Pitting corrosion modelling of X80 steel utilized in offshore petroleum pipelines

• Published in: Process safety and environmental protection Vol. 141; pp. 135 - 139
• Main Authors: Arzaghi, Ehsan, Chia, Bing H., Abaei, Mohammad M., Abbassi, Rouzbeh, Garaniya, Vikram
• Format: Journal Article
• Language: English
• Published: Rugby Elsevier B.V 01.09.2020; Elsevier Science Ltd
• Subjects: Bayesian analysis; Bayesian Inference; Corrosion; Corrosion environments; Corrosion rate; Corrosion resistance; Degradation; Deterioration; Growth rate; High strength low alloy steels; Marine environment; Markov Chain Monte-Carlo; Methodology; Offshore; Offshore engineering; Offshore Structures; Parameter uncertainty; Petroleum pipelines; Pipelines; Pitting Corrosion; Probabilistic models; Probability theory; Reliability analysis; Reliability engineering; Sodium chloride; Steel; Structural reliability; Bayesian Inference; Offshore Structures; Deterioration; Markov Chain Monte-Carlo; Pitting Corrosion
• ISSN: 0957-5820; 1744-3598
• DOI: 10.1016/j.psep.2020.05.024

•In-situ experimental analysis of pitting corrosion growth as a function of time.•Development of a Bayesian methodology for probabilistic modelling of pitting corrosion growth in steels.•Prediction of time to reach a critical pit size, based on actual damage observations of corrosion.•Presenting a Bayesian approach to estimating the uncertainty associated with corrosion growth in offshore environment. High strength steels such as X80 steels have recently been used more frequently in production of offshore structures. However, they may still be subject to degradation processes such as corrosion considering the conditions in marine environment. Pitting corrosion is a destructive form of corrosion which reduces the material resistance and may result in failure accidents with severe financial, human life and environmental consequences. The process of pitting corrosion is inconsistent and largely stochastic being influenced by a number of parameters with a high level of uncertainty. This makes it very difficult to predict corrosion in terms of its initiation time and spatial behavior. Therefore, it is vital to investigate pitting corrosion phenomena in offshore structures using a probabilistic approach for the assessment of structural reliability and operational safety. In this study, an in-situ experiment has been conducted on X80 steel in an NaCl solution in a laboratory environment to observe the generation and growth of corrosion pits. A probabilistic model based on Hierarchical Bayesian Approach (HBA) is developed for predicting the pitting corrosion growth rate using experimental results. In order to model the process more realistically, the proposed methodology considers the degradation process to be consisting of the time needed for pit initiation and propagation. The results indicate that the proposed methodology is capable of predicting the time required to reach a specific pit size. The methodology developed in this study can be applied to estimate the remaining useful life of subsea structures.