Reinoso-Burrows, J.C.; Toro, N.; Cortés-Carmona, M.; Pineda, F.; Henriquez, M.; Galleguillos Madrid, F.M. Cellular Automata Modeling as a Tool in Corrosion Management. Materials2023, 16, 6051.
Reinoso-Burrows, J.C.; Toro, N.; Cortés-Carmona, M.; Pineda, F.; Henriquez, M.; Galleguillos Madrid, F.M. Cellular Automata Modeling as a Tool in Corrosion Management. Materials 2023, 16, 6051.
Reinoso-Burrows, J.C.; Toro, N.; Cortés-Carmona, M.; Pineda, F.; Henriquez, M.; Galleguillos Madrid, F.M. Cellular Automata Modeling as a Tool in Corrosion Management. Materials2023, 16, 6051.
Reinoso-Burrows, J.C.; Toro, N.; Cortés-Carmona, M.; Pineda, F.; Henriquez, M.; Galleguillos Madrid, F.M. Cellular Automata Modeling as a Tool in Corrosion Management. Materials 2023, 16, 6051.
Abstract
Cellular automata (CA) models have emerged as a valuable tool in corrosion management. This manuscript provides an overview of the application of cellular automata models in corrosion research, highlighting their benefits and contributions to understanding the complex nature of corrosion processes. Cellular automata models offer a computational approach to simulate corrosion behavior at the microscale, capturing the intricate interactions between electrochemical reactions, material properties, and environmental factors generating a new vision of predictive maintenance. It discusses the key features of cellular automata, such as the grid-based representation of the material surface, the definition of state variables, and the rules governing cell-state transitions. The ability to model local interactions and emergent global behavior makes cellular automata particularly suitable for simulating corrosion processes. Finally, cellular automata models offer a powerful and versatile approach to studying corrosion processes, expanding models that can continue to enhance our understanding of corrosion and contribute to the development of effective corrosion prevention and control strategies.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.