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Approximate Bayesian Computation of the occurrence and size of defects in Advanced Gas-cooled nuclear Reactor boilers

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  • Mason, Paolo

Abstract

A campaign of visual inspections was undertaken in 2014 on a specific component of thirty-two Advanced Gas-cooled nuclear Reactor boilers at Hartlepool and Heysham A power stations, as a consequence of an anomalous reading previously obtained in a routine ultrasonic test. While the presence of a crack in Heysham A boiler 1D1 was confirmed, no further defect was detected; not all components could be inspected in all of their eight sections (octants), however, because of the very unfavourable conditions in which the work had to be performed. The occurrence and size of defects in the uninspected octants are here inferred on the basis of models of crack initiation and growth fitted, by Approximate Bayesian Computation, to the results of the campaign. The probability of failure of one or more components in an extreme seismic event is also inferred.

Suggested Citation

  • Mason, Paolo, 2016. "Approximate Bayesian Computation of the occurrence and size of defects in Advanced Gas-cooled nuclear Reactor boilers," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 21-25.
    • Handle: RePEc:eee:reensy:v:146:y:2016:i:c:p:21-25
    DOI: 10.1016/j.ress.2015.10.012
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    References listed on IDEAS

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    1. Kaushik Chatterjee & Mohammad Modarres, 2013. "A probabilistic approach for estimating defect size and density considering detection uncertainties and measurement errors," Journal of Risk and Reliability, , vol. 227(1), pages 28-40, February.
    2. Yuan, X.-X. & Mao, D. & Pandey, M.D., 2009. "A Bayesian approach to modeling and predicting pitting flaws in steam generator tubes," Reliability Engineering and System Safety, Elsevier, vol. 94(11), pages 1838-1847.
    3. repec:dau:papers:123456789/5724 is not listed on IDEAS
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    Cited by:

    1. Mason, Paolo, 2017. "A Bayesian analysis of component life expectancy and its implications on the inspection schedule," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 87-94.
    2. Kristin McCullough & Tatiana Dmitrieva & Nader Ebrahimi, 2022. "New approximate Bayesian computation algorithm for censored data," Computational Statistics, Springer, vol. 37(3), pages 1369-1397, July.

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