Cellular automata approach to corrosion and passivity phenomena

Abstract

Our research on employing the cellular automata methodology to corrosion and passivation phenomena is reviewed. Examples of a peculiar pit development are found and presented. The diffusion rate in the corroding medium is argued and shown in the simulation results to affect mainly the characteristic length scale for the corrosion process. New data for the pitting corrosion development on a planar interface are presented and discussed.

Corrosion-passivation processes in a cellular automata based simulation study

“…3a are already published and discussed [17,18]. Here we show some additional examples illustrating the peculiar behavior of the cavity shape and the main features of these results.…”

“…It is used mainly to describe development of a cavity initiated by a punctual damage of the insulating layer covering the surface. In a recent paper we considered this model also for a planar surface [18] concentrating on a single pit development and its morphology. Here we sketch the general outline of the model (Sect.…”

Modeling pitting corrosion by means of a 3D discrete stochastic model

“…Microscopic description of the Monte Carlo or molecular dynamics type are not interesting for pitting corrosion since this is a rather scarce event on the atomic scale. With the size of the corrosion pits in the range of 10-100 nm, the time and space scales of the phenomenon are far beyond the reach of the presentday atomistic level computations [38]. On the other hand, a macroscopic description with classical kinetic equations, normally based on a system of PDEs, poses the problem that in most cases analytical solutions of the resulting equations are not at hand.…”

“…The transition function U determines the state of a cell c i;j;k at the ðt þ 1Þth time step based on the cell's current state and the states of its neighboring cells and is devised as to mimic, as closely as possible, the physicochemical processes involved in pitting corrosion at a mesoscopic level [38]. The transition function U that is used in the remainder of this paper is executed in a stochastic and synchronous manner.…”

“…The use of CAs in the field of corrosion is relatively new [36,37], but the number of researchers employing CAs as well as the knowledge on the subject is growing. Although many different aspects that influence corrosion, such as film formation, pH, potential differences and heterogeneous composition of alloys, are being explored and are incorporated in CAbased models, most of them only establish a qualitative resemblance between the simulated model output and the real-world phenomenon, ignoring the importance of a sound model validation that is a prerequisite to have a model with predictive value [2,17,19,[38][39][40][41]. Only very recently, a few authors validated their CA-based model using time series of data, but with modest success [42].…”