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Research Papers: Nuclear Power

Bayesian Analysis of Piping Leak Frequency Using OECD/NEA Data

[+] Author and Article Information
Min Wang, Mahesh D. Pandey

Department of Civil Engineering, University of Waterloo, Waterloo, ON, N2L 3G1, Canada

Jovica R. Riznic

 Canadian Nuclear Safety Commission, Ottawa, ON, K1P 5S9, Canada

J. Eng. Gas Turbines Power 132(7), 072902 (Apr 26, 2010) (7 pages) doi:10.1115/1.4000343 History: Received July 21, 2009; Revised July 28, 2009; Published April 26, 2010; Online April 26, 2010

The estimation of piping failure frequency is an important task to support the probabilistic risk analysis and risk-informed in-service inspection of nuclear power plant systems. This paper describes a hierarchical or two-stage Poisson-gamma Bayesian procedure and applies this to estimate the failure frequency using the Organization for Economic Co-operation and Development/Nuclear Energy Agency pipe leakage data for the United States nuclear plants. In the first stage, a generic distribution of failure rate is developed based on the failure observations from a group of similar plants. This distribution represents the interplant (plant-to-plant) variability arising from differences in construction, operation, and maintenance conditions. In the second stage, the generic prior obtained from the first stage is updated by using the data specific to a particular plant, and thus a posterior distribution of plan specific failure rate is derived. The two-stage Bayesian procedure is able to incorporate different levels of variability in a more consistent manner.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

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Figure 1

Posterior distribution of hyperparameters (a) α and (b) β

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Figure 2

Comparison of estimated and parent PVCs

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Figure 3

Estimated PDF of failure rate (λ31)

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Figure 4

PVCs for different NPPs

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Figure 5

Plant-specific pipe leak rate for different NPPs

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Figure 6

Comparison of posterior distributions of λ for Plant 1 obtained from different Bayesian methods

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