Corrosion analysis and studies on prediction model of 16Mn steel by grey system theory

The accident caused by the corrosion of steel in the production of alumina has become an important issue. The corrosion behaviour of 16Mn steel was investigated using weightlessness, scanning electron microscopy, energy-dispersive spectrometry and grey system theory in the sulfur-containing alkaline solutions. This paper proposes three methods to improve prediction accuracy of GM(1, 1) model. Results indicated that corrosion time is the most important influence factor of the corrosion rate of 16Mn steel which satisfies the mathematical relationship of power function in the early stages of corrosion. The corrosion products is mainly composed of elements O, S, Fe, Al, Cr and C, and the particles with better crystallization are mainly oxides (Fe3O4), while the bulk particles are mainly sulfides (FeS). The accuracy of four GM(1, 1) prediction models is better than that of the power function, among which metabolic GM(1, 1) model is the best.