During the Al-killed steel continuous casting process, the molten steel corrosion and the accumulation of alumina inclusion deposits affect the submerged entry nozzle (SEN) wall surface, including the surface morphologies of the smooth wall, porous refractory wall, and clogged wall. The SEN wall surface morphology affects the boundary layer structure and alumina inclusions transport. In this study, a physical modeling method was adopted, and the surface morphologies simulation was realized by filling up the natural porous refractory material and inserting the real clog material in the polymethyl methacrylate SEN model. The velocity in the boundary layer was measured using the particle image velocimetry (PIV) technology, and the alumina inclusions transport path in the boundary layer was calculated by MATLAB software. The MATLAB codes combined the velocity data from the PIV measurement results and the inclusion transport equation. The four-quadrant analysis showed that sweep and ejection events existed in the boundary layer. The fluctuations of the velocity and the turbulent kinetic energy in the normal direction were increased in the porous refractory and the clogged wall boundary layer when the sweep and ejection events existed. The transport of the alumina inclusions with a diameter of 1–15 μm was affected by the ejection and the sweep events. The alumina inclusions moved toward the boundary in the sweep event. During the sweep event, the transport path of alumina inclusions with 1 μm diameter was close to the boundary; the alumina inclusions were more easily attached to the boundary. The alumina inclusions escaped from the boundary in the ejection event. In the porous refractory and the clogged walls, the alumina inclusion transport path in the normal direction was increased. When the SEN wall’s morphologies changed from smooth wall to porous refractory wall and clogged wall, the sweep event area proportion increased from 10.17% to 39.77%, and the ejection event area proportion decreased from 32.96% to 9.24%. Moreover, the sweep event’s probability increased from 25.83% to 28.24% when the morphologies of the SEN wall changed from smooth wall to porous refractory wall and clogged wall, which will increase the alumina inclusion deposition rate in the porous refractory wall and the clogged wall boundary.
Nozzle clogging affects molten steel flow, inclusion transport and slab quality. In this paper, a numerical simulation model for the nozzle clogging and the effect of the relevant parameters on the nozzle clogging simulation is studied. The nozzle clogging impact on the flow, inclusion transport and the nozzle clogging formation process are studied. The numerical simulation of the flow in the mold and nozzle is verified by particle image velocimetry measurement of the mold. The obtained simulation results of the clogged nozzle are verified by industrial experiments. The nozzle clog growth rate increases when the higher inclusion magnification factor is used. However, the nozzle clogging simulation results show that a hole exists in the nozzle clog. The deviation between the nozzle clog thickness obtained by the simulation results and those obtained from the experiments increase when the inclusion magnification factor increases from 1 to 20. The increase of the random walk model parameter increases the randomness of the inclusion transport. It is beneficial to increase the homogeneous simulation results of the nozzle clog thickness. The nozzle clogs that are initially formed in the upper section of the nozzle and extend then to the nozzle port. The nozzle clogs change the inner shape of the nozzle and result in the jet stream disperse, and the impact depth of the jet stream decreases when the solution time increases. The solid shell captures more inclusions, and the solid shell cleanliness decreases when the solution time increases.
The reduction of ferroalloy consumption in the steelmaking process has great significance in reducing energy consumption and saving production costs of steelmaking. However, the consumption of ferroalloys was influenced by many factors; few studies focus on the influence factors on the consumption and cost of ferroalloys. In this paper, the drum experimental method, the data analysis method, the calibration method of the molten steel weight, the alloy consumption data, the record data of steelmaking, and the yield data of the alloy were used. The linear programming optimal solution model contained the steelmaking data, the yield, composition, and cost of the alloy that, based on the lowest cost, were established in this work. The alloy consumption during the steelmaking was affected by the converter endpoint carbon content, alloy yield, alloy pulverization rate, alloy composition, and the molten steel weight deviation. The alloy yield rate will decrease when the alloy pulverization rate increases, which results in the alloy cost increase of 1.01-6.03 yuan per ton of molten steel in the steel A alloying process. The content accuracy of the alloying elements in the molten steel was increased when the weight of molten steel deviation ratio is within the range of -2%~0%that resulted in the average cost of the alloying decreasing by 2 yuan in one ton of steel.
The argon-stirred ladle is a standard piece of steelmaking refining equipment. The molten steel quality will improve when a good argon-stirred process is applied. In this paper, a Multiphysics model that contained fluid flow, bubble transport, alloy transport, bubble heat flux, alloy heat flux, alloy melting, and an alloy concentration species transport model was established. The fluid model and bubble transport model that were used to calculate the fluid velocity were verified by the hydraulic model of the ladle that was combined with particle image velocimetry measurement results. The numerical simulation results of the temperature fields and steel–slag interface shape were verified by a ladle that contained 25 t of molten steel in a steel plant. The velocity difference between the hydraulic model and numerical model decreased when the CL (integral time-scale constant) increased from 0 to 0.3; then, the difference increased when the CL increased from 0.3 to 0.45. The results showed that a CL of 0.3 approached the experiment results more. The bubble heat flux model was examined by the industrial practice, and the temperature decrease rate was 0.0144 K/s. The simulation results of the temperature decrease rate increased when the initial bubble temperature decreased. When the initial bubble temperature was 800 °C, the numerical simulation results showed that the temperature decrease rate was 0.0147 K/s, and the initial bubble temperature set at 800 °C was more appropriate. The average melting time of the alloy was 12.49 s and 12.71 s, and the mixture time was approximately the same when the alloy was added to two slag eyes individually. The alloy concentration had fewer changes after the alloy was added in the ladle after 100 s.
The bubbles have been widely applied in industrial processing, including steelmaking. Recently, industrial trials of natively generated bubbles via decomposition reactions have been successfully adopted in steel refining and inclusion removal. The refining efficiency was proved to be outstanding due to the small bubble sizes and the subsequent satisfying dynamic conditions. However, the bubble behaviors, including growth and detachment, are still not thoroughly clarified due to the strict requirements for observation conditions. Therefore, the growth and detachment behavior of the bubbles generated by decomposition reactions were carefully observed with physical modeling and shadow imaging method. The detachment sizes of the bubbles were extracted accordingly. Based on the statistical data on the detachment bubble sizes, a traditional nozzle flow model was modified for the prediction of the bubble detachment size in decomposition reactions. This work provides the foundation for further studies on the interaction mechanism between the natively generated bubbles and the impurities in liquid steel in terms of inclusion removal.
Two submerged entry nozzles (SENs) used for casting 1300 tons and 260 tons of Al-killed steel were dissected. Several parameters including block rate, nozzle clog angle, port width, and port height of the clogged nozzle were introduced to describe the geometry of clogs in the SENs based on the dissection; furthermore, a geometry model was established to describe the characteristics of the nozzle clogging of the SENs. A large-eddy simulation (LES) coupled with the volume of fraction (VOF) method was adopted to simulate the steel–slag interface’s interaction behavior. The vortex visualization and rotation magnitude were characterized by the Liutex method. Quantitatively, the influence of nozzle clogging resulted in block rates of 0% to 45.9% on the flow and vortex distribution in the mold, and the characteristics of the steel–slag interface fluctuation were well verified in the industrial experiment.
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