In this paper, factors influencing the inclusion removal in high-manganese and high-aluminum steel in RH refining process were studied by numerical simulations, production practice, and metallographic experiments. A mathematical model for inclusion removal was established, and the phenomenon of inclusions mixing in RH up-leg region was verified due to fluid circulation. Removal efficiency of RH circulation time 120 s is much better than 600 s, and it was the lowest efficiency after 600 s. After 600 s circulation time, it shall not apply in production practice. The mass concentration of inclusions in practical steel was 11.64% probability error than values obtained by numerical simulation, because the numerical simulation did not consider the problem of inclusions adsorbing to the walls of refractory materials and corrosion of refractories. This work lays the foundation for the optimization and upgrading of process technology and establishes big data for full automation of RH out of furnace refining.
With the optimization of quality and process, significant progress has been made in the applications of high-manganese and high-aluminum steel. They possess excellent strength, low density, high quality, and good elongation, thereby showing utility in automobile inner plates, electrical motor rotors, marine engineering, military applications, and refrigeration materials. However, the problem of nonmetallic inclusions in metallurgical industry seriously affects the quality of high-manganese and high-aluminum steel, which leads to lower service life. With the rapid development in the steel industry, there is increasing demand for high-quality steel. Researchers have found that oxide nonmetallic inclusions play an important role in the performance of clean steel [
Chen et al. analyzed the process of inclusion collision and growth removal, and considered the influence of gas bubbles in the formation model. However, the influence factors of inclusions adsorbing RH refractory material walls were neglected [
In this paper, a mathematical model of RH inclusion-argon-liquid steel is established in order to provide the foundation for process production by combining mathematical simulation with production practice. By determining the influence of RH circulation time and circulation flow rate on inclusion-argon-molten steel, the RH inclusions-argon-molten steel are analyzed by using the methods of numerical simulation and production practice, and the feasibility of the mathematical model is demonstrated on the basis of experimental data. The proposed method overcomes the probability error between the mathematical model and experimental data, making it more valuable for production practice. Two technical routes of numerical simulation and experimental research are used to analyze and predict the accuracy and reliability of RH inclusion removal, which provide a theoretical basis for process production practice and lay a basis for fully automated steelmaking.
The hypothesis of the model is as follows.
The liquid steel is an incompressible Newtonian fluid, and its multiphase flow is unsteady. The fluctuation of liquid level in ladle top slag and vacuum chamber and the influence of temperature on other physical quantities are neglected. Inclusions nucleate into spheres instantaneously in molten steel, ignoring the effect of slag on other physical quantities. Ladle refractories and RH refractories set wall function. The effect of inclusions on the physical quantity of molten steel is neglected in fluid flow. When inclusions reach the molten steel level, they can be considered to be removed. Argon bubbles are assumed to have a circular [
In the simulation, continuity equations were used to model the reference materials, as follows:
Momentum equation:
Energy equation:
The turbulence model constants are
Turbulent flow energy dissipation equation:
In the formulas (
Here, there is no top slag on the liquid surface of the RH vacuum chamber. Inclusions adsorbed by bubbles return to the molten steel. Inclusions adsorbed by bubbles float to the liquid level of the ladle for removal. The liquid level in RH vacuum chamber has no ability to remove inclusions directly. The mass conservation equation of inclusion collision removal can be expressed as follows [
In the formula (
Inclusion-argon-steel liquid property parameters.
Steel liquid | Inclusions | Argon | |
---|---|---|---|
Density (kg/m3) | 7020 | 3900 | 1.6228 |
Viscosity (kg/m·k) | 0.0006 | 0.02 | 0.00002135 |
Thermal conductivity (w/m·k) | 34 | 1 | 0.0158 |
Cp (J/kg·k) | 680 | 600 | 520.64 |
RH ladle physical model and grid model.
As shown in Figure
Numerical simulation and experiment of inclusion mass concentration.
Mass concentration comparison between numerical simulation and experimental data for different circulation times.
Circulation time (s) | 0 | 120 | 240 | 360 | 480 | 600 | Average value |
|
|||||||
Numerical simulation (ppm) | 187 | 165 | 152 | 136 | 124 | 114 | 146 |
Experiment (ppm) | 187 | 151 | 143 | 127 | 112 | 99 | 129 |
The removal of RH inclusions is analyzed by numerical simulation, the circulation time is set to 1200 s. Figure
Removal of RH inclusions with different circulation flow rates.
Meanwhile, the residual amount of inclusions is influenced by many factors, among which the turbulence and buoyancy plays a dominant role. Figure
The residual amount of inclusions as a function of circulation time with different diameters.
RH circulation time affects the efficiency of inclusion removal and the process production. Optimization of RH circulation time is one of the effective methods to remove inclusions. For RH circulation times of 120 s, 360 s, and 600 s, mass concentration of 165 ppm, 136 ppm, and 114 ppm are observed, respectively. Figure
Inclusions removal at different circulation times. (a) Circulation time: 120 s. (b) Circulation time: 360 s. (c) Circulation time: 600 s.
Figure
Inclusions in RH particle trajectory.
Based on the production of high-manganese and high-aluminum steel, RH vacuum is set to 100 Pa and the circulation flow is 120 Nm3/h. Samples are taken every 120 seconds: A0, A120, A240, A360, A480, and A600, until a time of 600 s is achieved. As listed in Table
Samples of 5 mm × 10 mm are polished by inclusion A0, A120, A240, A360, A480, and A600 and then map scanning Al2O3. The morphology of inclusions is characterized by strips that are irregular, long, and angular, as shown in Figure
Map scanning of inclusions in RH: (a) A0; (b) A120; (c) A240, (d) A360; (e) A480; (f) A600.
In the production of high-manganese and high-aluminum steel by RH, a mathematical model of inclusions removal is established, which lays a theoretical foundation for predicting removal of inclusions from liquid steel. Optimizing RH circulation flow rate and circulation time are effective for removing inclusions by numerical simulations. Compared with the RH circulation times of 120 s and 600 s, the RH circulation time of 120 s has the highest removal efficiency. A 600 s circulation time makes the removal efficiency the lowest, and thus it is not recommended for application in production practice. The turbulence intensity of molten steel in RH fluid field is large, and there exists mixing phenomenon in the up-leg area of RH suction nozzle, which leads to “mixing” of inclusions into vacuum chamber or ladle, which affects the removal efficiency of inclusions. In the later stage of RH circulation, removal of small size inclusions becomes a limiting step in RH refining. Samples of high-manganese and high-aluminum steel produced by RH are taken for metallographic analysis every 120 seconds after the beginning of circulation time. The size of inclusion A0 is larger in the early stage of RH circulation, and its content decreases in the later stage of circulation. The mass concentration probability error of the mathematical model is 11.64%, because the numerical simulation does not consider the problem of inclusions adsorbing to the refractory material walls and corrosion of refractories. This meets the technological requirements of producing high-manganese and high-aluminum steel by RH treatment.
The data used to support the findings of this study are included within the article.
The authors declare that there are no conflicts of interest regarding the publication of this paper.
The authors are grateful for the financial support by the National Key R&D Project of China (2017YFC0805100), the Science and Technology Projects of Liaoning Province (2018307003), the Excellent Talent Project of University of Science Technology of Liaoning (2017RC01), and the project (SKLMEA-USTIN201903) supported by State Key Laboratory of Metallic Materials for Offshore Equipment and Applications.