Physical study of the impact of injector design on mixing, convection and turbulence in ladle metallurgy

Gajjar, Prince; Haas, Tim; Owusu, Kwaku Boateng; Eickhoff, Moritz; Kowitwarangkul, Pruet; Pfeifer, Herbert

doi:10.1016/j.jestch.2018.11.010

Cited by 14 publications

(9 citation statements)

References 31 publications

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“…The reliability of numerical modeling could be verified by the same mixing times for KCl solution of experimental and simulated results, the agreement of velocity field between simulated result and the PIV result in Gajjar's work [51], and the same diffusion paths for color dye of experimental result and KCl solution of simulated result.…”

Section: Discussionmentioning

confidence: 66%

“…The comparison of Figure 6a,b shows that the velocity magnitudes of water in the model ladle; except the plume zone of the PIV, result are almost the same as that of the simulated result. In Gajjar's work [51], since the bubble plume is very dense, the void fraction in this region is very high. Consequently, fewer tracers could be detected for the evaluation of the flow field.…”

Section: Verification For Numerical Modelingmentioning

confidence: 95%

“…The mixing times of numerical modeling agree well with the results of the physical modeling. Figure 6 shows the velocity fields of the PIV (particle image velocimetry) result for case V of the previous study of Gajjar et al [51], and the result of a simulation based on the dimensional parameters, blowing parameters of the case V in Gajjar's study [40], and the numerical modeling in Section 3. The comparison of Figure 6a,b shows that the velocity magnitudes of water in the model ladle; except the plume zone of the PIV, result are almost the same as that of the simulated result.…”

Section: Verification For Numerical Modelingmentioning

confidence: 99%

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Effect of Side Blowing on Fluid Flow and Mixing Phenomenon in Gas-Stirred Ladle

Cheng

Zhang

Yin

et al. 2021

Metals

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To investigate the gas agitation characteristics of side blowing, the fluid flow and mixing phenomenon in a 1:3 scale model ladle of a 150 t industrial gas-stirred ladle with bottom and side plugs were studied by using physical and numerical modelings together. Side blowing enhanced the horizontal flow of water in the model ladle. Compared with bottom blowing, side blowing that is close to the ladle bottom with more than two plugs increases the average velocity of water, which represents the agitation power, improves the uniformity of water velocity distribution, reduces the stagnant region rate, and shortens the mixing time. The mixing time of dual bottom plugs is almost 1.5 times of that of four side plugs at 116 mm under the same flow rate. The mixing time is not only influenced by the agitation power but also by the uniformity of water velocity distribution. Although the agitation power of four side plugs at 450 mm under the flow rate of 1.8 m3/h is about 1.5 times of that at 116 mm with 0.6 m3/h. The mixing time of the 1.8 m3/h flow rate is about 1.2 times of that of the 0.6 m3/h because of the different water velocity distributions.

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Section: Discussionmentioning

confidence: 66%

Section: Verification For Numerical Modelingmentioning

confidence: 95%

Section: Verification For Numerical Modelingmentioning

confidence: 99%

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Effect of Side Blowing on Fluid Flow and Mixing Phenomenon in Gas-Stirred Ladle

Cheng

Zhang

Yin

et al. 2021

Metals

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“…It is discussed extensively in the next chapter. Some previous experimental studies [28,29] suggest that bubble coagulation and breakup have an influence on the flow. However, the governing mechanisms of coagulation and breakup are not fully understood and still require additional research, especially in liquid metals.…”

Section: Bubblesmentioning

confidence: 94%

Full‐Scale Large Eddy Simulation of a 185 t Ladle Optimizing a Hybrid Eulerian Grid and a Discrete Bubble Mapping Approach

Haas

Schubert

Eickhoff

et al. 2021

steel research int.

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Numerical simulation is a vital tool for the continuous improvement of all steelmaking processes. In previous works, the authors have dedicated different approaches to optimize modeling of fluid flow in the ladle. This includes a sensitivity analysis of validation techniques, assembling of a validation database, and a model optimization on the water model scale. Herein, the final part of this project is presented at which the optimized model is scaled to the real process. Associated problems are identified and solutions are proposed. To achieve a tradeoff between large eddy simulation (LES) grid requirements and current computational capacities, a hybrid meshing strategy is optimized. To overcome the intrinsic drawbacks of the Euler–Lagrange model, a mapping approach for phase decoupling is implemented and made publicly available on GitHub. The upscaling of semi‐empiric submodels is discussed. Good agreement with experimental mixing time measurements is found, indicating the success of upscaling. A first time‐averaged flow field of a full‐scale 185 t ladle with the LES model is presented. Due to the extreme computing requirements, these results may currently be used as a benchmark, but the trend toward increasing computing capacities may make LES models state of the art in the future.

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“…However, various works have been reported in literature with contrasting conclusions, such as the investigations carried out by Krishna Murthy and his colleagues [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] in which the authors conclude that the measurements obtained of the mixing time do not depend on the location neither on the tracer amount released with which the conductivity technique is performed. On the other hand, various authors conclude that not only the location of the sensors 22) affects the mixing time measurements but also the location of the tracer addition [23][24][25] is a variable that considerably affects the time required to reach a homogeneity degree of 95%. The discrepancies between authors have given rise to discussions and communications 26) between authors with reference to the relevance of the influence that a location of the addition of the tracer has on the experimental measurements of mixing time.…”

Section: Introductionmentioning

confidence: 99%

Effect of the Location of Tracer Addition in a Ladle on the Mixing Time through Physical and Numerical Modeling

et al. 2021

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In the present work, the release of tracer location on the global mixing time in an agitated ladle furnace by gas bottom injection was analyzed. Then, a numerical multiphasic steel-slag-argon-air system of a prototype with a capacity of 150 tons was carried out. The simulation was validated by using a physical model with a 1/6 geometric scale using colorant, KCl dispersion measurements techniques and open slag eye opening. Four different tracer addition locations were strategically established to study the influence of tracer releasing location on chemical homogenization. From the results, it was found that the measurement of mixing times varies according to the location of the tracer addition, which to a greater extent is conditioned by the convective currents that at some extent were related to turbulent viscosity.

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Physical study of the impact of injector design on mixing, convection and turbulence in ladle metallurgy

Cited by 14 publications

References 31 publications

Effect of Side Blowing on Fluid Flow and Mixing Phenomenon in Gas-Stirred Ladle

Effect of Side Blowing on Fluid Flow and Mixing Phenomenon in Gas-Stirred Ladle

Full‐Scale Large Eddy Simulation of a 185 t Ladle Optimizing a Hybrid Eulerian Grid and a Discrete Bubble Mapping Approach

Effect of the Location of Tracer Addition in a Ladle on the Mixing Time through Physical and Numerical Modeling

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