Document: NUREG-0800
Document ID: 7916b088-fb90-4163-84fe-027bd315bcc5
Document Type: srp
Title: REVIEW OF RISK INFORMATION USED TO SUPPORT PERMANENT PLANT-
Source: NUREG-0800
Source URL: https://www.nrc.gov/docs/ML0717/ML071700658.pdf
Revision Date: 2023-06
Chapter: 19
Section ID: 19.2
CFR Part: 
CFR Title: 

Content:
ty is discussed in Regulatory Guide 1.174, Section 2.2.5. In that discussion, uncertainties are categorized as parameter, model, and completeness uncertainties. In assessing analysis of uncertainties, reviewers should consider the types and sources of uncertainties identified by the licensee, and how those uncertainties have been addressed with reference to the decision guidelines. Specifically, review guidance is as follows. • Parameter Uncertainty: Reviewers should determine whether the licensee has accounted for parameter uncertainties in an appropriate manner so that the estimated values for CDF, LERF, CDF, and LERF can be regarded as equivalent to mean values. However, this does not imply that a detailed propagation of uncertainties is always necessary; in many cases, it is possible to show that a point estimate is an acceptable approximation of the mean value using qualitative arguments about the risk contributors. For example, if a formal propagation has not been performed, it is necessary for the licensee to demonstrate that the result is not affected by the so-called state of knowledge correlation (specifically, that there are no significant contributing cutsets or scenarios that involve multiple events for which the probabilities are determined using the same parameter, particularly if the parameter value is very uncertain). It is not uncommon for licensees to use point estimate values without defining probability distributions on the values. In such instances, it is not possible to characterize the point estimate as a mean value. However, for the more significant parameters, some characterization of uncertainty is essential to demonstrate that the point estimate is not an optimistic value. • Model Uncertainty: Reviewers should determine whether the results are strongly impacted by the specific models or assumptions adopted for the assessment of important elements of the PRA and whether the sensitivity analyses that have been performed (if any) are