PREDICTION OF ELECTROCHEMICAL PROCESSES OF LOCAL DISSOLUTION OF STAINLESS STEELS. PART 2. ANALYTICAL AND SIMULATION MODELING OF PROCESS DYNAMICS

Abstract

To analyze the process of pitting corrosion, a state graph was used, which displays the possible states of local dissolution of chromium-nickel steels, taking into account the additional state "unstable passivation of macropitting". The developed analytical model for calculating the process before the formation of stable pitting is based on homogeneous Markov chains. The calculation of conditional probabilities of system changes from one possible state to another determines the time in the VisualStudio 2010 environment on the platform of NetFramework using the C# programming language. A comparison of the calculation of states with “unstable passivation of macropitting” (UPM) and without it allowed us to establish for stainless steels (12X18N10T, 10X17N13M2T, 08X22N6T) that the formation time of stable pitting taking into account UPM is less than the formation time without it, but more for 08X22N6T steel, which is due to the increased chromium content in its composition. A simulation model (SM) has been created, which is based on the Monte Carlo method, in which a random number generator is used to implement random processes of local dissolution due to SM, a sequence of states in which the system is located before its transition to a stable state is obtained. Also, due to this model, it became possible to consider the change in the potential of the system in the process of local dissolution of the studied steels. The use of two modeling approaches taking into account the state of the UPM allowed us to establish that IT is better consistent with experimental results both on a quantitative and qualitative level. An algorithm for selecting the values of the mode parameters is proposed, which became the basis for predicting the formation of macropitting processes. For citation: Vinogradova S.S. Prediction of electrochemical processes of local dissolution of stainless steels Part 2. Analytical and simulation modeling of process dynamics. ChemChemTech [Izv. Vyssh. Uchebn. Zaved. Khim. Khim. Tekhnol.]. 2024. V. 67. N 6. P. 119-126. DOI: 10.6060/ivkkt.20246706.6972.