Document: NRC Regulatory Guide
Document ID: 22ccfd5e-c5d8-4615-a02c-32369aa9f533
Document Type: regulatory_guide
Title: Acceptability of Probabilistic Risk Assessment Results for Risk-Informed Activities (Rev. 3)
Source: NRC Regulatory Guide Division 1
Source URL: https://www.nrc.gov/docs/ML1930/ML19308B636.pdf
Revision Date: 2023-06
Chapter: 
Section ID: RG-1.200
CFR Part: 
CFR Title: 

Content:
uences and the model as a whole, using such tools as importance measure calculations (e.g., Fussell- Vesely Importance, risk achievement worth, risk reduction worth, and Birnbaum Importance). For many applications, it is necessary to combine the PRA results from different hazard groups (e.g., from internal events, internal fire, and seismic events). For this reason, an important aspect in interpreting the PRA results is understanding both the level of detail associated with the modeling of each of the hazard groups, and the hazard group-specific model uncertainties. With respect to the level of detail, for example, the analysis of specific scope items such as internal fire, internal flood, or seismic events typically involves a successive screening approach, so that more detailed analysis can focus on the more significant contributions. The potential conservatism associated with the evaluation of the less significant contributors using this approach is assessed for each hazard group. DG-1362, Page 34 In addition, each of the hazard groups has unique sources of uncertainty which can influence the insights derived from the PRA model. These sources can be a result of uncertainties in the parameter values used to quantify the PRA or from the models used to reflect the phenomena associated with the severe accident progression delineated in the PRA. Uncertainty and sensitivity analyses identify and characterize sources of uncertainty as well as the potential sensitivities of the results to related assumptions and modeling approximations. Assumptions made in response to sources of model uncertainty and any conservatisms introduced by the analysis approaches can bias the assessment of importance measures with respect to the combined risk assessment and the relative contributions of the hazard groups to the various risk metrics. Therefore, the sources of model uncertainty are identified and their impact on the results analyzed for each hazard group individually, so that,