Model Study on the Entrapment of Mold Powder into Molten Steel.

Iguchi, Manabu; Yoshida, Jin; Shimizu, Tomoyuki; Mizuno, Yuzo

doi:10.2355/isijinternational.40.685

Cited by 105 publications

(87 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lamant et al [9] showed that the high shear flows at the meniscus associated with the influx of mold powders may lead to product cracking. Iguchi et al [10] found in their experiments that the Kelvin-Helmholtz instability induced by high flow rates at the meniscus can lead to powder entrapment. These results established that high meniscus velocities should be avoided.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Flow Oscillations and Meniscus Fluctuations in a Funnel-Type Water Mold Model

Jeon

Sung

Lee

2009

Metall Mater Trans B

View full text Add to dashboard Cite

Transient flows in a funnel-type continuous casting process model were studied experimentally to investigate the flow oscillations inside the mold and the meniscus fluctuations. A full-scale water model was used with dimensions of 2000 mm (length) 9 1350 mm (width) 9 100 mm (thickness). Particle image velocimetry (PIV) was employed to measure the flow oscillations. To minimize high shear flow errors near the submerged entry nozzle (SEN) exit, the window deformation technique was adopted. The meniscus levels were extracted by edge-detection image processing. Three types of SEN and two funnel thicknesses (180 mm and 220 mm) were tested to examine the flow characteristics under five flow rates (10,20, 30, 40, and 50 m 3 /h). The vortex generation mechanism inside the mold was analyzed across the various mold conditions studied.

show abstract

Section: Introductionmentioning

confidence: 99%

“…The meniscus levels were extracted by edge-detection image processing. Three types of SEN and two funnel thicknesses (180 mm and 220 mm) were tested to examine the flow characteristics under five flow rates (10,20, 30, 40, and 50 m 3 /h). The vortex generation mechanism inside the mold was analyzed across the various mold conditions studied.…”

mentioning

confidence: 99%

Flow Oscillations and Meniscus Fluctuations in a Funnel-Type Water Mold Model

Jeon

Sung

Lee

2009

Metall Mater Trans B

View full text Add to dashboard Cite

show abstract

“…They found that the above equation is valid for lowviscosity and low-frequency disturbances where surface tension is not important or can be neglected (Iguchi et al, 2000).…”

mentioning

confidence: 99%

Numerical and physical modelling of tundish slag entrainment in the steelmaking process

Mabentsela

Akdogan

Bradshaw

2017

J. South. Afr. Inst. Min. Metall.

View full text Add to dashboard Cite

The tundish serves as the last metallurgical vessel through which steel passes before solidifying in the moulds. It is in the tundish that the last traces of non-metallic inclusions should be removed, otherwise the inclusions carry over to the moulds and cause defects in the steel product. In the tundish, the slag is less dense than the melt and thus resides on the top of the melt. The slag provides a sink into which the non-metallic inclusions float to and dissolve. The slag also protects the melt from air and heat loss. However, when slag is entrained in the melt as a result of increased turbulence or shearing at the steel-slag interface, slag can become a source of nonmetallic inclusions.Numerous studies on flow patterns in the tundish have been carried out since the introduction of the tundish. These studies were aimed at improving the flow characteristics in the tundish (Chattopadhyay, Isac, and Guthri, 2010;Cloete, 2014;Jha, Dash, and Kumar, 2001;Jha, Rao, and Dewan, 2008;Kumar, Koria, and Mazumdar, 2007;Kumar, Mazumdar, and Koria, 2008;Mazumdar and Guthri, 1999;Sahai and Emi, 1996;Sahai and Burval, 1992; Tripathi and Ajmani, 2011). These studies have led to the use of flow control devices (FCDs) to increase the melt residence time in the tundish and provide surface-directed flow so as to assist with inclusion removal. FCDs include dams, weirs, baffles, and turbulence inhibitors. It is now generally understood that any tundish without a FCD suffers from poor inclusion removal as a result of too short a melt residence time in the tundish (Mazumdar and Guthri, 1999).Due to the opaqueness of the steel melt and the elevated operating temperature (1600°C) in the tundish, the abovementioned studies were carried out using a combination of physical models, otherwise known as 'cold models', and numerical models. Physical models involve the use of reduced-scale water models where water is used to represent the steel melt. Numerical models involve using computational fluid dynamics packages to model the melt flow in the tundish. When used together, the physical model can be used to verify numerical model results. Once verified, the numerical model can then be adapted without the need of a physical model. This significantly reduces the costs of exploring new designs and also saves time.The flow behaviour studies that have led to the use of FCDs were done using both physical and numerical models. In most of these studies, the researchers were only concerned with the melt phase, i.e. how the FCD affects the melt residence time. Most researchers opted to use only water in their physical and numerical models (Chattopadhyay, Isac, and Guthri, 2010;Cloete, 2014; Numerical and physical modelling of tundish slag entrainment in the steelmaking process by A. Mabentsela*, G. Akdogan*, and S. Bradshaw* Physical and numerical modelling methods were followed to identify mechanism(s) for tundish slag entrainment in a bare tundish and one with a flow control device (FCD).The physical and numerical models made use of water and paraffi...

show abstract

“…It is usually employed in secondary metallurgy processes and continuous casting to achieve a homogeneous distribution of temperature and composition, and to eliminate second phases and dissolved impurities. [1][2][3][4] Earlier studies on the water model reported particle removal using gas bubble flotation. [5][6][7][8][9][10] To analyze phenomena associated with the agitation of liquid baths, the determination of the mixing time is very important.…”

Section: Introductionmentioning

confidence: 99%

Determination of Mixing Time in a Ladle-Refining Process Using Optical Image Processing

Kuo

2011

ISIJ Int.

View full text Add to dashboard Cite

Water model experiments were performed to measure the mixing time and to investigate the effect of nozzle depth in a ladle-refining process. The depth of the submergence nozzle was varied by 6.0, 7.2, and 8.4 cm, which correspond to fractional depths of 0.5, 0.6, and 0.7, respectively. A new technique was proposed in the present study to measure the mixing time using optical image processing. The mixing time for fractional depths of 0.5, 0.6, and 0.7 determined is 26, 19, and 20 sec, respectively. The gas dispersions in the plume zone are distributed asymmetrically. An increase in the nozzle depth, which enhances recirculation speeds, leads to a decrease in mixing time.

show abstract

Model Study on the Entrapment of Mold Powder into Molten Steel.

Cited by 105 publications

References 9 publications

Flow Oscillations and Meniscus Fluctuations in a Funnel-Type Water Mold Model

Flow Oscillations and Meniscus Fluctuations in a Funnel-Type Water Mold Model

Numerical and physical modelling of tundish slag entrainment in the steelmaking process

Determination of Mixing Time in a Ladle-Refining Process Using Optical Image Processing

Contact Info

Product

Resources

About