Unification of the deterministic and statistical approaches for predicting localized corrosion damage. I. Theoretical foundation

Abstract

In this paper, we provide an alternative, more general theoretical basis for damage function analysis (DFA), by drawing an analogy between the growth of a pit and the movement of a particle. In contrast to our previous formulation of DFA, which was developed specifically for enabling the damage function for localized corrosion to be calculated from the point defect model for passivity breakdown, the coupled environment pitting model for pit growth, and the theory of prompt and delayed repassivation, the new formulation readily incorporates any theories or models (deterministic or empirical) for these stages in the development of a pit. We show that the new formulation leads to the original expressions for the damage functions for active (living) and passivated (dead) pits, and hence for the differential and integral damage functions, as were obtained from the original theory. We also describe the unification of deterministic (damage function analysis, DFA) and empirical, statistical (extreme value statistics, EVS) methods for predicting the development of localized corrosion damage on metal surfaces. In particular, we have devised a means of estimating the central and scale parameters of EVS directly from DFA in a “first principles” manner, as well as from fitting the EVS distribution function to experimental data for short times, in order to predict the extreme value distributions at longer times. The techniques have been evaluated on EVS data for the pitting of manganese steel in CO 2-acidified seawater and for the pitting of aluminum in tap water. Finally, we outline the generalization of pit nucleation, as described by the point defect model, for external conditions that depend on time.