Document: NUREG-0800
Document ID: 8dd882f4-a34f-4415-acd1-ebb441c72786
Document Type: srp
Title: PROBABILISTIC RISK ASSESSMENT AND SEVERE ACCIDENT
Source: NUREG-0800
Source URL: https://www.nrc.gov/docs/ML1213/ML12132A481.pdf
Revision Date: 2023-06
Chapter: 19
Section ID: 19.0
CFR Part: 
CFR Title: 

Content:
��s DI&C risk assessment. B. The modeling of DI&C systems should include the identification of how DI&C systems can fail and what these failures can affect. The failure modes of DI&C systems are often identified by the performance of failure modes and effects analyses (FMEA). It is difficult to define DI&C system failure modes especially for software because they occur in various ways depending on specific applications. Also, failure modes, causes, or effects often are intertwined or defined ambiguously, and sometimes overlap or are contradictory. The reviewer should review the depth of the FMEA or other hazard analysis techniques employed by the applicant to ensure the process employed is systematic and comprehensive in its identification of failure modes. The PRA reviewer should work with the instrumentation and control reviewer to evaluate the methodology and results provided by the applicant. Examine applicant documentation to ensure that the most significant failure modes of the DI&C are documented with a description of the sequence of events that need to take place to fail the system. The sequence of events should realistically represent the system’s behavior at the level of detail of the model. C. The DI&C system CCF events should be identified by the applicant and the bases provided for grouping of CCFs. Review the discussion of how the applicant determined the probabilities associated with CCFs. The PRA reviewer should work closely with the I&C reviewer to evaluate the applicant’s justifications. D. Uncertainties in DI&C modeling and data should be addressed in the DI&C risk assessment. It is expected that the DI&C risk assessment will address uncertainties by at least performing a number of sensitivity studies that vary modeling assumptions, reliability data, and parameter values both at the component and system level. The reviewer should evaluate the sensitivity studies performed by the applicant on the PRA models and data to assess the effect of