Resumen
The durability and safety of steel structures during their life cycle are affected by steel corrosion. Limited test conditions and time hinder the reproduction of actual atmospheric steel corrosion. Most test studies have focused on the effect of pitting or uniform corrosion of steel structures, leading to the development of vague engineering methods that make it difficult to design steel structures with excellent corrosion resistance. In this study, a method involving three-dimensional cellular automata and a genetic algorithm was developed for predicting the corrosion behavior of structural steel. The calculation efficiency of three-dimensional cellular automata was improved by small iterative steps and adaptive activation for potential corrosion. Furthermore, the proposed method was tested with published tests, and the results showed that the method can simulate atmospheric corrosion with excellent accuracy and efficiency. The simulation results were used to calculate the structural steel cross-sectional performance with greater accuracy than that of the method of assuming uniform corrosion. Meanwhile, with accurate material parameters, the proposed method can also simulate the atmospheric corrosion of high-performance steel of different strengths and properties.