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Treating uncertainties in a nuclear seismic probabilistic risk assessment by means of the Dempster-Shafer theory of evidence

Abstract : The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) areaffected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantifiedcoherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can betaken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment istypically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST)framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The maincontributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build theDempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesianupdating based on plant specific data into the framework. The results of the application to a case study show that the approachis feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii)providing ‘conservative’ bounds on the safety quantities of interest (i.e. Core Damage Frequency, CDF) that reflect the(limited) state of knowledge of the experts about the system of interest.
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Chung-Kung Lo, Nicola Pedroni, Enrico Zio. Treating uncertainties in a nuclear seismic probabilistic risk assessment by means of the Dempster-Shafer theory of evidence. Nuclear Engineering and Technology, 2014, 46 (1), pp.11-26. ⟨10.5516/NET.03.2014.701⟩. ⟨hal-01090253⟩

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