Incorporation of Markov reliability models for digital instrumentation and control systems into existing PRAs
- Ohio State Univ., Dept. of Computer Science and Engineering, 395 Dreese Labs., 2015 Neil Ave., Columbus, OH 43210 Ohio (United States)
- State Univ., Nuclear Engineering Program, 650 Ackerman Road, Columbus, OH 43202 (United States)
- U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Washington, DC 20555 (United States)
Markov models have the ability to capture the statistical dependence between failure events that can arise in the presence of complex dynamic interactions between components of digital instrumentation and control systems. One obstacle to the use of such models in an existing probabilistic risk assessment (PRA) is that most of the currently available PRA software is based on the static event-tree/fault-tree methodology which often cannot represent such interactions. We present an approach to the integration of Markov reliability models into existing PRAs by describing the Markov model of a digital steam generator feedwater level control system, how dynamic event trees (DETs) can be generated from the model, and how the DETs can be incorporated into an existing PRA with the SAPHIRE software. (authors)
- Research Organization:
- American Nuclear Society, 555 North Kensington Avenue, La Grange Park, IL 60526 (United States)
- OSTI ID:
- 22030001
- Country of Publication:
- United States
- Language:
- English
Similar Records
Constructing Dynamic Event Trees from Markov Models
Investigation of the Use of Dynamic Probabilistic Risk Assessment Methodologies for Identifying Digital I&C System Common Cause Failures