Ladle metallurgy is an important steelmaking technology in high-quality steel production. The blowing of argon at the ladle bottom has been applied in ladle metallurgy for several decades. Until now, the issue of breakage and coalescence among bubbles was still far from being solved. In order to have a deep insight into the complex process of fluid flow in the gas-stirred ladle, the Euler-Euler model and population balance model (PBM) are coupled to investigate the complex fluid flow in the gas-stirred ladle. Here, the Euler-Euler model is applied to predict the two-phase flow, and PBM is applied to predict the bubble and size distribution. The coalescence model, which considers turbulent eddy and bubble wake entrainment, is taken into account to determine the evolution of the bubble size. The numerical results show that if the mathematical model ignores the breakage of bubbles, the mathematical model gives the wrong bubble distribution. For bubble coalescence in the ladle, turbulent eddy coalescence is the main mode, and wake entrainment coalescence is the minor mode. Additionally, the number of the bubble-size group is a key parameter for describing the bubble behavior. The size group number 10 is recommended to predict the bubble-size distribution.
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http://dx.doi.org/10.3390/ma16103782 | DOI Listing |
Materials (Basel)
December 2024
Department of Metallurgy and Metals Technology, Faculty of Production Engineering and Materials Technology, Czestochowa University of Technology, Armii Krajowej 19 Ave, 42-201 Czestochowa, Poland.
In this paper, the influence of the structure of the bottom of the ladle with ceramic dam or set of dams on the mixing process was assessed, determining the mixing time required to achieve the level of 95% chemical homogenization. The 0.1 scale water model was used for the physical experiments.
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November 2024
Department of Metal Forming and Metallurgical Engineering, Faculty of Metals Engineering and Industrial Computer Science, AGH University of Krakow, Adama Mickiewicza 30 Ave., 30-059 Kraków, Poland.
The efficiency of the hot metal pretreatment process plays a very important role in achieving high-quality and low-cost advanced steel. From macromixing phenomena obtained by numerical modeling and physical experiments to compound interaction databases from industry trials, the Authors compared fundamental relationships from the literature with their own laboratory results and plant data. A simple numerical model based on the LES turbulence approach was well-validated by water modeling.
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September 2024
Laiwu Iron and Steel Group Yinshan Section Steel Co., Ltd., Jinan 271104, China.
The steelmaking-continuous casting process (SCCP) is a complex manufacturing process which exhibits the distinct features of process manufacturing. The SCCP involves a variety of production elements, such as multiple process routes, a wide array of smelting and auxiliary devices, and a variety of raw and auxiliary materials. The production-simulation of SCCP holds a natural advantage in being able to accurately depict the intricate production behavior involved, and this serves as a crucial tool for optimizing the production operation of the SCCP.
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May 2024
College of Materials Science and Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
Inclusions are one of the important factors affecting the cleanliness of molten steel. The current optimization of inclusion removal methods mainly focuses on promoting inclusions to float to the slag-steel interface so that the inclusions can be absorbed and removed by the refining slag. However, the research on the floating removal of inclusions cannot be carried out directly in the ladle, so methods such as mathematical models and physical models were developed.
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March 2024
Institute of Geotechnics Slovak Academic Science, Watsonova 45, 04 001 Košice, Slovakia.
In metallurgical practice, the material is considered of adequate quality if it meets the customer's expectations. It is necessary to take representative samples and perform quality testing to avoid financial and intangible losses. Sample contamination and matrix and surface quality play a significant role in the accuracy of chemical analyses.
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