Prediction Model for Degree of Solid-shell Unevenness during Initial Solidification in the Mold

Kwon, SangJoo; Won, Young-Mok; Back, Gu Seul; Kim, Hyeju; Lee, Jae Sang; Kim, Dong-Gyu; Heo, Yoon Uk; Yim, Chang Hee

doi:10.2355/isijinternational.isijint-2021-155

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…The uneven temperature distribution of the molten steel in the mould may lead to stress concentration in the billet and increase the surface and subcutaneous cracks of the billet. [ 18 ]…”

Section: Resultsmentioning

confidence: 99%

“…The uneven temperature distribution of the molten steel in the mould may lead to stress concentration in the billet and increase the surface and subcutaneous cracks of the billet. [18] Figure 8 shows solidification contours and streamlines on the Y ¼ 0 m plane, where the liquid fraction ranges from 0 to 1, with 0 and 1 representing fully solidified and fully molten steel, respectively. To determine the thickness of the solidified shell at the mould wall, it was assumed that the mushy region with a liquid fraction of less than 0.3 was fully solidified (assuming that the mushy region containing 70% solids was strong enough to withstand the load).…”

Section: Effect Of Nozzle Position On Heat Transfer and Solidificationmentioning

confidence: 99%

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Effect of Nozzle Position on Fluid Flow and Solidification in a Billet Curved Mould using Mould Electromagnetic Stirring

Wang

Qiu

Zhu

et al. 2023

steel research int.

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Owing to the smaller cross-sectional size of the billet, the effect of the position of the submerged entry nozzle (SEN) on the fluid flow in a curved mold is more prominent. The transient fluid flow, heat transfer, and solidification behavior at different nozzle positions and mold electromagnetic stirring (M-EMS) are investigated using a 3D transient mathematical model. The symmetry index, S, is introduced to quantitatively evaluate the symmetry of the flow field. When the SEN is offset to the outer curve, S is the highest, the flow field mixing is the best, and the liquid level fluctuation is minimal. When the SEN is offset to the inner curve, S is the lowest, and the washing of the solidified shell on the inner curve side is more significant, causing the solidified shell thickness on the inner curve to be thinner, which can easily cause steel breakout accidents. The M-EMS can improve the uneven flow field caused by the nozzle position. In actual production, the SEN can be appropriately offset to the outer curve, and the application of M-EMS can improve the flow field distribution of molten steel.

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“…The uneven temperature distribution of the molten steel in the mould may lead to stress concentration in the billet and increase the surface and subcutaneous cracks of the billet. [ 18 ]…”

Section: Resultsmentioning

confidence: 99%

Section: Effect Of Nozzle Position On Heat Transfer and Solidificationmentioning

confidence: 99%

Effect of Nozzle Position on Fluid Flow and Solidification in a Billet Curved Mould using Mould Electromagnetic Stirring

Wang

Qiu

Zhu

et al. 2023

steel research int.

View full text Add to dashboard Cite

show abstract

“…As can be seen, heat exchange inside mould plays a significant role in the entire process; moreover, the majority of flaws on the casted material, such fractures and pinholes, are created here and are related to uneven heat extraction (see ref. [12]). It should be pointed out that uneven heat extraction results in irregular shell thickness growth for all casted sections: these phenomena are not predictable with a standard 3D FEM model, in which skin growth is kept as an average value.…”

Section: Numerical Modeling Of the Continuous Casting Processmentioning

confidence: 99%

Effectiveness of Travelling Slice Modeling in Representing the Continuous Casting Process of Large Product Sections

Bazzaro,

De Bona

2023

Metals

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It is critical in the metal continuous casting process to estimate the temperature evolution of the casted section along the machine from the meniscus (the point where liquid metal is poured) to the cutting machine, where the product is cut to commercial length. A convenient approximated model to achieve this goal with a feasible computational effort, particularly in the case of large sections, is the so-called travelling slice: the transversal section of casted product is subjected to different thermal boundary conditions (e.g., thermal flux, radiation, convection) that are found during the movement at constant speed from meniscus to the end of machine. In this work, the results obtained with the approximated travelling slice model are analyzed in the favorable case of an axisymmetric section. In this case, the reference model is 2D, whereas the travelling slice model degenerates in a simple 1D model. Three different casted shapes were investigated, rounds with diameters of 200 mm, 850 mm, and 1200 mm, spanning from traditional to only recently adopted product diameter sizes. To properly test the validity of the travelling slice model, other casting speeds were considered, even outside the industrial range. Results demonstrate the advantage of using the travelling slice, particularly the much lower computational cost without sacrificing precision, even at low casting speed and large dimensions.

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Characterizing and Controlling Abnormal Periodic Mold Level Fluctuations in a Commercial Slab Continuous Caster Using Big Data

Meng,

Luo,

et al. 2024

Metall Mater Trans B

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Prediction Model for Degree of Solid-shell Unevenness during Initial Solidification in the Mold

Cited by 6 publications

References 36 publications

Effect of Nozzle Position on Fluid Flow and Solidification in a Billet Curved Mould using Mould Electromagnetic Stirring

Effect of Nozzle Position on Fluid Flow and Solidification in a Billet Curved Mould using Mould Electromagnetic Stirring

Effectiveness of Travelling Slice Modeling in Representing the Continuous Casting Process of Large Product Sections

Characterizing and Controlling Abnormal Periodic Mold Level Fluctuations in a Commercial Slab Continuous Caster Using Big Data

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