Elisa Ferrario

A framework for the system-of-systems analysis of the risk for a safety-critical plant exposed to external events

We consider a critical plant exposed to risk from external events. We propose an original framework of analysis, which extends the boundaries of the study to the interdependent infrastructures which support the plant. For the purpose of clearly illustrating the conceptual framework of system-of-systems analysis, we work out a case study of seismic risk for a nuclear power plant embedded in the connected power and water distribution, and transportation networks which support its operation. The technical details of the systems considered (including the nuclear power plant) are highly simplified, in order to preserve the purpose of illustrating the conceptual, methodological framework of analysis. Yet, as an example of the approaches that can be used to perform the analysis within the proposed framework, we consider the Muir Web as system analysis tool to build the system-of-systems model and Monte Carlo simulation for the quantitative evaluation of the model. The numerical exercise, albeit performed on a simplified case study, serves the purpose of showing the opportunity of accounting for the contribution of the interdependent infrastructure systems to the safety of a critical plant. This is relevant as it can lead to considerations with respect to the decision making related to safety critical-issues.

Evaluation of the robustness of critical infrastructures by Hierarchical Graph representation, clustering and Monte Carlo simulation

In this paper, we present a methodological work that adopts a system-of-systems (SoS) viewpoint for the evaluation of the robustness of interdependent critical infrastructures (CIs). We propose a Hierarchical Graph representation, where the product flow is dispatched to the demand nodes in consideration of different priorities. We use a multi-state model to describe different degrees of degradation of the individual components, where the transitions between the different states of degradation occur stochastically. The quantitative evaluation of the CIs robustness is performed by Monte Carlo simulation. The methodological approach proposed is illustrated by way of two case studies: the first one concerns small-sized gas and electricity networks and a supervisory control and data acquisition (SCADA) system; the second one considers a moderately large power distribution network, adapted from the IEEE 123 node test feeders. The large size of the second case study requires hierarchical clustering for performing the robustness analysis.

Assessing nuclear power plant safety and recovery from earthquakes using a system-of-systems approach

Abstract We adopt a ‘system-of-systems’ framework of analysis, previously presented by the authors, to include the interdependent infrastructures which support a critical plant in the study of its safety with respect to the occurrence of an earthquake. We extend the framework to consider the recovery of the system of systems in which the plant is embedded. As a test system, we consider the impacts produced on a nuclear power plant (the critical plant) embedded in the connected power and water distribution, and transportation networks which support its operation. The Seismic Probabilistic Risk Assessment of such system of systems is carried out by Hierarchical modeling and Monte Carlo simulation. First, we perform a top-down analysis through a hierarchical model to identify the elements that at each level have most influence in restoring safety, adopting the criticality importance measure as a quantitative indicator. Then, we evaluate by Monte Carlo simulation the probability that the nuclear power plant enters in an unsafe state and the time needed to recover its safety. The results obtained allow the identification of those elements most critical for the safety and recovery of the nuclear power plant; this is relevant for determining improvements of their structural/functional responses and supporting the decision-making process on safety critical-issues. On the test system considered, under the given assumptions, the components of the external and internal water systems (i.e., pumps and pool) turn out to be the most critical for the safety and recovery of the plant.

Resilience analysis framework for interconnected critical infrastructures

To investigate the resilience of interconnected critical infrastructures (CIs), a framework combining dynamic modeling and resilience analysis is proposed. Resilience is defined in this work as the...

Analysis of the Robustness and Recovery of Critical Infrastructures by Goal Tree–Success Tree: Dynamic Master Logic Diagram, Within a Multistate System-of-Systems Framework, in the Presence of Epistemic Uncertainty

In this paper, we evaluate the robustness and recovery of connected critical infrastructures (CIs) under a system-of-systems (SoS) framework taking into account: (1)xa0the dependencies among the components of an individual CI and the interdependencies among different CIs; (2)xa0the variability in component performance, by a multistate model; and (3)xa0the epistemic uncertainty in the probabilities of transitions between different components states and in the mean values of the holding-times distributions, by means of intervals. We adopt the goal tree success tree–dynamic master logic diagram (GTST–DMLD) for system modeling and perform the quantitative assessment by Monte Carlo simulation. We illustrate the approach by way of a simplified case study consisting of two interdependent infrastructures (electric power system and gas network) and a supervisory control and data acquisition (SCADA) system connected to the gas network. This article is available in the ASME Digital Collection at http://dx.doi.org/10.1115/...

Analysis of the robustness of critical infrastructures within a multistate systems-of-systems framework in the presence of epistemic uncertainties

In this paper, we look at the robustness of connected critical infrastructuresunder a systems-of-systems framework taking into accounti) the dependencies and interdependencies among the components of a critical infrastructure and between different critical infrastructures, respectively; ii) the variability of the performance of each component by means of a multistate model; iii) the epistemic uncertainty in the transition probability between different components states by means of probability intervals. We adopt the Goal Tree Success Tree – Dynamic Master Logic Diagram for system modellingand we perform a quantitative assessment of the systems-ofsystems performance by Monte Carlo simulation. We illustrate the approach by way of a simplified case study consisting of two interdependent infrastructures (electric power system and a gas network) and a supervisory control and data acquisition system connected to the gas network.