United States Nuclear Regulatory Commission - Protecting People and the Environment

A Benchmark Implementation of Two Dynamic Methodologies for the Reliability Modeling of Digital Instrumentation and Control Systems (NUREG/CR-6985)

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Publication Information

Manuscript Completed: September 2008
Date Published: February 2009

Prepared by:
T. Aldemir1, S. Guarro2, J. Kirschenbaum3, D. Mandelli1, L.A. Mangan1,
P. Bucci3, M. Yau2, B. Johnson4, C. Elks4, E. Ekici5, M.P. Stovsky1,
D.W. Miller1, X. Sun1, S.A. Arndt6, Q. Nguyen6, J, Dion7

1The Ohio State University, Nuclear Engineering Program,
Columbus, OH 43210

2ASCA, Inc., 1720 S. Catalina Avenue, Suite 220,
Redondo Beach, CA 90277-5501

3The Ohio State University, Department of Computer Science and
Engineering, Columbus, OH 43210

4University of Virginia, Department of Electrical and Computer Engineering,
Charlottesville, VA 22904

5The Ohio State University, Department of Electrical and Computer
Engineering, Columbus, OH 43210

6U.S. Nuclear Regulatory Commission, Washington, DC 20555-0001

7Sandia National Laboratories, Department of Risk and Reliability
Analysis, Albuquerque, NM 87185

S.A. Arndt and Q. Nguyen, NRC Project Managers

NRC Job Code K6472

Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

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Abstract

Two dynamic methodologies, dynamic flowgraph methodology (DFM) and the Markov/Cell-to-cell 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-1150, “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.

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