Empirical Bayes Estimation of the Reliability of Nuclear-Power-Plant Emergency Diesel Generators

Abstract

For a binomial sampling model using pass/fail data and a beta prior distribution, parametric empirical Bayes (PEB) point and credibility interval estimates are provided for the time-and-diesel average emergency diesel generator (EDG) reliability to load-run on demand at 63 U.S. commercial nuclear power stations. For a geometric sampling model and a beta prior distribution, similar estimates of the time-dependent EDG-average reliability are also obtained for four plants. This is an expository article that introduces seven practical steps, involving both model validation and inference, in applying modern PEB methods. It also illustrates some important advantages of using industry-wide data to make inferences on individual items.