Study of the stell/slag interface instability and the influence of injected gas in the continuous casting of steel
Kountouriotis, Z., Pericleous, K., Djambazov, G., Domgin, J.F. and Gardin, P. (2012) Study of the stell/slag interface instability and the influence of injected gas in the continuous casting of steel. In: Proceedings of the 8th international conference on CFD in the oil & gas, metallurgical and process industries. E SINTEF research reports . SINTEF, Norway. ISBN 9788214052626Full text not available from this repository.
Main objective of this work is the development of a time-dependent Finite Volume (FV) numerical model to analyse the hydrodynamic behaviour of the steel/slag interface in the Continuous Casting (CC) of steel. The Eulerian representation of the flowfield in the mould region, driven by the Submerged Entry Nozzle (SEN) jets supplying the steel, is accompanied by a Lagrangian representation of gas bubble tracks. Coupling of the gas and liquid fields modifies the flow and consequently interface stability. Due to the cost and risk involved in actual casting measurements, the numerical model has been validated against water-model experiments, using Laser Doppler Anemometry (LDA) technology to obtain time-dependent velocity data and video to capture the interface dynamics. In the experiment, silicon oil mimics the protective slag layer; water the liquid steel and air injected through the SEN imitates the argon gas used in an actual caster. LDA measurements - taken over 600s real time - identify low frequency oscillations in the flow. To uncover the source of these oscillations and reproduce the same information in the model, long transient 3D simulations are necessary. Standard Volume of Fluid (VOF) techniques (Donor-Acceptor, Van Leer, Level-Set-Methods) are normally used to analyse interface motion. However, since these are in general explicit, very small time steps are needed, leading to extremely long computations. In this study, interface motion is modelled using an implicit Counter Diffusion Method (CDM) formulation (Pericleous et al. 2008) reducing computational time by an order of magnitude. Qualitative comparison of the results against water model visualizations explains several observed phenomena and highlights the effects of different process parameters (casting speed, gas flowrate, oil layer thickness). Quantitative comparison is against LDA data for the mean value and standard deviation of the horizontal velocity component and its frequency spectrum. The study suggests that the observed frequencies are related to the turnover time of the two main recirculation loops that appear in the CC mould following the collision of the SEN jets and the narrow faces of the mould.
With the inclusion of heat transfer and solidification, the numerical model addresses the full three-phase problem of a real caster. In particular, the model investigates the influence of argon buoyancy on the steel flow pattern in an industrial configuration. The predicted results compare favourably with available measurements, where the flowfield shows a change in the overall steel velocity pattern from a single roll to a double roll as the relative amount of gas increases. The model in addition predicts the solidified skin thickness and heat distribution across the slag layer as a function of casting parameters.
|Item Type:||Conference Proceedings|
|Title of Proceedings:||Proceedings of the 8th international conference on CFD in the oil & gas, metallurgical and process industries|
|Additional Information:|| Paper appears in this report, which is the proceedings of 8th International Conference on CFD in Oil & Gas, Metallurgical and Process Industries hosted by SINTEF and NTNU (Norwegian University of Science & Technology) in Trondheim, 21-23 June 2011.|
|Uncontrolled Keywords:||continuous casting, bubble tracking, moving interface techniques, multi-phase flow, process metallurgy|
|Subjects:||Q Science > QA Mathematics
T Technology > T Technology (General)
|Pre-2014 Departments:||School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
|Last Modified:||14 Oct 2016 09:17|
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