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On Broadening Failure Rate Distributions in PRA Uncertainty Analyses

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  • Harry F. Martz

Abstract

Several recent nuclear power plant probabilistic risk assessments (PRAs) have utilized broadened Reactor Safety Study (RSS) component failure rate population variability curves to compensate for such things as expert “overvaluation bias” in the estimates upon which the curves are based. A simple two‐components of variation empirical Bayes model is proposed for use in estimating the between‐expert variability curve in the presence of such biases. Under certain conditions this curve is a population variability curve. Comparisons are made with the existing method. The popular procedure appears to be generally much more conservative than the empirical Bayes method in removing such biases. In one case the broadened curve based on the popular method is more than two orders of magnitude broader than the empirical Bayes curve. In another case it is found that the maximum justifiable degree of broadening of the RSS curve is to increase α from 5% to 12%, which is significantly less than the 20% value recommended in the popular approach.

Suggested Citation

  • Harry F. Martz, 1984. "On Broadening Failure Rate Distributions in PRA Uncertainty Analyses," Risk Analysis, John Wiley & Sons, vol. 4(1), pages 15-23, March.
    • Handle: RePEc:wly:riskan:v:4:y:1984:i:1:p:15-23
    DOI: 10.1111/j.1539-6924.1984.tb00128.x
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    Cited by:

    1. George Apostolakis, 1985. "The Broadening of Failure Rate Distributions in Risk Analysis: How Good Are the Experts?," Risk Analysis, John Wiley & Sons, vol. 5(2), pages 89-91, June.
    2. Harry F. Martz, 1986. "Response to “Problems with Empirical Bayes”," Risk Analysis, John Wiley & Sons, vol. 6(3), pages 273-274, September.

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