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With the help of numerous case studies and real-world examples, this must-read book explores the latest developments in the ongoing effort to use risk assessment as a means for characterizing knowledge and/or lack of knowledge about a system or process of interest. --

International audience ; In this work, we propose a multi-perspective framework of analysis of critical infrastructures (CIs) with respect to supply service, topology and controllability. The framework enables identifying the role of CI elements and quantifying the consequences of scenarios of multiple failures, with respect to the different perspectives considered. To present the analysis framework, a benchmark network representative of a real gas transmission network across several countries of the European Union (EU) is considered. The information extracted from such analysis can help us to identify the critical elements and how the properties of the network are affected by failures, and to propose corresponding improvements for CIs. The findings of this paper demonstrate the interest of considering several perspectives in the analysis of CIs for providing useful information for ensuring their safe and reliable operation.

International audience ; In this work, we propose a multi-perspective framework of analysis of critical infrastructures (CIs) with respect to supply service, topology and controllability. The framework enables identifying the role of CI elements and quantifying the consequences of scenarios of multiple failures, with respect to the different perspectives considered. To present the analysis framework, a benchmark network representative of a real gas transmission network across several countries of the European Union (EU) is considered. The information extracted from such analysis can help us to identify the critical elements and how the properties of the network are affected by failures, and to propose corresponding improvements for CIs. The findings of this paper demonstrate the interest of considering several perspectives in the analysis of CIs for providing useful information for ensuring their safe and reliable operation.

International audience ; In this work, we propose a multi-perspective framework of analysis of critical infrastructures (CIs) with respect to supply service, topology and controllability. The framework enables identifying the role of CI elements and quantifying the consequences of scenarios of multiple failures, with respect to the different perspectives considered. To present the analysis framework, a benchmark network representative of a real gas transmission network across several countries of the European Union (EU) is considered. The information extracted from such analysis can help us to identify the critical elements and how the properties of the network are affected by failures, and to propose corresponding improvements for CIs. The findings of this paper demonstrate the interest of considering several perspectives in the analysis of CIs for providing useful information for ensuring their safe and reliable operation.

This is a perspective article on foundational issues in risk assessment and management. The aim is to discuss the needs, obstacles, and challenges for the establishment of a renewed, strong scientific foundation for risk assessment and risk management suited for the current and future technological challenges. The focus is on (i) reviewing and discussing the present situation and (ii) identifying how to best proceed in the future, to develop the risk discipline in the directions needed. The article provides some reflections on the interpretation and understanding of the concept of "foundations of risk assessment and risk management" and the challenges therein. One main recommendation is that different arenas and moments for discussion are needed to specifically address foundational issues in a way that embraces the many disciplinary communities involved (from social scientists to engineers, from behavioral scientists to statisticians, from health physicists to lawyers, etc.). One such opportunity is sought in the constitution of a novel specialty group of the Society of Risk Analysis.

In general, two types of dependence need to be considered when estimating the probability of the top event (TE) of a fault tree (FT): "objective" dependence between the (random) occurrences of different basic events (BEs) in the FT and "state‐of‐knowledge" (epistemic) dependence between estimates of the epistemically uncertain probabilities of some BEs of the FT model. In this article, we study the effects on the TE probability of objective and epistemic dependences. The well‐known Frèchet bounds and the distribution envelope determination (DEnv) method are used to model all kinds of (possibly unknown) objective and epistemic dependences, respectively. For exemplification, the analyses are carried out on a FT with six BEs. Results show that both types of dependence significantly affect the TE probability; however, the effects of epistemic dependence are likely to be overwhelmed by those of objective dependence (if present).

In this work, specific indicators are used to characterize the criticality of components in a network system with respect to their contribution to failure cascade processes. A realistic‐size network is considered as reference case study. Three different models of cascading failures are analyzed, differing both on the failure load distribution logic and on the cascade triggering event. The criticality indicators are compared to classical measures of topological centrality to identify the one most characteristic of the cascade processes considered.

In risk analysis, the treatment of the epistemic uncertainty associated to the probability of occurrence of an event is fundamental. Traditionally, probabilistic distributions have been used to characterize the epistemic uncertainty due to imprecise knowledge of the parameters in risk models. On the other hand, it has been argued that in certain instances such uncertainty may be best accounted for by fuzzy or possibilistic distributions. This seems the case in particular for parameters for which the information available is scarce and of qualitative nature. In practice, it is to be expected that a risk model contains some parameters affected by uncertainties that may be best represented by probability distributions and some other parameters that may be more properly described in terms of fuzzy or possibilistic distributions. In this article, a hybrid method that jointly propagates probabilistic and possibilistic uncertainties is considered and compared with pure probabilistic and pure fuzzy methods for uncertainty propagation. The analyses are carried out on a case study concerning the uncertainties in the probabilities of occurrence of accident sequences in an event tree analysis of a nuclear power plant.