Document: NUREG-0800
Document ID: 0d034ca5-ee9b-43ca-a6d6-b08e537d605b
Document Type: srp
Title: Determining the Technical Adequacy of Probabilistic Risk
Source: NUREG-0800
Source URL: https://www.nrc.gov/docs/ML0625/ML062510220.pdf
Revision Date: 2023-06
Chapter: 19
Section ID: 19.1
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use-effect relationships are mapped, but also all the events that appear together with those events in the affected accident sequences, and the parts of the analysis required to evaluate the necessary results. For some applications, this may be a limited set, but for others, e.g., risk-informing the scope of special treatment requirements, all parts of the PRA model are relevant. In addition, when the assessed impact of the proposed change, measured in terms of ∆CDF or ∆LERF, is greater than 1E-06/yr or 1E-07/yr respectively, the total CDF and LERF are required to be estimated, broadening the scope of review for technical adequacy. In applying this SRP, the reviewer need only address those parts identified as being required to support the PRA results used. III.2 Assessment of the PRA The part of the PRA used for the application is assessed to determine whether it is of sufficient technical quality. There are two aspects to assessing the acceptability and adequacy of the PRA results. First, the underlying PRA must be technically sound. This implies that (1) the PRA model, or the parts of the model required to support the application, represent the as-built and as-operated plant, which in turn implies that the PRA is up to date and reflects the current design and operating practices, (2) the PRA logic model has been developed in a manner consistent with current good practice and it correctly reflects the dependencies of systems on one another and on operator actions, and (3) the probabilities and frequencies are estimated consistently with the definitions of the corresponding events of the logic model. Second, the engineering analyses, assumptions, and approximations used in developing the PRA model must be appropriate and must demonstrate the robustness of the conclusions with 7 respect to the uncertainties in the analysis. There are issues for which there is no consensus on analytical models or methods of analysis. Furthermore, PRAs are models, and in that sense