Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems

Critical infrastructure systems must be both robust and resilient in order to ensure the functioning of society. To improve the performance of such systems, we often use risk and vulnerability analysis to find and address system weaknesses. A critical component of such analyses is the ability to accurately determine the negative consequences of various types of failures in the system. Numerous mathematical and simulation models exist which can be used to this end. However, there are relatively few studies comparing the implications of using different modeling approaches in the context of comprehensive risk analysis of critical infrastructures. Thus in this paper, we suggest a classification of these models, which span from simple topologically-oriented models to advanced physical flow-based models. Here, we focus on electric power systems and present a study aimed at understanding the tradeoffs between simplicity and fidelity in models used in the context of risk analysis. Specifically, the purpose of this paper is to compare performances measures achieved with a spectrum of approaches typically used for risk and vulnerability analysis of electric power systems and evaluate if more simplified topological measures can be combined using statistical methods to be used as a surrogate for physical flow models. The results of our work provide guidance as to appropriate models or combination of models to use when analyzing large-scale critical infrastructure systems, where simulation times quickly become insurmountable when using more advanced models, severely limiting the extent of analyses that can be performed

Critical materials for infrastructure: local vs global properties

Introducing new technologies into infrastructure (wind turbines, electric vehicles, low-carbon materials and so on) often demands materials that are ‘critical’; their supply is likely to be disrupted owing to limited reserves, geopolitical instability, environmental issues and/or increasing demand. Non-critical materials may become critical if introduced into infrastructure, owing to its gigatonne scale. This potentially poses significant risk to the development of low-carbon infrastructure. Analysis of this risk has previously overlooked the relationship between the ‘local properties’ that determine the selection of a technology and the overall vulnerability of the system, a global property. Treating materials or components as elements having fixed properties overlooks optima within the local–global variable space that could be exploited to minimise vulnerability while maximising performance. In this study, a framework for such analysis is presented along with a preliminary measure of relative materials criticality by way of a case study (a wind turbine generator). Although introduction of critical materials (in this case, rare earth metals) enhances technical performance by up to an order of magnitude, the associated increase in criticality may be two or three orders of magnitude. Analysis at the materials and component levels produces different results; design decisions should be based on analysis at several levels

Physical, Economical, Infrastructural and Social Flood Risk -- Vulnerability Analyses in GIS

An exhaustive knowledge of flood risk, vulnerability and exposure in different spatial locations is essential for developing an effective flood mitigation strategy for a watershed. In the present study, a flood risk-vulnerability analysis is performed. All four components of flood vulnerability: (a) physical; (b) economic; (c) infrastructure and (d) social, are evaluated individually using a Geographic Information System (GIS) environment. The proposed methodology estimates the impact on infrastructure vulnerability due to inundation of critical facilities, emergency service stations, and road bridges. The components of vulnerability are combined to determine the overall vulnerability. The patterns of land use and soil type are considered as two major components of flood exposure. Flood hazard maps, overall vulnerability and exposure are used to finally compute the flood risk at different locations in the watershed. The proposed methodology is implemented to six major damage centers in the Upper Thames River watershed, located in south-western Ontario of Canada to assess the flood risk. A web-based information system is developed for systematic presentation of the flood risk, vulnerability and exposures by postal code regions or Forward Sortation Areas (FSAs). The system is designed to provide support for different users, i.e., general public, decision-makers and water management professionals. An interactive analysis tool is developed within the web-based information system to assist in evaluation of the flood risk in response to a change in land use pattern.https://ir.lib.uwo.ca/wrrr/1019/thumbnail.jp

Vulnerability of the Critical Infrastructure in the Healthcare

Import 18/04/2016Import 02/11/2016Disertační práce se zabývá problematikou kritické infrastruktury ve zdravotnictví a stanovení zranitelnosti jejích prvků. Na začátku práce je řešena problematika kritické infrastruktury, jejich oblastí a podoblastí v České republice, v rámci Evropské unie a NATO, i vybraných státech světa. Uvedeny jsou také přístupy k ochraně prvků kritické infrastruktury. Práce se zabývá také přístupy ke stanovení zranitelnosti prvku kritické infrastruktury, a to jak v České republice, tak ve vybraných zemích světa. Hlavní částí práce je zaměřena na zdravotnickou kritickou infrastrukturu v České republice z pohledu její připravenosti na mimořádné události a krizové situace. V disertační práci jsou navržena nová odvětvová kritéria pro nemocniční péči, která je jednou z podoblastí kritické infrastruktury, neboť současná odvětvová kritéria nesplňuje žádné zdravotnické zařízení. Na základě těchto navržených odvětvových kritérií jsou stanoveny prvky zdravotnické kritické infrastruktury. Jedna část práce se zabývá analýzami ohrožení a analýzami rizik mimořádných událostí, které ohrožují zdravotnickou kritickou infrastrukturu. Tyto analýzy ohrožení a rizik jsou využity pro stanovení obecného modelu pro stanovení zranitelnosti zdravotnické kritické infrastruktury. Tento obecný model byl aplikován při tvorbě Metodiky pro stanovení zranitelnosti prvku kritické infrastruktury ve zdravotnictví. Významnou část práce tvoří Metodika pro připravenost nemocnice na mimořádné události a krizové situace, která je určena především pro styčné bezpečnostní zaměstnance subjektu kritické infrastruktury. Součástí této metodiky je i Metodika pro stanovení zranitelnosti prvku kritické infrastruktury ve zdravotnictví a návrh typových scénářů pro snížení zranitelnosti zdravotnické kritické infrastruktury. Poslední kapitolu disertační práce tvoří aplikace Metodiky pro připravenost nemocnice na mimořádné události a krizové situace pro vybranou nemocnici.The dissertation deals with the problem of the critical infrastructure in health care and the assessment of the vulnerability of its assets. In the beginning of the thesis there is described critical infrastructure and its sectors in the Czech Republic, in the European Union, NATO and chosen states. The major part of the dissertation it is focused to critical infrastructure in the health care in the Czech Republic from the point of view of its preparedness for the emergencies and the crisis situation. There are design new sectoral criteria for the hospital care that is one of the health care parts. This was made because of no hospital complies current sectoral criteria. On the basis of these new criteria there are assessed the components of the critical infrastructure. The part of the thesis follows up threat analysis and risk analysis of the emergencies that threaten the asset of the critical infrastructure in the health care. Those threat and risk analysis they are used for the determination of the general model for the assessment of the vulnerability of the critical infrastructure in the health care. This general model was applied for the formation of Methodology for assessment of the vulnerability of component of the critical infrastructure in the health care. The important part of the thesis is created by the Methodology for hospital’s preparedness for the emergencies and the crisis situation. This methodology is intended for security liaison officers of the owner/operators of the critical infrastructure. Part of this methodology is made by the Methodology for assessment of the vulnerability of component of the critical infrastructure in the health care and the suggestion of the model scenario for reduction of the vulnerability of the critical infrastructure in the health care. The last chapter of the thesis there is the application of the Methodology for hospital’s preparedness for the emergencies and the crisis situation for the chosen hospital.Prezenční050 - Katedra ochrany obyvatelstvavyhově

Policy-relevant Assessment Method of Socio-Economic Impacts of Floods: an Italian Case Study

This paper estimates the direct and indirect socio-economic impacts of the 2000 flood that took place in the Po river basin (Italy) using a combination of Computable General Equilibrium (CGE) model and Spatial and Multi-Criteria Analysis. A risk map for the whole basin is generated as a function of hazard, exposure and vulnerability. The indirect economic losses are assessed using the CGE model, whereas the direct social and economic impacts are estimated with spatial analysis tools combined with Multi-Criteria Analysis. The social impact is expressed as a function of physical characteristics of the extreme event, social vulnerability and adaptive capacity. The results indicate that the highest risk areas are located in the mountainous and in the most populated portions of the basin, which are consistent with the high values of hazard and vulnerability. Considerably economic damages occurred to the critical infrastructure of all the sectors with the industry/commercial sector having the biggest impact. A negative variation in the country and industry Gross Domestic Product (GDP) was also reported. Our study is of great interest to those who are interested in estimating the economic impact of flood events. It can also assist decision makers in pinpointing factors that threaten the sustainability and stability of a risk-prone area and more specifically, to help them understand how to reduce social vulnerability to flood events

A network-based system for assessment and management of infrastructure interdependency

Critical infrastructures (CIs) provide services that are essential to both the economy and well-being of nations and their citizens. Over the years, CIs are becoming more complex and interconnected, they are all interdependent in various ways, including logically, functionally, and geographically. The interconnection between CIs results in a very complex and dynamic system which increases their vulnerability to failures. In fact, when an infrastructure is experiencing failures, it can rapidly generate a cascade or domino effect to impact the other infrastructures. Thus, identifying, understanding and modeling infrastructure interdependency is a new field of research that deals with interrelationships between critical infrastructure sectors for disaster management. In the present research project, an integrated network-based analysis system with a user-friendly graphic user interface (GUI) was developed for risk analysis of complex critical infrastructure systems and their component interdependencies, called FCEPN (Fragility Curve and Extended Petri Net analysis). This approach combines: 1) Fragility Curve analysis of the vulnerability of the infrastructure, based on predefined "damage states" due to particular "hazards"; 2) Extended Petri Net analysis of the infrastructure system interdependency to determine the possible failure states and risk values. Two types of Extended Petri Net, Stochastic Petri Net and Fuzzy Petri Net were discussed in this study respectively. The FCEPN system was evaluated using the Bluestone Dam in West Virginia and Huai River Watershed in China as the case studies. Evaluation study results suggested that the FCEPN system provides a useful approach for analyzing dam system design, potential and actual vulnerability of dam networks to flood related impact, performance and reliability of existing dam systems, and appropriate maintenance and inspection work

Spatial analysis and modelling of flood risk and climate adaptation capacity for assessing urban community and critical infrastructure interdependency

Flood hazards are the most common and destructive of all natural hazards in the world. A series of floods that hit the south east region of Queensland in Australia from December 2010 to January 2011 caused a massive devastation to the State, people, and its critical infrastructures. GIS-based risk mapping is considered a vital component in land use planning to reduce the adverse impacts of flooding. However, the integrated mapping of climate adaptation strategies, analysing interdependencies of critical infrastructures, and finding optimum decisions for natural disaster risk reduction in floodplain areas remain some of the challenging tasks. In this study, I examined the vulnerability of an urban community and its critical infrastructures to help alleviate these problem areas. The aim was to investigate the vulnerability and interdependency of urban community’s critical infrastructures using an integrated approach of flood risk and climate adaptation capacity assessments in conjunction with newly developed spatially-explicit analytical tools. As to the research area, I explored Brisbane City and identified the flood-affected critical infrastructures such as electricity, road and rail, sewerage, stormwater, water supply networks, and building properties. I developed a new spatially-explicit analytical approach to analyse the problem in four components: 1) transformation and standardisation of flood risk and climate adaptation capacity indicating variables using a) high resolution digital elevation modelling and urban morphological characterisation with 3D analysis, b) spatial analysis with fuzzy logic, c) geospatial autocorrelation, among others; 2) fuzzy gamma weighted overlay and topological cluster analyses using Bayesian joint conditional probability theory and self-organising neural network (SONN); 3) examination of critical infrastructure interdependency using utility network theory; and 4) analysis of optimum natural disaster risk reduction policies with Markov Decision Processes (MDP). The flood risk metrics and climate adaptation capacity metrics revealed a geographically inverse relationship (e.g. areas with very high flood risk index occupy a low climate adaptation capacity index). Interestingly, majority of the study area (93%) exhibited negative climate adaptation capacity metrics (-22.84 to < 0) which indicate that the resources (e.g. socio-economic) are not sufficient to increase the climate resiliency of the urban community and its critical infrastructures. I utilised these sets of information in the vulnerability assessment of critical infrastructures at single system level. The January 2011 flood instigated service disruptions on the following infrastructures: 1) electricity supplies along 627km (75%) and 212km (25%) transmission lines in two separate areas; 2) road and rail services along 170km (47%) and 2.5km (38%) networks, respectively; 3) potable water supply along 246km (56%) distribution lines; and 4) stormwater and sewerage services along 33km (91%) and 32km (78%) networks, respectively. From the critical infrastructure interdependency analysis, the failure of sewerage system due to the failure of electricity supply during the January 2011 flood exemplified the first order interdependency of critical infrastructures. The ripple effects of electricity failure down to road inaccessibility for emergency evacuation demonstrated the higher order interdependency. Moreover, an inverted pyramid structure demonstrated that the hierarchy of climate adaptation strategies of the infrastructures was graded from long-term measures (e.g. elimination) down to short-term measures (e.g. protection). The analysis with Markov Decision Processes (MDP) elucidated that the Australian Commonwealth government utilised the natural disaster risk reduction expenditure to focus on recovery while the State government focused on mitigation. There was a clear indication that the results of the MDP analysis for the State government established an agreement with the previous economic analysis (i.e. mitigation could reduce the cost of recovery by 50% by 2050 with benefit-cost ratio of 1.25). The newly developed spatially-explicit analytical technique, formulated in this thesis as the flood risk-adaptation capacity index-adaptation strategies (FRACIAS) linkage model, integrates the flood risk and climate adaptation capacity assessments for floodplain areas. Exacerbated by the absence of critical infrastructure interdependency assessment in various geographic analyses, this study enhanced the usual compartmentalised methods of assessing the flood risk and climate adaptation capacity of flood plain areas. Using the different drivers and factors that exposed an urban community and critical interdependent infrastructures to extreme climatic event, this work developed GIS-enabled systematic analysis which established the nexus between the descriptive and prescriptive modelling to climate risk assessment

Vulnerability assessment modelling for railway networks

Railway networks are prone to many different potential disruptive events such as technical failures (e.g. the failure of aging components), natural disasters (e.g. flooding) and intentional man-made disasters (e.g. trespass and suicide). Assessing the vulnerability of railway networks can help infrastructure managers to create the right preventive strategies to improve the robustness and the resilience of railway networks before the occurrence of disruptions. This study proposes a stochastic-vulnerability analysis model that enables the critical components of railway networks to be identified. The model is developed using a discrete event simulation technique. Its framework includes modules for assigning the disruption to the network components, predicting the network vulnerability, in terms of passenger delays and journey cancellations, and calculating the risk-based criticality of network components. Finally, an example application of the model is presented using a part of the East Midland railway network in UK

A Systematic Review of Smart City Infrastructure Threat Modelling Methodologies: A Bayesian Focused Review

Smart city infrastructure and the related theme of critical national infrastructure have attracted growing interest in recent years in academic literature, notably how cyber-security can be effectively applied within the environment, which involves using cyber-physical systems. These operate cross-domain and have massively improved functionality and complexity, especially in threat modelling cyber-security analysis—the disparity between current cyber-security proficiency and the requirements for an effective cyber-security systems implementation. Analysing risk across the entire analysed system can be associated with many different cyber security methods for overall cyber risk analysis or identifying vulnerability for individually modelled objects. One method for performing risk analysis proposed in the literature is by applying Bayesian-based threat modelling methodologies. This paper performs a systematic literature review of Bayesian networks and unique alternative methodologies for smart city infrastructure analysis and related critical national infrastructures. A comparative analysis of the different methodological approaches, considering the many intricacies, metrics, and methods behind them, with suggestions made for future research in the field of cyber-physical threat modelling for smart city infrastructure