Abstract: In this study, 2.40 million pieces of big data related to weathering steel corrosion in marine atmospheric environments were collected. An explainable machine learning model was developed to deeply mine this dataset, complemented by laboratory experiments to validate the data-driven insights. A critical atmospheric temperature point was identified, where the corrosion rate of weathering steel is universally low. The governing mechanism primarily operates by regulating the rust layer’s protective performance. When temperature deviates from this critical value, the physical state of the rust layer, chemical reaction kinetics, and wet-dry cycle durations are disrupted, leading to compromised rust layer integrity, inhibited stable phase transformation, and disruption of the thickening-transformation equilibrium, ultimately degrading the corrosion resistance of weathering steel in marine environments.

Key words: Weathering steel, Corrosion, Monitoring, Machine learning, Rust