Two dynamic methodologies, dynamic flowgraph methodology (DFM) and the Markov/Cell-tocell mapping technique (CCMT), are implemented on the benchmark Digital Feedwater Control System (DFWCS) specified in NUREG-6942, “Dynamic Reliability Modeling of Digital Instrumentation and Control Systems for Nuclear Reactor Probabilistic Risk Assessments,” to demonstrate how an existing nuclear power plant probabilistic risk assessment (PRA) can incorporate a digital upgrade of the instrumentation and control system. The results obtained from the DFM and Markov/CCMT models of the DFWCS failure modes are compared, and the impact of scenarios directly related to the hypothetical digital upgrade on the core damage frequency (CDF) is assessed on a demonstrative basis, using a plant PRA from NUREG-1 150, “Severe Accident Risks: An Assessment for Five U.S. Nuclear Power Plants.” The study shows that a DFWCS similar to that of an operating plant can be modeled using dynamic methodologies and that the results can be incorporated into an existing PRA to quantify the impact of a digital upgrade on the plant CDF.
–
ASCA, Inc. and Ohio State University, A Benchmark Implementation of Two Dynamic Methodologies for the Reliability Modeling of Digital Instrumentation and Control Systems, U.S. Nuclear Regulatory Commission Report NUREG/CR-6985, February 2009
