Bayesian Modelling of PWR Vessels Flaw Distributions

Gilles Celeux 1 Matthieu Persoz Joseph Ngatchou Wandji François Perrot
1 IS2 - Statistical Inference for Industry and Health
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive
Abstract : We present a full Bayesian method for estimating the density and size distribution of subclad-flaws in French Pressurized Water Reactor (PWR) vessels. This model takes into account in service inspection (ISI) data, a flaw size-dependent probability of detection function (different function types are possible) with a threshold of detection, and a flaw sizing error distribution (different distribution types are possible). It is identified through a Markov Chain Monte Carlo (MCMC) algorithm. The article includes discussion for choosing the prior distribution parameters and an illustrative application is presented highlighting its ability to provide good parameter estimates even when a small number of flaws is observed.
Type de document :
RR-3551, INRIA. 1998
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Soumis le : mercredi 24 mai 2006 - 11:57:08
Dernière modification le : jeudi 28 juin 2018 - 14:37:59
Document(s) archivé(s) le : dimanche 4 avril 2010 - 21:41:35



  • HAL Id : inria-00073132, version 1



Gilles Celeux, Matthieu Persoz, Joseph Ngatchou Wandji, François Perrot. Bayesian Modelling of PWR Vessels Flaw Distributions. RR-3551, INRIA. 1998. 〈inria-00073132〉



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