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Analysis of surveillance test interval by Markov process for SDS1 in CANDU nuclear power plants

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  • Cho, Sungwhan
  • Jiang, Jin

Abstract

The Canadian Nuclear Safety Commission (CNSC) requires that each shutdown system (SDS) of CANDU plant should be available more than 99.9% of the reactor operating time and be tested periodically. The compliance with the availability requirement should be demonstrated using the component failure rate data and the benefits of the tests. There are many factors that should be considered in determining the surveillance test interval (STI) for the SDSs. These includes: the desired target availability, the actual unavailability, the probability of spurious trips, the test duration, and the side effects such as wear-out, human errors, and economic burdens. A Markov process model is developed to study the effect of test interval in the shutdown system number one (SDS1) in this paper. The model can provide the quantitative data required for selecting the STI. Representing the state transitions in the SDS1 by a time-homogeneous Markov process, the model can be used to quantify the effect of surveillance test durations and interval on the unavailability and the spurious trip probability. The model can also be used to analyze the variation of the core damage probability with respect to changes in the test interval once combined with the conditional core damage model derived from the event trees and the fault trees of probabilistic safety assessment (PSA) of the nuclear power plant (NPP).

Suggested Citation

  • Cho, Sungwhan & Jiang, Jin, 2008. "Analysis of surveillance test interval by Markov process for SDS1 in CANDU nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 1-13.
  • Handle: RePEc:eee:reensy:v:93:y:2008:i:1:p:1-13
    DOI: 10.1016/j.ress.2006.10.007
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    Cited by:

    1. Yan, Rundong & Dunnett, Sarah & Andrews, John, 2023. "A Petri net model-based resilience analysis of nuclear power plants under the threat of natural hazards," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Marhavilas, P.K. & Koulouriotis, D.E., 2012. "A combined usage of stochastic and quantitative risk assessment methods in the worksites: Application on an electric power provider," Reliability Engineering and System Safety, Elsevier, vol. 97(1), pages 36-46.
    3. Hellmich, Mario & Berg, Heinz-Peter, 2015. "Markov analysis of redundant standby safety systems under periodic surveillance testing," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 48-58.

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