Atmospheric corrosion prediction of carbon steel and weathering steel based on big data technology

Abstract

In this work, the atmospheric corrosion behavior of Q235 carbon steel and Q420 weathering steel in the environment of Qingdao and Hangzhou was studied. Field exposure tests as well as corrosion big data analysis method were used for evaluating the different corrosion mechanisms of the steels. Results suggest that corrosion big data evaluation method is quite an efficient method for distinguishing the corrosion behavior of different steels in different atmospheric environments. The structure composition of the corrosion products plays a vital role in the corrosion resistance of the steel. Corrosion monitoring method with the corrosion clock diagram and accumulative electric quantity data evaluation method can be used for visualizing the corrosion big data and evaluating the atmospheric corrosion resistance and atmospheric corrosion evolution behavior of Q235 and Q420 steels. The structure and constitute of the rust layer forms on Q235 and Q420 steels in Qingdao and Hangzhou are different. The rust layer formed on Q235 carbon steel has no inner and outer layers while Q420 weathering steel has an inner and outer rust layer. The rust layer of Q420 weathering steel has more α-FeOOH, which helps to accelerate the formation of the protective rust layer, while the rust layer of Q235 carbon steel has more β-FeOOH, which reduces the protection of the rust layer and accelerates the corrosion rate of the metal.