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:
nd attributes as for at-power. Source Term Analysis • The source term analysis includes the same characteristics and attributes as for at- power. NOTE: (1) For low-power and shutdown conditions, the following characteristics and attributes are also needed: • verification of temporary alignments for the specific outage or average modeled outage for data collection • identification of existing flood barriers that may be impaired or disabled that could impact the flood zone • consideration of automatic responses that may differ from at-power conditions • identification of fire barriers that may be breached that could impact fire propagation between fire areas and fire zones. Technical Elements for Interpretation of Results (Including Uncertainty Analysis) The results of the Level 1 PRA are examined to identify the contributors sorted by hazard group, initiating events (e.g., transients, LOCAs) or specific hazard plant damage states (e.g., fire scenarios, internal flood scenarios, seismic plant damage states), accident sequences, equipment failures, and human errors. Methods such as importance measure calculations (e.g., Fussell-Vesely Importance, risk achievement worth, risk reduction worth, and Birnbaum Importance) are used to identify the contributions of various events to the estimation of CDF for both individual sequences and the total CDF [i.e., both contributors to the total CDF, including the contribution from the different hazard groups and different operating modes (i.e., full- and low-power and shutdown) and contributors to each contributing sequence are identified]. The results of the Level 2 PRA are examined to identify the contributors (e.g., containment failure mode, physical phenomena) to the model estimation of LERF or LRF for both individual sequences 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