Hougaard process stochastic model to predict wall thickness in Flow Accelerated Corrosion

Abstract Nuclear Power Plants (NPPs) operate at very high temperature and high fluid mass flow rate which are favourable for Flow Accelerated Corrosion (FAC) resulting in wall thickness reduction in pipes, bends and other geometries. The prediction of progressive reduction in pipe wall thickness is required for safety of operating NPP. In this paper, Hougaard process stochastic model is proposed for prediction of wall thickness reduction in pipes between two consecutive in-service-inspections. The probability distribution function (PDF) for the Hougaard process is computationally unstable near the origin. Hence, its saddle point approximation was used along with method of maximum likelihood (MLE) to derive the mathematical expressions for the three parameters with generally given time interval between in-service-inspection and corresponding changes in wall thickness. The gamma process model fit and linear fit to data have also been carried out. The predictions of change in pipe wall thickness from probabilistic model are validated by using (a) Experimental data for FAC for 58° bend pipe and (b) NPP feeder pipe data on FAC. The results compare well with the experimental and field data used in analysis.