Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
