System reliability of corroding pipelines considering stochastic process-based models for defect growth and internal pressure

Abstract

A methodology is presented to evaluate the time-dependent system reliability of pressurized pipelines that contain multiple active metal-loss corrosion defects and have been subjected to at least one inline inspection (ILI). The methodology incorporates a homogeneous gamma process-based corrosion growth model and a Poisson square wave process-based internal pressure model, and separates three distinctive failure modes, namely small leak, large leak and rupture. The hierarchical Bayesian method and Markov Chain Monte Carlo (MCMC) simulation are employed to characterize the parameters in the corrosion growth model based on data obtained from high-resolution inline inspections (ILIs). An example involving an in-service gas pipeline is used to validate the developed corrosion growth model and illustrate the proposed methodology for the system reliability analysis. Results of the parametric analysis indicate that both the uncertainties in the parameters of the growth model as well as their correlations must be accounted for in the reliability analysis. The proposed methodology will facilitate the application of reliability-based pipeline corrosion management programs.