Multiobjective Collaborative Optimization of Argon Bottom Blowing in a Ladle Furnace Using Response Surface Methodology

Zicheng Xin, Jiankun Sun, Jiangshan Zhang, Bingchang He, Junguo Zhang and Qing Liu
Additional contact information
Zicheng Xin: State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China
Jiankun Sun: State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China
Jiangshan Zhang: State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China
Bingchang He: State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China
Junguo Zhang: Tangshan Branch, Hebei Iron and Steel Co., Ltd., Tangshan 063000, China
Qing Liu: State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing, Beijing 100083, China

Mathematics, 2022, vol. 10, issue 15, 1-16

Abstract: In order to consider both the refining efficiency of the ladle furnace (LF) and the quality of molten steel, the water model experiment is carried out. In this study, the single factor analysis, central composite design principle, response surface methodology, visual analysis of response surface, and multiobjective optimization are used to obtain the optimal arrangement scheme of argon blowing of LF, design the experimental scheme, establish the prediction models of mixing time ( MT ) and slag eye area ( SEA ), analyze the comprehensive effects of different factors on MT and SEA , and obtain the optimal process parameters, respectively. The results show that when the identical porous plug radial position is 0.6R and the separation angle is 135°, the mixing behavior is the best. Moreover, the optimized parameter combination is obtained based on the response surface model to simultaneously meet the requirements of short MT and small SEA in the LF refining process. Meanwhile, compared with the predicted values, the errors of MT and SEA for different conditions from the experimental values are 1.3% and 2.1%, 1.3% and 4.2%, 2.5% and 3.4%, respectively, which is beneficial to realizing the modeling of argon bottom blowing in the LF refining process and reducing the interference of human factors.

Keywords: ladle furnace; argon bottom blowing; hydraulic experiment; mixing time; slag eye area; multiobjective collaborative optimization; response surface methodology (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/15/2610/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/15/2610/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:15:p:2610-:d:872182

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().