by Escobar Rangel, Lina; Leveque, Francois (Centre d'Economie Industrielle. ecole des Mines de Paris. 75006, Paris (France)); CERNA, MINES ParisTech, 60 boulevard Saint Michel, 75006 Paris (France) http://inis.iaea.org/search/search.aspx?orig_q=source:%22HAL--00740684-V1%22
[en]
How to predict the probability of a nuclear accident using past observations? What
increase in probability the Fukushima Dai-ichi event does entail? Many models and
approaches can be used to answer these questions. Poisson regression as well as Bayesian
updating are good candidates. However, they fail to address these issues properly
because the independence assumption in which they are based on is violated. We propose
a Poisson Exponentially Weighted Moving Average (PEWMA) based in a state-space time
series approach to overcome this critical drawback. We find an increase in the risk
of a core meltdown accident for the next year in the world by a factor of ten owing
to the new major accident that took place in Japan in 2011. (authors)SubjectGENERAL STUDIES OF NUCLEAR REACTORS (S22), MATHEMATICAL METHODS AND COMPUTING (S97)
Source/ReportOct 2012, 18 p, INIS-FR--13-0008, HAL--00740684-V1, 15 refs., Available from the INIS Liaison Officer for France, see the 'INIS contacts' section of the INIS website for current contact and E-mail addresses: http://www.iaea.org/INIS/contacts/
Record TypeMiscellaneous
Country/Org.France
DECACCIDENTS, CALCULATION METHODS, COMPUTER CODES, MATHEMATICS, REACTOR ACCIDENTS, STATISTICS
DEIMATHEMATICAL MODELS, MELTDOWN, P CODES, PROBABILISTIC ESTIMATION, REGRESSION ANALYSIS, RELIABILITY, RISK ASSESSMENT, SAFETY ANALYSIS, TIME-SERIES ANALYSIS
LanguageEnglish
Ref. Number44011505
Publ. Year2012
INIS Volume44
INIS Issue03
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