An approach to the analysis of common cause failure data for plant-specific application
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Abstract The analysis of common cause failures of redundant systems, i.e. failure of multiple components due to a shared cause within their mission time, involves the estimation of probabilities of events for which data based on operating experience are hard to obtain and, when available, do not often provide enough information for unambiguous interpretation and use in the analysis. Because of rarity of common cause failure events on a plant- and system-specific basis, plant-specific probabilistic risk assessments have to rely heavily on the industry (genetic) experience to develop a statistically significant data base for estimation of common cause failure probabilities. The overall approach is described in detail in NUREG/CR 4780 (1989). The process of interpreting generic experience event data and translating them for plant-specific applications involves considerable judgement for which only limited explicit guidance was provided in the aforementioned document. The methods and suggestions given in this paper are intended to fill the gap and to provide the analyst with tools that would enable him or her to adopt a self-consistent, systematic and well-documented approach to failure event interpretation and to provide a quantitative assessment for plant-specific studies. Formulae and parameter estimates are developed to address the most commonly encountered cases in common cause failure data analysis, i.e. events involving degraded states of components, and failures separated in time. Several examples are provided to illustrate the application.
[1] L. Cave. Nuclear power experience : IAEA International Conference on `Nuclear power experience', Vienna, 13-17 September 1982 , 1983 .
[2] K. N. Fleming,et al. Classification and analysis of reactor operating experience involving dependent events , 1985 .
[3] B. D. Johnston. A structured procedure for dependent failure analysis (DFA) , 1987 .
[4] H. M. Paula,et al. Data needs for common cause failure analysis , 1990 .