Employment of different turbulence models to the design of optimum steel flows in a tundish

Employment of different turbulence models to the design of optimum steel flows in a tundish The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a large scale industrial size tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlets of a six strand billet caster tundish. The numerical prediction of the tracer concentration has been made with six different turbulence models (the standard k‐ϵ, the k‐ϵ RNG, the Low Re number Lam‐Bremhorst model, the Chen‐Kim high Re number model (CK), the Chen‐Kim low Re number model (CKL) and the simplest constant effective viscosity model (CEV)) which favorably compares with that of the experimental observation for a single strand bare tundish. It has been found that the overall comparison of the k‐ϵ model, the RNG, the Lam‐Bremhorst and the CK model is much better than the CKL model and the CEV model as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. However, the k‐ϵ model predicts the closest value to the experimental observation compared to all other models. The prediction of the transient behavior of the tracer is best done by the Lam‐Bremhorst model and then by the RNG model, but these models do not predict the gross quantities that accurately like the k‐ϵ model for a single strand bare tundish. With the help of the above six turbulence models mixing parameters such as the ratio of mix to dead volume and the mean residence time were computed for the six strand tundish for different outlet positions, height of advanced pouring box (APB) and shroud immersion depth. It was found that three turbulence models show a peak value in the ratio of mix to dead volume when the outlets were placed at 200 mm away from the wall. An APB was put on the bottom of the tundish surrounding the inlet jet when the outlets were kept at 200 mm away from the wall. It was also found that there exists an optimum height of the APB where the ratio of mix to dead volume and the mean residence time attain further peak values signifying better mixing in the tundish. At this optimum height of the APB, the shroud immersion depth was made to change from 0 to 400 mm. It was also observed that there exists an optimum immersion depth of the shroud where the ratio of mix to dead volume still attains another peak signifying still better mixing. However, all the turbulence models do not predict the same optimum height of the APB and the same shroud immersion depth as the optimum depth. The optimum height of the APB and the shroud immersion depth were decided when two or more turbulence models predict the same values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Numerical Methods for Heat & Fluid Flow Emerald Publishing

Employment of different turbulence models to the design of optimum steel flows in a tundish

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Publisher
Emerald Publishing
Copyright
Copyright © 2004 Emerald Group Publishing Limited. All rights reserved.
ISSN
0961-5539
DOI
10.1108/09615530410544283
Publisher site
See Article on Publisher Site

Abstract

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a large scale industrial size tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlets of a six strand billet caster tundish. The numerical prediction of the tracer concentration has been made with six different turbulence models (the standard k‐ϵ, the k‐ϵ RNG, the Low Re number Lam‐Bremhorst model, the Chen‐Kim high Re number model (CK), the Chen‐Kim low Re number model (CKL) and the simplest constant effective viscosity model (CEV)) which favorably compares with that of the experimental observation for a single strand bare tundish. It has been found that the overall comparison of the k‐ϵ model, the RNG, the Lam‐Bremhorst and the CK model is much better than the CKL model and the CEV model as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. However, the k‐ϵ model predicts the closest value to the experimental observation compared to all other models. The prediction of the transient behavior of the tracer is best done by the Lam‐Bremhorst model and then by the RNG model, but these models do not predict the gross quantities that accurately like the k‐ϵ model for a single strand bare tundish. With the help of the above six turbulence models mixing parameters such as the ratio of mix to dead volume and the mean residence time were computed for the six strand tundish for different outlet positions, height of advanced pouring box (APB) and shroud immersion depth. It was found that three turbulence models show a peak value in the ratio of mix to dead volume when the outlets were placed at 200 mm away from the wall. An APB was put on the bottom of the tundish surrounding the inlet jet when the outlets were kept at 200 mm away from the wall. It was also found that there exists an optimum height of the APB where the ratio of mix to dead volume and the mean residence time attain further peak values signifying better mixing in the tundish. At this optimum height of the APB, the shroud immersion depth was made to change from 0 to 400 mm. It was also observed that there exists an optimum immersion depth of the shroud where the ratio of mix to dead volume still attains another peak signifying still better mixing. However, all the turbulence models do not predict the same optimum height of the APB and the same shroud immersion depth as the optimum depth. The optimum height of the APB and the shroud immersion depth were decided when two or more turbulence models predict the same values.

Journal

International Journal of Numerical Methods for Heat & Fluid FlowEmerald Publishing

Published: Dec 1, 2004

Keywords: Turbulence; Optimization techniques; Modelling

References

  • Computational Methods for Fluid Dynamics
    Ferziger, J.H.; Peric, M.
  • Effect of outlet positions and various turbulence models on mixing in a single and multi‐strand tundish
    Jha, P.K.; Dash, S.K.

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