Bayesian Analysis of Piping Leak Frequency Using OECD/NEA Data

Abstract

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.