Stochastic modeling of pitting corrosion in aluminum alloys

The stochastic theory of pitting corrosion has been successfully used to analyze the statistical nature of pitting. In this paper a Monte Carlo model is used to predict the extent of damage accumulation in aluminum alloys. This model uses experimental parameters obtained by electrochemical noise measurements on electrodes arrays. The algorithm is based on the random occurrence of the metastable pit birth/death or the stable pit growth. Simulated pit depth distributions are compared to experimental data obtained by Optical Profilometry (OP), leading to an improvement of the model and challenging the existence of a metastable/stable transition in free corrosion conditions.

► The evolution of metastable pit birth rate with time shows an initial linear increase and an exponential decay.
► Monte Carlo modeling can successfully reproduce experimental pit depth distributions in aluminum alloys.
► The current density used as a criterion for pit stabilization does not seem to be valid in open circuit conditions.
► The existence of a metastable/stable transition is challenged.