A Probabilistic Degradation Model for the Estimation of the Remaining Life Distribution of Feeders

Abstract

Wall thinning due to flow accelerated corrosion (FAC) is a pervasive form of degradation in the outlet feeder pipes of the primary heat transport system of CANDU reactors. The prediction of the end-of-life of a feeder from wall thickness measurement data is confounded by the sampling and temporal uncertainties associated with the FAC degradation phenomenon. Traditional regression-based statistical methods deal with only the sampling uncertainties, leaving the temporal uncertainties unresolved. This paper presents an advanced probabilistic model, which is able to integrate the temporal uncertainties into the prediction of lifetime. In particular, a random gamma process model is proposed to model the FAC process and it is calibrated with a set of wall thickness measurements using the method of maximum likelihood. This information can be used to establish an optimum strategy for inspection and replacement of feeders.