Determining the heat and mass transfer patterns in the tundish of a continuous casting machine
DOI:
https://doi.org/10.15587/1729-4061.2025.336057Keywords:
tundish, continuous casting of billets, liner, CFD modeling, SHAP analysis, machine learningAbstract
This study’s object is the thermal state of the tundish ladle in a continuous billet casting machine, aimed at prolonging the duration of the series of melts.
This paper reports the numerical modeling of the heat and mass transfer processes in the tundish ladle of a continuous billet casting machine (CCM). The model takes into account the hydrodynamics of liquid steel, as well as the temperature distribution in the multilayer lining and the ladle casing; it also makes it possible to predict local wear of the lining based on the analysis of the technological parameters of the process and the chemical composition of steel. Special attention is paid to the study of the temperature and turbulent characteristics of the flow, the residence time of the steel in the ladle, and the influence of its composition on the intensity of destruction of the lining layers.
The results make it possible to localize critical areas of thermal and mechanical overload of the ladle lining, in particular the contact zones of the liquid steel jet and the wall areas near the turbos tops, where the following are recorded: shear stress up to 275 Pa; turbulent kinetic energy over 0.14 m2/s2; and metal temperature up to 1830 K.
The local wear map built shows the distribution of the lining erosion rate within 2.4–4.3 mm/h depending on the hydrodynamic and chemical conditions. The predictive model combines CFD parameters, the chemical composition of steel, and the pouring speed, which showed high accuracy confirmed by the coefficient of determination R2 = 0.99937.
A feature of the result is the comprehensive combination of local flow conditions and steel composition with the erosion model, which has made it possible to give engineering-based recommendations for optimizing the ladle operating modes.
The developed predictive model of liner wear rate could be used to monitor its condition, improve ladle operating modes, and increase the reliability of the continuous casting process
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