Porosity distribution of moving burden layers in the blast furnace throat

Han, Wei; Ding, Weitian; Li, Ying; Nie, Hao; Saxén, Henrik; Long, Hongming; Yu, Yaowei

doi:10.1007/s10035-020-01080-4

Cited by 12 publications

(21 citation statements)

References 37 publications

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“…Therefore, there are more large particles in the center of the furnace. Other researchers [38,49,50] provided a similar explanation after observing this accumulation trend in their DEM results. Yu & Saxén [51] also found this trend in their study of pellet charging, but they reported that the degree of segregation was much less compared to sinter due to the relatively narrow size distribution of pellet particles.…”

Section: • During Layer Build-upsupporting

confidence: 52%

“…Fig. 6), which is densely packed and has a lower permeability than the individual coke and ore layers [49]. Kajiwara et al [58] performed full-scale experiments of charging ore onto a coke layer and observed both the coke push phenomenon and the mixed layer formation.…”

Section: • During Layer Build-upmentioning

confidence: 99%

“…Several researchers [59][60][61][62] have shown experimentally that, depending on the size ratio between particles of the individual layers, this "interface resistance" can have a significant effect on the pressure drop over a stagnant bed. Wei et al [49] used DEM to simulate sinter and coke layer formation using a small-scale setup. They charged three alternating layers of sinter and coke, and studied the effect of segregation and mixed layer formation on the porosity distribution within the entire bed.…”

Section: • During Layer Build-upmentioning

confidence: 99%

See 2 more Smart Citations

Modelling of phenomena affecting blast furnace burden permeability using the Discrete Element Method (DEM) – A review

et al. 2023

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Section: • During Layer Build-upsupporting

confidence: 52%

Section: • During Layer Build-upmentioning

confidence: 99%

Section: • During Layer Build-upmentioning

confidence: 99%

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Modelling of phenomena affecting blast furnace burden permeability using the Discrete Element Method (DEM) – A review

et al. 2023

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“…[ 9 ] Since the shape of lump ore is nonspherical and random, and the difference in shape will affect the charge compliance to a great extent, it is necessary to consider the difference in charge distribution and movement behavior in the shaft furnace due to the shape of the lump ore. Currently, the discrete element method (DEM) has been widely used to study the basic solid flow behavior in iron‐making processes such as blast furnace, [ 10–12 ] smelting processes such as COREX, [ 13–16 ] and direct reduction processes such as MIDREX. [ 7 ] In addition, in a previous study, Yu et al [ 17 ] verified that DEM can predict the flow of irregular and spherical particles.…”

Section: Introductionmentioning

confidence: 99%

Influence of Lump Ore Ratio and Shapes on the Particle Flow Behavior Inside the Direct Reduction Shaft Furnace by Discrete Element Modeling Model

Liao

Zong

et al. 2022

steel research int.

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In recent years, with the attention given to hydrogen reduction‐related technologies, the parameter indicators of direct reduction in the shaft furnace have gained importance. Herein, the numerical simulation of the particle flow field in the shaft furnace is investigated with the help of discrete element method (DEM) model. In contrast to the subregional modeling and the single particle shape study of the previous studies, this study innovatively uses the real shape of the particles and the overall structure of the vertical furnace for modeling. The transient characteristics of solid particle flow under ten lump ore ratios and three shapes are considered. The results show that the mass fraction and the shape of lump ore have little effect on the particle falling speed, but have a significant effect on the particle segregation behavior. In addition, the void ratio responds to the permeability condition in the furnace, which is also influenced by the lump ore proportion and shape.

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“…Widely used in agriculture, military and the chemical industry, TiCl 4 is not only an important intermediate product for the production of titanium dioxide and sponge titanium, but also a solvent for dissolving and synthesizing organic substances such as plastics and resins [1][2][3]. The main methods of producing titanium tetrachloride in industry are molten salt chlorination and boiling chlorination [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Bubble and Velocity Distribution in a Furnace

Ding

Chen

et al. 2022

Metals

Self Cite

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An industrial furnace, such as a blast furnace, molten salt furnace and a basic oxygen furnace, is a popular reactor, where the distribution of liquid, flow pattern of the fluid and the velocity of the fluid determine the energy distribution and chemical reaction in the reactor. Taking a furnace as the research object, this paper studies the effects of different inlet velocities, liquid densities and viscosity on bubble and velocity distribution. A three-dimensional mathematical model of the furnace is set up by a numerical simulation, and the volume-of-fluid (VOF) method is used to study the behavior of bubbles. The accuracy of the simulation parameters selected in the simulation calculation is verified by comparing the simulation with the experimental results. The findings show that an excessive or too small an inlet velocity will lead to an uneven distribution of chlorine in the furnace, therefore, an inlet velocity of about 30 m/s is more appropriate. In addition, changing the liquid density has little effect on the bubble and velocity distribution while choosing the appropriate liquid viscosity can ensure the proper gas holdup and fluidity of chlorine in the furnace.

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Porosity distribution of moving burden layers in the blast furnace throat

Cited by 12 publications

References 37 publications

Modelling of phenomena affecting blast furnace burden permeability using the Discrete Element Method (DEM) – A review

Modelling of phenomena affecting blast furnace burden permeability using the Discrete Element Method (DEM) – A review

Influence of Lump Ore Ratio and Shapes on the Particle Flow Behavior Inside the Direct Reduction Shaft Furnace by Discrete Element Modeling Model

Numerical Simulation of Bubble and Velocity Distribution in a Furnace

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