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Auteur Jovica R. Riznic
Documents disponibles écrits par cet auteur
Affiner la rechercheBayesian analysis of piping leak frequency using OECD/NEA data / Min Wang in Transactions of the ASME . Journal of engineering for gas turbines and power, Vol. 132 N° 7 (Juillet 2010)
[article]
in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 132 N° 7 (Juillet 2010) . - 07 p.
Titre : Bayesian analysis of piping leak frequency using OECD/NEA data Type de document : texte imprimé Auteurs : Min Wang, Auteur ; Mahesh D. Pandey, Auteur ; Jovica R. Riznic, Auteur Année de publication : 2011 Article en page(s) : 07 p. Note générale : Génie Mécanique Langues : Anglais (eng) Mots-clés : Nuclear power stations Pipelines Risk analysis Statistical distributions Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : 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. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ000132000007 [...] [article] Bayesian analysis of piping leak frequency using OECD/NEA data [texte imprimé] / Min Wang, Auteur ; Mahesh D. Pandey, Auteur ; Jovica R. Riznic, Auteur . - 2011 . - 07 p.
Génie Mécanique
Langues : Anglais (eng)
in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 132 N° 7 (Juillet 2010) . - 07 p.
Mots-clés : Nuclear power stations Pipelines Risk analysis Statistical distributions Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : 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. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ000132000007 [...]