Estimation of Trends in the Scram Rate at Nuclear Power Plants
1999; Taylor & Francis; Volume: 41; Issue: 4 Linguagem: Inglês
10.2307/1271351
ISSN1537-2723
AutoresHarry F. Martz, Robert L. Parker, D.M. Rasmuson,
Tópico(s)Statistical Methods and Bayesian Inference
ResumoAbstract An important task of the U.S. Nuclear Regulatory Commission is to examine annual operating data from the nation's population of nuclear power plants for trends over time. We are interested here in trends in the scram rate at 66 commercial nuclear power plants based on annual observed scram data from 1984–1993. For an assumed Poisson distribution on the number of unplanned scrams, a gamma prior, and an appropriate hyperprior, a parametric empirical Bayes (PEB) approximation to a full hierarchical Bayes formulation is used to estimate the scram rate for each plant for each year. The PEB-estimated prior and posterior distributions are then subsequently smoothed over time using an exponentially weighted moving average. The results indicate that such bidirectional shrinkage is quite useful for identifying reliability trends over time. KEY WORDS: Data smoothingGamma prior distributionHierarchical BayesParametric empirical BayesPoisson samplingReliabilityScram rate estimationShrinkage
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