This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.

The applicability of galvanic-cell-based atmospheric corrosion monitoring (ACM) technology has been confirmed empirically in field tests, however the corrosion behaviors on the ACM sensors have rarely been studied systematically. In this study, the influence of temperature, chloride ions, and hydrosulfite (simulated sulfur dioxide) ions on the corrosion behaviors of Fe/Cu-type ACM sensors was investigated. The results show that the hydrosulfite ions led to a larger increase in the Fe/Cu-based ACM current than chloride ions in the initial stage of corrosion, and both changed the components of the corrosion products. Moreover, the hydrosulfite and chloride ions showed a synergistic effect on the corroded ACM sensor. Lastly, a positive correlation between ACM technology and the mass loss method was observed, further indicating that ACM technology can be an effective, convenient, and fast approach to studying the accelerated corrosion behaviors of steels.

In this study, the Fe/Cu-based two-electrode corrosion monitoring technique was employed to monitor the long-term atmospheric corrosion of carbon steel at five different outdoor sites within the China National Environmental Corrosion Platform. Based on the fitted monitoring data, the variation trend of corrosion-critical humidity as a function of exposure time at different monitoring locations was obtained. The cross-sectional rust layer of corrosion coupons from different experimental periods at each location was characterized using scanning electron microscopy and Raman spectroscopy to identify variations in the thickness and phase composition of the carbon steel rust layer. The influence of rust layer thickness and phase structure on the critical humidity of carbon steel in atmospheric environments was investigated. Finally, the corrosion resistance of weathering steel in Tianjin, China, was validated using corrosion monitoring techniques, and the corrosion mechanism of weathering steel was elucidated by analyzing the influence of the acquired rust layer phase structure on the critical humidity of carbon steel in atmospheric environments.