Calibration of a Pitting Corrosion Simulation Model using Pit Population Data obtained from White Light Interferometry
The annual cost of corrosion worldwide is about US$ 2.5 trillion (i.e. 3 to 4% of GDP of industrialised countries). Out of all types of corrosion, pitting corrosion is most dangerous form because it is very difficult to detect. Once these pits are evolved in to sufficiently large stable pits, they act as a potential source for crack initiation. This is very dangerous for the safety of the structures. It is one of the pressing concerns of our metal based civilisation. Within the framework of mCBEEs Marie Curie ITN, the purpose of this study is to create a simulation tool to predict pitting corrosion behaviour of passivating materials (e.g. AA2024) using numerical modelling.
The objective is to develop and validate a mathematically sound deterministic pitting corrosion model. The challenge here is how to account for and predict various stages of these pits over time. What makes it peculiar is the fact that many factors are involved in this process. The goal is to have conservation equation for pit populations as well as kinetic equations for the accumulation rate of meta-stable, stable pits, and for the re-passivation of large pits. As precipitates induced local potential differences at the surface heavily influences pitting corrosion, the aim is to include those local electrochemical effects in the numerical modelling.
The presentation will cover a brief overview of the idea and methodology of using white light interferometry to model pitting corrosion. Furthermore, the challenges involved in the process will be discussed.