. The second research outcome, a computer-based KCDSS, provides a convenient and efficient platform for enhanced decision making through a knowledge-base consisting of real-life recovery strategies. These strategies have been identified from the respective decision-makers of the CI network providers through the Critical Decision Method (CDM), a Cognitive Task Analysis (CTA) method for requirement elicitation. The capabilities of the KCDSS are demonstrated through electricity, potable water, and road networks in the Wellington region of Aotearoa New Zealand. The network performance has been analysed independently and with interdependencies to generate outage of services spatially and temporally. The outcomes of this study provide a range of theoretical and practical contributions. Firstly, the topology network-based analysis of CI interdependencies will allow a group of users to build different models, make and test assumptions, and try out different damage scenarios for CI network components. Secondly, the step-by-step process of knowledge elicitation, knowledge representation and knowledge modelling of CI network recovery tasks will provide a guideline for improved interactions between researchers and decision-makers in this field. Thirdly, the KCDSS can be used to test the variations in outage and restoration time estimates of CI networks due to the potential uncertainty related to the damage modelling of CI network components. The outcomes of this study also have significant practical implications by utilizing the KCDSS as an interface to integrate and add additional capabilities to the hazard and socio-economic modelling tools. Finally, the variety of ‘what-if’ scenarios embedded in the KCDSS would allow the CI network providers to identify vulnerabilities in their networks and to examine various post-disaster recovery options for CI reinstatement projects

Vulnérabilité, interdépendance et analyse des risques des postes sources et des modes d’exploitation décentralisés des réseaux électriques

In view of the increasing use of Information and Communication Technol-ogies in power systems, it is essential to study the interdependencies between these coupled heterogeneous systems. This thesis focuses on the modeling of multi- infrastructure systems. This includes interdependencies and the three major failures families: common mode, escalat-ing and cascading. It is indeed necessary to identify the weaknesses that can trigger one or multiple failure(s) and cascade through these interdependent infrastructures, causing unex-pected and increasingly more serious failures to other infrastructures. In this context, different approaches, based on the theory of Complex Networks, are developed to identify the most critical components in the coupled heterogeneous system. One of the major scientific barriers addressed in this thesis is the development of a unified mathematical model to represent the behavior.Au vu de l’utilisation croissante des technologies de l’information et de la communication dans les réseaux électriques, il est indispensable d’étudier l’étroite liaison entre ces infrastructures et d’avoir une vision intégrée du système couplé. Cette thèse porte ainsi sur la modélisation des systèmes multi-infrastructures. Cela inclut les interdépendances et les trajectoires de défaillances de type modes communs, aggravations et cascades. Il est en effet nécessaire d’identifier les points de faiblesse qui peuvent déclencher une ou de multiples défaillance(s), se succéder en cascade au travers de ces infrastructures liées et ainsi entrainer des défaillances inattendues et de plus en plus graves dans des autres infrastructures. Dans cette optique, différents modèles basés sur la théorie des Réseaux Complexes sont développés afin d’identifier les composants les plus importantes, et pourtant critiques, dans le système interconnecté. Un des principaux verrous scientifiques levé dans cette thèse est relatif au développement d'un modèle mathématique « unifié » afin de représenter les comportements des multiples infrastructures non-homogènes qui ont des interdépendances asymétriques

Résilience systémique d’un territoire composé d’activités essentielles suite à une perturbation majeure – Approches systémique et spatiale

Too many dramatic events occurred over the last ten years have demonstrated the severity and extent of impacts that territories may be confronted with. Damages to critical infrastructures may have a variety of downfall disturbing effects, which can lead territories and society into a huge crisis. Interdependency between these essential activities on the one hand, and between these activities and the population on the other hand, increases their vulnerability. This thesis presents a methodology to better assess direct and indirect impacts of a major disturbance. The issue is addressed from a multi-activity perspective, to take into account territories complexity.In the first stage, a territory is modeled using existing interdependency links between essential activities and the population. The methodology then identifies, based on a defined initial event, possible propagation scenarios and their consequences on services “users”. Finally, this simulation gives an assessment of the territory stakes resilience. This works provides a decision-making tool for the development of activity continuity plans, or risk assessment and mitigation policies.De trop nombreux évènements survenus la décennie passée illustrent la gravité et l’étendue des impacts auxquels les territoires peuvent être confrontés. L'atteinte aux infrastructures critiques peut induire de très nombreux dysfonctionnements en cascade pouvant plonger ce territoire et sa société dans une crise de grande ampleur. Les interdépendances entre ces activités essentielles et celles avec la population accentuent leur fragilité. Afin d'évaluer les impacts directs et indirects d'une perturbation majeure, la méthodologie développée étudie la problématique sous un angle multisectoriel répondant ainsi à une prise en compte de la complexité des territoires. Dans un premier temps, le territoire via ses activités essentielles et sa population est modélisé en s'appuyant sur les liens d'interdépendance existants. Sur la base d'un évènement initial donné, la méthode identifie les scénarios de propagation possibles et leurs conséquences sur les "usagers" concernés par la délivrance des services touchés. Cette simulation permet ainsi d'apprécier la résilience systémique des enjeux du territoire. Basé sur une approche systémique et spatiale, ce travail a pour objectif de fournir une aide à la décision à la planification des mesures de continuité et de rétablissement d'activité ou à la mise en place de mesures de traitement des risques

Simulation of Heterogeneous and Interdependent Critical Infrastructures

In this paper, a simulation tool specifically designed for the analysis of heterogeneous and (inter)dependent infrastructures is proposed. The simulator, named Critical Infrastructure Simulation by Interdependent Agents (CISIA), adopts a modular and sufficiently abstract representation of the different infrastructures components to allow consistent descriptions, starting from the incomplete and generic data acquirable from stakeholders. An important part of the modelling effort was reserved for the representation of the dependencies and interdependencies, these being the cause of the complex behaviours we are interested in. Each component interacts with the others via a multitude of mechanisms that codify different concepts of proximity. The simulator has been used to analyse, in a simplified scenario, crisis evolution in the urban area of Rome, in the presence of a failure in the electric power system