Modeling Progress of High-Temperature Melt Multiphase Flow in Continuous Casting Mold

doi:10.11900/0412.1961.2022.00175

Acta Metall Sin

2022, Vol. 58

Issue (10): 1236-1252 DOI: 10.11900/0412.1961.2022.00175

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Modeling Progress of High-Temperature Melt Multiphase Flow in Continuous Casting Mold

LIU Zhongqiu¹^,², LI Baokuan¹(

), XIAO Lijun², GAN Yong²

^1.School of Metallurgy, Northeastern University, Shenyang 110819, China
^2.Central Iron and Steel Research Institute, Beijing 100081, China

Cite this article:

LIU Zhongqiu, LI Baokuan, XIAO Lijun, GAN Yong. Modeling Progress of High-Temperature Melt Multiphase Flow in Continuous Casting Mold. Acta Metall Sin, 2022, 58(10): 1236-1252.

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Abstract

The cleanliness, homogenization, and refinement of the high-quality steel are highly dependent on the high-temperature melt multiphase flow in the continuous casting mold. The high-temperature melt multiphase flow is unsteady-state turbulence that is coupled with heat transfer, mass transfer, phase change, chemical reaction, and electromagnetic effect, forming an extremely complex, unsteady, nonlinear, and nonequilibrium multiphysical fields, where various physical quantities are nearly impossible to on-line measure through on-site testing. With the similarity of flow and solidification processes ensured, both the physical experiment and the numerical simulation of multiscale transport phenomenon have emerged as the prime choices to study the formation mechanism of various defects in continuous casting slabs. However, in various forms, the conventional hydrodynamic problems, such as the high-temperature melt multiphase flow in various metallurgical reactors, is characterized by a considerable change in physical properties, complex constitutive equations, diverse influencing factors of phase interface, and large gradient of physical quantities near the boundary. In addition, in the multiphysical fields inside continuous casting mold, there exists complex and variable multiscale interface phenomena like large-scale interface deformation of the continuous phase, transport of discrete phase particle, and transition between continuous and discrete phase, as well as the multiscale turbulent vortex structure, which poses a great challenge to modeling of high-temperature melt multiphase flow. Compared with the single-phase flow, the multiphase flow is characterized by the topological variation of the phase interface. In this paper, the research progress on modeling the high-temperature melt multiphase flow in the continuous casting mold is discussed from the following four perspectives: the scale distribution of discrete flow interface, cross-scale phenomenon of mixed flow interface, multiscale phenomenon of solidification interface, and role of turbulence in revealing the multiscale phase interface structure. Finally, the potential study direction in the future is considered.

Key words: continuous casting mold high-temperature melt multiphase flow multiscale modeling

Received: 17 April 2022

ZTFLH:

TF777.1

Fund: National Natural Science Foundation of China(51974071);National Natural Science Foundation of China(52171031);China Postdoctoral Science Foundation(2020M680475)

About author: LI Baokuan, professor, Tel: 13840054268, E-mail: libk@smm.neu.edu.cn

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https://www.ams.org.cn/EN/10.11900/0412.1961.2022.00175 OR https://www.ams.org.cn/EN/Y2022/V58/I10/1236

Fig.1 Multiphase, multi-physics, and multi-scale characteristics in the mold (SEN—submerged entry nozzle)

Fig.2 Trajectories of bubbles with different sizes^[25]
(a) 1-1.5 mm (b) 1.5-2 mm (c) 2-2.5 mm (d) > 2.5 mm

Fig.3 Spatial distributions of bubbles and inclusions in actual slab (D_m—bubble size)^[12]

Fig.4 Bubbles cluster and bubbles outside cluster
(a) macro-distribution of bubbles (b) 0 ms (c) 15 ms (d) 30 ms (e) 40 ms

Fig.5 Locations of captured inclusions on solidified shell^[10]
(a) 1.5 s (b) 3.0 s (c) 10 s (d) 30 s (e) 100 s

Fig.6 Locations of exposed slag eyes on the top surface of the mold^[51]
(a) industrial scene (b) numerical prediction (α_g—gas volume fraction)

Fig.7 Comparisons of gas void fraction profiles inside the SEN between experiment (a) and MUltiple SIze Group (MUSIG) model (b) and average bubble number density (ABND) model (c) simulations

Fig.8 Vortex slag entrapment phenomenon observed in water model experiment^[78]
(a) near SEN (b) near the quarter width

Fig.9 Emulsifying phenomenon observed in water model experiment^[51]
(a) top surface of slag layer
(b) wide face of the mold

Fig.10 Vortex slag entrapment phenomenon predicted by numerical simulation^[52]
(a) interface of slag and steel
(b) 20 mm below the slag-steel interface
(c) flow field in the mold

Fig.11 Transient dumbbell coalescence process from a bottom view^[109]
(a) experiment (b) numerical simulation (DPM—discrete phase model, ICM—interface-capturing model)

Fig.12 Evolution of macroscopic solidification structure observed in solidification experiment
(a) device for solidification^[129] (b) without inner cooler^[128] (c) with inner cooler^[128]

Fig.13 Relation between ratio of equiaxed zone and initial temperature of steel strip^[129] (d₀—initial thickness of steel strip, D—diffusion coefficient of solute, $T d 0$ —initial temperature of steel strip, R—equiaxed crystal ratio)

Method	Continuity	Momentum equation	Solvable scale	Model	Computation
	equation				requirement
DNS	$∂ u i ∂ x i = 0$	$∂ u i ∂ t + u j ∂ u i ∂ x j =$	Eddies of all scales	No	Huge
		$- 1 ρ ∂ p ∂ x j + υ ∂ 2 u i ∂ x j ∂ x j + f i$
LES	$∂ u ¯ i ∂ x i = 0$	$∂ u ¯ i ∂ t + u j ∂ u i u j ¯ ∂ x j =$	Eddies of large scales	Subgrid scale model	High
		$- 1 ρ ∂ p ¯ ∂ x j + υ ∂ 2 u ¯ i ∂ x j ∂ x j + f ¯ i$
RANS	$∂ u i ∂ x i = 0$	$∂ u i ∂ t + ∂ u i u j ∂ x j =$	Eddies of average scale	Time-averaged turbulence model	Low
		$- 1 ρ ∂ p ∂ x j + υ ∂ 2 u i ∂ x j ∂ x j + f i$

Table 1 Basic equations and characteristics of the three turbulent numerical methods

Fig.14 Characteristics of molten steel-argon gas two-phase transient flow field in the mold^[50]
Color online
(a) RANS (b) LES
(c) comparison of numerical simulation with experiment (

u ¯

—horizontal average velocity,

v ¯

—vertical average velocity, Q_w—water-carrying capacity, Q_g—gas flow rate, k—turbulent kinetic energy, ε—turbulent dissipation rate, SST—shear stress transport, RSM—Reynolds stress model)

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