A Stochastic Model for Piping Failure Frequency Analysis Using OPDE Data

Abstract

The accurate estimation of piping failure frequency is an important task to support the probabilistic risk assessment and risk-informed in-service inspection of nuclear power plants. Although probabilistic models have been reported in the literature to analyze the piping failure frequency, this paper proposes a stochastic point process model that incorporates both a time dependent trend and plant-specific (or cohort) effects on the failure rate. A likelihood based statistical method is proposed for estimating the model parameters. A case study is presented to analyze the Class 1 pipe failure data given in the OPDE Database.