Bibliographic Details
| Title: |
Multiobjective Collaborative Optimization of Argon Bottom Blowing in a Ladle Furnace Using Response Surface Methodology |
| Authors: |
Zicheng Xin, Jiankun Sun, Jiangshan Zhang, Bingchang He, Junguo Zhang, Qing Liu |
| Source: |
Mathematics, Vol 10, Iss 15, p 2610 (2022) |
| Publisher Information: |
MDPI AG, 2022. |
| Publication Year: |
2022 |
| Collection: |
LCC:Mathematics |
| Subject Terms: |
ladle furnace, argon bottom blowing, hydraulic experiment, mixing time, slag eye area, multiobjective collaborative optimization, Mathematics, QA1-939 |
| More Details: |
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. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2227-7390 |
| Relation: |
https://www.mdpi.com/2227-7390/10/15/2610; https://doaj.org/toc/2227-7390 |
| DOI: |
10.3390/math10152610 |
| Access URL: |
https://doaj.org/article/6edf1ce100a342aabbfaac12f6da6493 |
| Accession Number: |
edsdoj.6edf1ce100a342aabbfaac12f6da6493 |
| Database: |
Directory of Open Access Journals |
