Infrastructure network vulnerability

The work presented in this paper aims to propose a methodology of analyzing infrastructure network vulnerability in the field of prevention or reduction of the natural disaster consequences. After a state of the art on vulnerability models in the academic literature, the various vulnerability factors are classified and discussed. Eventually, a general model of vulnerability analysis including societal parameters is presented

Decision support for infrastructure network vulnerability assessment in natural disaster crisis situations

This thesis deals with infrastructure network vulnerability analysis in the natural disaster context. It starts from the observation that infrastructure such as water supply or power grid has significant influence on natural disasters’ indirect consequences. The aim is to model the vulnerability to take efficient actions. The scientific approach is divided into two complementary parts. The first one deals with the vulnerability assessment, while the second one focuses on the decision aiding process to be implemented for the assessed vulnerability reducing. The proper vulnerability analysis is based on the analysis objects modelling. In order to achieve this, we will adopt a graph theory representation. A literature review will allow us to identify the graph structure which best suits the context of the thesis. In a multi network analysis environment, interdependences, i.e. relationships between components of the same network or different networks - are a determining factor for any vulnerability model. We have thus proposed an approach to model interdependence compatible with the graph theory. There are two types of relationships: the one first is functional (dependence), while the second one is dysfunctional (influence). The vulnerability is assessed by a simulation-based approach. It is composed of one part relating to the system ability to resist the feared event; and the other part relative to its ability to be back on its nominal state after the disaster. When the vulnerability is determined, the next step will be to take the necessary decisions to manage it. This part on the decision aiding is itself divided into two sub parts: first of all the process to be used for the crisis management is established. Then a methodology for decision aiding is proposed and results on a Decision Support System development. In the age of the internet and social networks, it is possible to deploy the application on the internet

Decision Support System for Infrastructure Networks Vulnerability to Natural Disaster

This poster presents the mean contribution of the project VESTA (Vulnérabilité des rESeaux face aux caTastrophes nAturelles

Decision aid problems criteria for infrastructure networks vulnerability analysis (regular paper)

Natural disasters through infrastructure networks might aggravate or mitigate consequences to stakes. The objective of this paper is to characterize this kind of situation in order to provide a solid foundation for the decision aid. This characterization includes a description of the typology, actions and potential actions identification, determining preference systems, as well as a set of specific problems to each phase

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependency

Increased coupling between critical infrastructure networks, such as power and communication systems, will have important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several have studied interdependent network models and reported that increased coupling can increase system vulnerability. However, these results come from models that have substantially different mechanisms of cascading, relative to those found in actual power and communication networks. This paper reports on two sets of experiments that compare the network vulnerability implications resulting from simple topological models and models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid shows a much higher level of vulnerability, relative to the contagion model. Second, we compare a model of topological cascades in coupled networks to three different physics-based models of power grids coupled to communication networks. Again, the more accurate models suggest very different conclusions. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the coupled topological model, in which zero coupling is optimal. Finally, an extreme case in which communication failures immediately cause grid failures, suggests that if systems are poorly designed, increased coupling can be harmful. Together these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems

Aide à la décision pour l’analyse de la vulnérabilité des réseaux d’infrastructure face à une crise de catastrophe naturelle

Cette thèse traite de la Vulnérabilité des réseaux face aux catastrophes naturelles. Elle part du constat que les infrastructures telles que les réseaux d’eau, d’électricité influencent considérablement les conséquences indirectes des catastrophes naturelles. Elle vise donc à modéliser la vulnérabilité dans de telles situations pour une prise de décision efficace. La démarche scientifique est divisée en deux parties complémentaires. La première traite de la vulnérabilité des dits systèmes, tandis que la seconde se concentre sur le processus d’aide à la décision à mettre en œuvre en vue de réduire la vulnérabilité. L’analyse proprement dite de la vulnérabilité repose sur la modélisation des objets de l’analyse. Pour ce faire nous adopterons une représentation par la théorie des graphes. La revue de la littérature à ce niveau nous a permis d’identifier les structures de graphe les mieux adaptées au contexte de la thèse. Dans un environnement d’analyse multi réseau, les interdépendances, c’est-à-dire les liens entre les composants d’un même réseau ou de réseaux différents-sont un facteur déterminant pour tout modèle de vulnérabilité. Nous avons ainsi proposé un modèle compatible avec la théorie des graphes. Sont distingués deux types d’interdépendances. La première est fonctionnelle (dépendance), et la seconde est dysfonctionnelle (influence). La vulnérabilité quant à elle, est déterminée par une approche basée sur la simulation. Elle est composée d’une première partie relative à l’aptitude du système à résister à l’évènement redouté ; et d’une seconde partie relative à son aptitude à se recouvrer des conditions opérationnelles après la catastrophe. Le calcul de la vulnérabilité est un point d’entrée pour assister l’analyste dans sa prise de décision. La deuxième partie aborde ce thème. Elle est elle-même divisée en deux sous parties : La première traite du processus à mettre en œuvre pour la gestion de la crise ; la deuxième du Système Interactif d’Aide à la Décision réalisé. Une méthodologie d’aide à la décision et supportée par un outil informatique. À l’ère de l’internet et des réseaux sociaux, il est envisageable de déployer l’application sur internet. ABSTRACT : This thesis deals with infrastructure network vulnerability analysis in the natural disaster context. It starts from the observation that infrastructure such as water supply or power grid has significant influence on natural disasters’ indirect consequences. The aim is to model the vulnerability to take efficient actions. The scientific approach is divided into two complementary parts. The first one deals with the vulnerability assessment, while the second one focuses on the decision aiding process to be implemented for the assessed vulnerability reducing. The proper vulnerability analysis is based on the analysis objects modelling. In order to achieve this, we will adopt a graph theory representation. A literature review will allow us to identify the graph structure which best suits the context of the thesis. In a multi network analysis environment, interdependences, i.e. relationships between components of the same network or different networks - are a determining factor for any vulnerability model. We have thus proposed an approach to model interdependence compatible with the graph theory. There are two types of relationships: the one first is functional (dependence), while the second one is dysfunctional (influence). The vulnerability is assessed by a simulation-based approach. It is composed of one part relating to the system ability to resist the feared event; and the other part relative to its ability to be back on its nominal state after the disaster. When the vulnerability is determined, the next step will be to take the necessary decisions to manage it. This part on the decision aiding is itself divided into two sub parts: first of all the process to be used for the crisis management is established. Then a methodology for decision aiding is proposed and results on a Decision Support System development. In the age of the internet and social networks, it is possible to deploy the application on the internet

Decision aid problems criteria for infrastructure networks vulnerability analysis. Context of natural disasters.

Natural disasters through infrastructure networks might aggravate or mitigate consequences to stakes. The objective of this paper is to characterize this kind of situation in order to provide a solid foundation for the decision aid. Characterization consists in determining decision aid criteria. It includes typology description, actions and potential actions identification, determining preference systems, as well as a set of specific problems to each phase. Through decisions aggregation, some recommendations are given

Intégration de la sûreté de fonctionnement en phase de réponse à appel d’offres

Nous proposons dans ce travail une approche d’évaluation, en amont du cycle de développement d’un produit, de l’impact des exigences de sûreté de fonctionnement (SdF) sur la réalisation du projet associé. La nécessité d’allier les connaissances SdF et les connaissances « métiers » sur les dimensions fonctionnelles et structurelles du produit conduit à utiliser un formalisme de représentation matricielle. Nous présentons ce type de modèle et illustrons la démarche d’exploitation pour évaluer, tôt dans le projet, les effets de la dimension SdF du produit

Complex system representation for vulnerability analysis

Many socio-technical systems are endowed of dynamism, self-organization, emergency etc. These attributes make them as complex systems. Because of this complexity, the representation is a crucial step for vulnerability analysis. The objective of this paper is to provide a generic framework of complex systems representation for vulnerability analysis. We used infrastructure network such as power grid, gas and telecommunication system to illustrate our proposal. It is separated in five layers: Spatial framework, Stake, Flow, Environment, and Network structure. The static view consists of a network structure (Nodes and edges). The dynamic view is related to the flow circulation, components’ states variations, and interdependences among them. Characteristics of these factors are described. The environment refers to outside perturbations that could happen. With our proposal it is possible to model many classes of complex system as the basis of vulnerability analysis. For this purpose, some modelling rules are proposed. The result allows performing simulations. Results of the simulation can be used for instance to find out vulnerability model into complex systems, or to validate existing models

Methods for risk and resilience evaluation in interdependent infrastructure networks

Urban infrastructure plays a key role in the structure and dynamics of every city. Besides ensuring the sustainability of communities and businesses, high-quality infrastructure services are crucial for generating jobs and attracting capital investments. Modern infrastructure systems are highly interconnected to enhance efficiency and safety of operations; however, the interconnections increase the risks of cascading failures during extreme events, such as natural disasters, acts of terrorism, and pandemics. Not only are the normal operations interrupted during such events, but prolonged operational disruptions in infrastructure services also have debilitating effects on emergency response and economic recovery in affected regions. With the emergence of new threats and intensifying climate change, the resilience of infrastructure systems has become a necessity rather than a choice for our cities. As with any resource allocation problem, potential resilience investments require identifying priorities and evaluating project alternatives. Appropriate resilience indicators can be used to rank and prioritize infrastructure components and systems as well as to evaluate the efficacy of resilience interventions. The dissertation proposes five indicator-based methodological frameworks to assist decision-makers in analyzing the intrinsic risks and resilience in large-scale interdependent infrastructure networks. For generic interdependent networks, an agent-based simulation approach is adopted. In this approach, the interdependent network is modeled as a weighted bi-directed network where nodes represent infrastructure components and links denote the interconnections. For evaluating the risks of cascading failures and the network's resilience, a hybrid risk measure based on the well-known Inoperability Input-Output Model (IIM) using expert judgments is developed. In the process, to handle the issue of epistemic uncertainty associated with subjective infrastructure dependency data, a method based on possibility theory is also proposed. Later, the hybrid risk measure is extended to develop two resilience indexes for quantifying the criticality and susceptibility of infrastructure components and ranking algorithms are presented. In addition, the hybrid risk measure is combined with socio-economic characteristics obtained from census data to develop a priority index to quantify the risks of cascading failures in various urban communities. With regard to infrastructure-specific networks, the dissertation developed infrastructure ranking and prioritization methods for two distinct transportation systems, specifically road networks, and marine port systems, based on empirical disaster data. For characterizing the resilience of road networks, the dissertation proposed three indicators based on the concepts of resilience triangle and extreme travel time observations. The dissertation combined time series decomposition techniques with anomaly detection algorithms to segregate disaster effects from normal traffic patterns. For characterizing the risks of natural hazards to port systems, the dissertation employed disaster impact data along with international trade data and identified the ports with the highest risks.Civil, Architectural, and Environmental Engineerin