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Human society is frequently surprised by extreme natural events that lead to tremendous losses both in human lives as well as in economic capital. Risk assessment methods regularly fail to predict such disasters by treating extreme events as low probability, tolerable ones. Critical infrastructures and life lines are often found to be poorly protected due to their inadequate design basis. A method of hazard assessment for extreme natural events is presented that allows for the consideration of unex- pected extreme events (‘black swan’ events). Including such events into the design basis prevents the failure of critical infrastructures due to ‘cliff-edge’ effects. The method makes use of some general properties of heavy-tailed distributions and the mathematical theory of records, and takes advantage of a distribution-free approach without need to calculate probabilities of exceedance. The application of the method is demonstrated on several examples for nuclear power plants (NPP), including High Wind and High Temperature hazards. The results are compared with the results of hazard assessment using conventional probabilistic hazard analysis methods. The risk implications are discussed
black swan theory, critical infrastructures, natural hazards, risk assessment
[1] Klügel, J.U., Lessons not yet learned from the Fukushima disaster. Acta Geodaetica Geophysica, 50, pp. 5–19, 2015. http://dx.doi.org/10.1007/s40328-014-0084-2
[2] WENRA, “Guidance document issue T: natural hazards head document.” guidance for the WENRA safety reference levels for natural hazards introduced as lesson learned from TEPCO Fukushima dai-ichi accident, 2015.
[3] The Fukushima Daichii Accident, report by the director general, IAEA, Vienna, 2015.
[4] Klügel, J.-U., Uncertainty analysis and expert judgment in seismic hazard analysis. Pure and Applied Geophysics, 168, pp. 27–53, 2011. http://dx.doi.org/10.1007/s00024-010-0155-4
[5] Klügel, J.-U., Error inflation in probabilistic seismic hazard analysis. Engineering Geology, 90, pp. 186–192, 2007. http://dx.doi.org/10.1016/j.enggeo.2007.01.003
[6] Taleb, N., The black swan, the impact of the highly improbable, Random House, 2007.
[7] Embrechts, P., Klüppelberg, C. & Mikosch, T., Modelling Extremal Events for Insurance and Finance, Springer: New York, Berlin, Heidelberg, 1997.
[8] Woo, G., The Mathematics of Natural Catastrophes, Imperial College Press, London, 1999.
[9] NRC, Handbook of parameter estimation for probabilistic risk assessment, NUREG/ CR-6823, Washington: U.S. Nuclear Regulatory Commission, 2003.
[10] Nevzorov, V.B., Records: mathematical theory, translations of mathematical monographs. American Mathematical Society, 194, 2001.
[11] Cook, R.M. & Nieboor, D., Heavy-Tailed Distributions: Data, Diagnostics and New Developments, RFF DP 11-19, Resources for the Future, Washington, 2011.
[12] S. F. Resnick, Heavy-Tail Phenomena. Probabilistic and Statistical Modeling., Berlin, Heidelberg, New York: Springer, 2009.
[13] Annaka, T., Satake, K., Sakakiyama, T., Yanagisawa, K. & Shuto, N., Logic-tree Approach for Probabilistic Tsunami Hazard Analysis and its Applications to the Japanese Coasts. Pure and Applied Geophysics, 164, pp. 577–592, 2007. http://dx.doi.org/10.1007/s00024-006-0174-3
[14] Klügel, J.-U., Consideration of “Black Swan” Events in the Seismic Safety Review and the Seismic Upgrade Programme of Existing Nuclear Power Plants – the NPP Goesgen Example, in Post-SmiRT23 Seminar, Istanbul, 2015.