Developing a regional environmental corrosion model for Q235 carbon steel using a data-driven construction method

Abstract

Studying the impact of the environment on metal corrosion is of considerable significance for the safety assessment of buildings and the life prediction of equipment. We developed a new regional environmental corrosion model (RECM) to predict the atmospheric corrosion of Q235 carbon steel based on measured environmental data and corrosion rates obtained from one-year-long static coupon tests. The corrosion of metals varies depending on the environment; therefore, the ability of the model to distinguish such differences is crucial for accurately predicting corrosion. Herein, the regions in which the test sites were located were divided based on the basic principles of atmospheric corrosion. Furthermore, random forest was used to assess the importance of various environmental factors in the corrosion process within each region, which established a close relationship between corrosion and environmental conditions. Our results showed that the accuracy of the RECM is higher than that of the dose-response function of the ISO9223-2012 standard. The method of model construction can be realized automatically using a computer.