Modeling of Pitting Corrosion Damage Based on Electrochemical and Statistical Methods

Abstract

A new prediction model for pitting corrosion damage considering both pit initiation and pit growth was presented. The pit initiation was modeled based on a combination of the Sridhar model and Macdonald model, and the critical potential was redefined at the same time. The pit initiation time can be divided into the time in which the open circuit potential (OCP) exceeds the repassivation potential (Erp), and the pit induction time, when OCP > Erp. The pit growth was modeled using the Markov process and extreme value statistics were used to describe the maximum pit depth distribution. If the time–consuming pit initiation process is neglected, it results in unacceptable errors in the pit growth kinetics parameters obtained. Thus, an acceleration method, the pre-initiated pits method, was developed to eliminate this negative effect. The proposed model was validated using experimental data on the pitting corrosion of 304 stainless steel (SS) and reproduces the experimental observations with high fidelity.