Accident risk assessment covers both comparative analysis (e.g., among technologies, scenarios), and analysis of specific critical infrastructure disruptions and their associated consequences (e.g., fatalities, supply disruption, etc.). In the context of critical energy infrastructure, two main methodological approaches have been used by PSI’s Technology Assessment group, namely metamodeling and complex network analysis.
Metamodeling is based on the framework developed by Sudret (2007), which takes into account uncertainty propagation and sensitivity analysis. This framework can be subdivided in four main steps: (1) a computational model is set up to solve the physical problem under interest and all inputs and outputs are defined; (2) marginal probability distributions for each uncertain input and dependences among the inputs are defined; (3) the input uncertainty is propagated through the computational model; (4) a sensitivity analysis completes the framework by identifying inputs that contribute most to the output variability. Such analysis identifies the most prominent uncertain input parameters that affect the uncertain outputs and could help stakeholders in prioritizing the measurements to be adopted to reduce the effect of an unwanted event. At PSI a framework based on metamodeling has been developed for the risk to the human health due to a dam break (e.g., Kalinina et al., 2020).
Complex network analysis is useful to assess the risk of a disruption for specific infrastructure networks. The method allows a simplif representation, while important features such as the network topology are retained. Complex networks assessment is based on three main phases (Lustenberger et al., 2019): (1) transform the real network into a connected and undirected weighted graph with no loop; (2) estimate the flow in the graph, e.g., by using a maximum flow estimation; (3) assess the impact on the network due to a disruption. Such an analysis can identify possible network related issues, and support stakeholders to develop mitigation strategies that improve system resilience. At PSI a complex network analysis framework has been developed to assess the effects of a disruption, triggered by accidents or natural hazards, on the supply at the European Natural Gas network level (e.g., Lustenberger et al., 2019).
A selection of references on the topic are shown below, while further publications can be found here.
Selected References
Kalinina, A., Spada, M., Vetsch, D., Marelli, S., Whealton, C., Burgherr, P., Sudret, B., 2020. Metamodeling for Uncertainty Quantification of a Flood Wave Model for Concrete Dam Breaks. Energies 13(14). http://dx.doi.org/10.3390/en13143685
Lustenberger, P., Schumacher, F., Spada, M., Burgherr, P., Stojadinovic, B., 2019. Assessing the Performance of the European Natural Gas Network for Selected Supply Disruption Scenarios Using Open-Source Information. Energies 12(24). http://dx.doi.org/10.3390/en12244685
Kalinina, A., Spada, M., Burgherr, P., 2018. Alternative life-loss rates for failures of large concrete and masonry dams in mountain regions of OECD countries, in: Haugen, S., Barros, A., Gulijk, C.v., Kongsvik, T., Vinnem, J. (Eds.), Safety and Reliability – Safe Societies in a Changing World. CRC Press, London, UK.
Kyriakidis, M., Lustenberger, P., Burgherr, P., Dang, V., Hirschberg, S., 2018.Quantifying energy systems resilience - A simulation approach to assess recovery, Energy Technology. https://dx.doi.org/10.1002/ente.201700841
Sudret, B., 2007. Uncertainty Propagation and Sensitivity Analysis in Mechanical Models: Contributions to Structural Reliability and Stochastic Spectral Methods, Habilitation a diriger des Recherches, Universit’e Blaise Pascal: Clermont-Ferrand, France