Flow of bubbles through nozzles

Kuo, J.T.; Wallis, G.B.

doi:10.1016/0301-9322(88)90057-2

Cited by 98 publications

(42 citation statements)

References 8 publications

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“…37) Computational modeling using the drag coefficient in molten steel and argon gas system showed reasonable agreement with measurements. 38 (20) is mass flow rate of injected argon gas bubble and Δt is time step of bubble trajectory calculation.…”

Section: Lagrangian Dpm Model For Argon Gasmentioning

confidence: 62%

Transient Fluid Flow during Steady Continuous Casting of Steel Slabs: Part I. Measurements and Modeling of Two-phase Flow

2014

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Unstable mold flow could induce surface velocity and level fluctuations, and entrain slag, leading to surface defects during continuous casting of steel. Both argon gas injection and Electro-Magnetic Braking (EMBr) greatly affect transient mold flow and stability. Part I of this two-part article investigates transient flow of steel and argon in the nozzle and mold during nominally steady-state casting using both plant measurements and computational modeling. Nail board dipping measurements are employed to quantify transient surface level, surface velocity, flow direction, and slag depth. Transient flow in the nozzle and strand is modeled using Large Eddy Simulation (LES) coupled with the Lagrangian Discrete Phase Model (DPM) for argon gas injection. The surface level of the molten steel fluctuates due to sloshing and shows greater fluctuations near the nozzle. The slag level fluctuates with time according to the lifting force of the molten steel motion below. Surface flow shows a classic double roll pattern with transient cross-flow between the Inside Radius (IR) and the Outside Radius (OR), and varies with fluctuations up to ~50% of the average velocity magnitude. The LES results suggest that these transient phenomena at the surface are induced by up-and-down jet wobbling caused by transient swirl in the slide-gate nozzle. The jet wobbling influences transient argon gas distribution and the location of jet impingement on the Narrow Face (NF), resulting in variations of surface level and velocity. A power-spectrum analysis of the predicted jet velocity revealed strong peaks at several characteristic frequencies from 0.5-2 Hz (0.5-2 sec).

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Section: Lagrangian Dpm Model For Argon Gasmentioning

confidence: 62%

Transient Fluid Flow during Steady Continuous Casting of Steel Slabs: Part I. Measurements and Modeling of Two-phase Flow

2014

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“…The parameter d B is the bubble diameter, which is expressed as reported in 23. The drag coefficient C D for distorted bubbles can be expressed by the reported correlation suggested by Kuo and Wallis 30…”

Section: Model Descriptionmentioning

confidence: 97%

An in‐Depth Model‐Based Analysis of Decarburization in the AOD Process

Andersson

Tilliander

Jonsson

et al. 2012

steel research int.

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A previously reported flow and reaction model for an argon‐oxygen decarburization converter was extended to also include a thermodynamic description. An in‐depth study of the model results has been conducted to answer how concentrations of elements and species in the converter at different locations change with time. This may contribute to the understanding of the mechanisms of the refining procedure in the argon‐oxygen decarburization process. The refining procedure includes several step‐wise changes of an injected gas composition to higher and higher inert gas ratio, called step changes. A step change leads to a decreased partial pressure of carbon monoxide and maintains the decarburization at a higher efficiency. The results shows early and late concentration profiles for the first injection step and suggests a way to determine when a step change should be made. Moreover, the step change could be determined by calculating the carbon concentration profiles and deciding when the carbon concentration gradients start to diminish.

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“…There are extensive works on the drag coefficient in the literature. The ''Dirty water'': model of Kuo and Wallis [17] is employed here. In this model …”

Section: Auxiliary Equationsmentioning

confidence: 99%