Journal Article

Corrosion Behavior and Corrosion Prediction of Carbon Steel under Dynamic Atmospheric Corrosion Environment in Harbin

Ren, Kaixu, Zhou, Lv, Sun, Yunwei, Zhang, Chao, Chen, Zhuo, Song, Xiaoxiao, Wang, Keyu

2025

Overview

A dynamic atmospheric corrosion test was carried out with a dedicated test vehicle operating in Harbin, China. Through corrosion kinetic analysis and corrosion product composition analysis, together with electrochemical tests, the corrosion damage behavior of carbon steel after specific periods of exposure was investigated. The corrosion rate of carbon steel showed a gradual decrease with the increase of corrosion time; the rust layer resistance R f and charge transfer resistance R ct gradually increased due to the hindering effect of the dense rust layer and deposition of SiO 2 . Moreover, three hybrid machine learning models, including ABC-SVR, GA-SVR, and PSO-SVR, were constructed to predict the dynamic atmospheric corrosion rate. The results showed that the PSO-SVR algorithm outperforms the GA-SVR and ABC-SVR algorithms, with MAPE = 6.13%, RMSE = 1.11 μm/year, and R 2  = 0.9810.

• Publisher: Springer US,Springer Nature B.V
• Subject: Accuracy / Algorithms / Atmospheric corrosion / Atmospheric corrosion tests / Carbon steel / Carbon steels / Characterization and Evaluation of Materials / Charge transfer / Chemistry and Materials Science / Corrosion and Coatings / Corrosion rate / Corrosion resistance / Corrosion tests / Damage assessment / Engineering Design / Hot rolling / Humidity / Machine learning / Materials Science / OEM / Optimization / Original Research Article / Pollutants / Quality Control / Reliability / Rusting / Safety and Risk / Silicon dioxide / Support vector machines / Test vehicles / Tribology / Vehicles