Traditional Probabilistic Risk Assessment Methods for Digital Systems (NUREG/CR-6962)
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Manuscript Completed: May 2008
Date Published: October 2008
T.L. Chu, G. Martinez-Guridi, M. Yue, J. Lehner, and P. Samanta
Brookhaven National Laboratory
P.O. Box 5000
Upton, NY 11973
A. Kuritzky, NRC Project Manager
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington DC 20555-0001
NRC Job Code N6413
At present, there are no consensus methods for quantifying the reliability of digital systems. The U.S. Nuclear Regulatory Commission (NRC) currently is undertaking assessments of the reliability of digital instrumentation and control (I&C) systems, using traditional and non-traditional (dynamic) methods in parallel. The NRC tasked Brookhaven National Laboratory (BNL) with conducting the research on the traditional methods. In general, these are methods that are well-established but they differ from dynamic methods in that they do not explicitly model the interactions between the plant system being modeled and the plant physical processes, nor the timing of these interactions.
The principal objective of the current project is to determine the capabilities and limitations of using traditional reliability modeling methods to develop and quantify digital system reliability models, with the desired goal of supporting the development of regulatory guidance for assessing risk evaluations involving digital systems. To accomplish this objective, the following tasks will be performed:
Develop desirable characteristics for reliability models of digital systems that could provide input to the technical basis for risk evaluations related to current and new reactors.
Select two traditional reliability methods and apply them to two example digital systems to determine the capabilities and limitations of these methods.
Compare the resulting digital system reliability models to the desirable characteristics to identify areas where additional research will improve the capabilities of the methods.
Develop a method, if necessary, for integrating the digital system reliability models into a nuclear power plant probabilistic risk assessment (PRA).
This report specifically addresses the development of the desirable characteristics and lays out the process by which the first reliability study of an example digital system will be performed. This work indicates that the traditional methods of Event Tree/Fault Tree and Markov modeling appear to be useful for the PRA of digital I&C systems, but also reveals limitations in the state-of-the-art for modeling digital systems using traditional PRA methods and where additional research and development are needed. The report offers other insights and conclusions obtained during this work and proposes activities to be conducted when applying these methods to the first reliability study. Note, in keeping with the principal objective stated above, this project will generally not involve advancements in the state-of-the-art, such as the estimation of risk from software faults.
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