Document: NRC Regulatory Guide
Document ID: 82659041-98b0-4721-b25d-c4fb2ea394d0
Document Type: regulatory_guide
Title: An Approach for Using Probabilistic Risk Assessment in Risk-Informed Decisions on Plant-Specific Changes to the Licensing Basis (Rev. 3)
Source: NRC Regulatory Guide Division 1
Source URL: https://www.nrc.gov/docs/ML1635/ML16358A153.pdf
Revision Date: 2023-06
Chapter: 
Section ID: RG-1.174
CFR Part: 
CFR Title: 

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should be based on an understanding of the contributors to the PRA results; the robustness of the assessment of those contributors, including any conservative or non-conservative biases resulting from modeling assumptions and approximations; and the impacts of the uncertainties, including uncertainties that are explicitly accounted for in the results and those that are not. This is a somewhat subjective process, and the basis for the decisions should be well documented. Section C.2.5.4 of this guide provides guidance on what should be addressed. However, the types of uncertainty that impact PRA results and methods typically used to analyze those uncertainties are briefly discussed first. NUREG-1855 provides acceptable guidance on the treatment of uncertainties in risk-informed decisionmaking. 2.5.1 Types of Uncertainty and Methods of Analysis There are two facets to uncertainty that, because of their natures, should be treated differently when creating models of complex systems. They have recently been termed aleatory and epistemic uncertainty. The aleatory uncertainty is associated with events or phenomena being modeled that are characterized as occurring in a “random” or “stochastic” manner and probabilistic models are adopted to describe their occurrences. It is this aspect of uncertainty that gives PRA the probabilistic part of its name. The epistemic uncertainty is associated with the analyst’s confidence in the predictions of the PRA model itself and reflects the analyst’s assessment of how well the PRA model represents the actual system being modeled. Epistemic uncertainty has also been referred to as state-of-knowledge uncertainty. This section discusses the epistemic uncertainty; the aleatory uncertainty is built into the structure of the PRA model itself. Because they are generally characterized and treated differently, it is useful to identify three classes of epistemic uncertainty that are addressed in and impact the results of PRAs: