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Research Papers: Nuclear Power

A Stochastic Model for Piping Failure Frequency Analysis Using OPDE Data

[+] Author and Article Information
X.-X. Yuan

Department of Civil Engineering, Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada

M. D. Pandey

Department of Civil and Environmental Engineering, University of Waterloo, 200 University Avenue, West Waterloo, ON, N2L 3G1, Canada

J. Riznic

 Canadian Nuclear Safety Commission, P. O. Box 1046, Station B, Ottawa, ON, K1P 5S9, Canada

J. Eng. Gas Turbines Power 131(5), 052901 (Jun 09, 2009) (9 pages) doi:10.1115/1.3094027 History: Received October 08, 2008; Revised October 15, 2008; Published June 09, 2009

The accurate estimation of piping failure frequency is an important task to support the probabilistic risk assessment and risk-informed in-service inspection of nuclear power plants. Although probabilistic models have been reported in the literature to analyze the piping failure frequency, this paper proposes a stochastic point process model that incorporates both a time dependent trend and plant-specific (or cohort) effects on the failure rate. A likelihood based statistical method is proposed for estimating the model parameters. A case study is presented to analyze the Class 1 pipe failure data given in the OPDE Database.

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Copyright © 2009 by American Society of Mechanical Engineers
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References

Figures

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Figure 1

Four cases of failure records

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Figure 2

Number versus time of the failure events

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Figure 3

Crow plot for the leakage events of BWR and PWR in U.S.

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Figure 4

Lexis diagram for the BWR-Class 1-Leakage data. The triangles denote a leakage event while the solid dot a permanent shutdown of the NPP.

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Figure 5

Lexis diagram of sample data for U.S.-PWR-Class 1-Leakage. The triangles denote a leakage event while the solid dots denote a permanent shutdown of the NPP.

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Figure 8

Contours of failure rate of BWRs (unit: per plant year)

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Figure 9

Contours of failure rate of PWRs (unit: per plant year)

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Figure 10

Comparison of failure rates of BWRs

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Figure 11

Comparison of failure rates of PWRs

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