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CFD-Derived Regression Model to Predict Surface Velocity for a Continuous-Casting Round Billet Mold

Guangchao Guo, Jiangshan Zhang

2026enmetallurgycontinuous castingflow velocityCFDregression model

Abstract

Language:

In the continuous casting process, the flow velocity of molten steel at the surface of the mold directly influences the melting of the flux, slag entrainment behavior, and the uniformity of heat transfer. Fast and accurate prediction of the magnitude and distribution of surface-flow velocity is crucial for defect suppression and ensuring continuous casting quality. In this study, a three-dimensional electromagnetic–fluid dynamic coupled model was established and validated to simulate the molten steel flow behavior under various casting speeds, Electromagnetic Stirring (EMS) currents, EMS frequencies, and Submerged Entry Nozzle (SEN) immersion depth. Subsequent predictive formulas for maximum surface velocity and high-velocity range were derived under varying process parameters. The CFD-derived regression model predicts key surface-flow characteristics within milliseconds with satisfying accuracy.

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Cite This Work

@article{e6d0280b-774e-4160-b552-dd1ddb47b369,
  title={CFD-Derived Regression Model to Predict Surface Velocity for a Continuous-Casting Round Billet Mold},
  author={Guangchao Guo and Jiangshan Zhang},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - CFD-Derived Regression Model to Predict Surface Velocity for a Continuous-Casting Round Billet Mold
AU  - Guangchao Guo
AU  - Jiangshan Zhang
PY  - 2026
LA  - en
ER  -

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