Simulation on the Melting Process of Iron Oxide Pellet in Slags

He, Yi; Guo, Wenda; Zhang, Wei; Li, Mingming; Zou, Zongshu

doi:10.1007/978-3-319-48764-9_391

Cited by 2 publications

(4 citation statements)

References 6 publications

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“…In their computations, the heat by convection (Qconv) depends on the convective heat transfer coefficient, which in turns depends on the knowledge of the velocity of the liquids. Previous researchers 28,29,32,[34][35][36][37] have applied different approaches in the estimation of the heat transfer coefficients by assuming and simplifying the bath velocity fields. One contribution from this work is a more realistic computation of the local convective heat transfer coefficient in the entire computational domain based on detailed velocity patterns.…”

Section: (10)mentioning

confidence: 99%

“…Previous investigations [27][28][29][30][31][32][33][34][35][36][37] have concluded that the melting time of spherical particles is decreased by increasing the temperature of the particles, increasing the temperature of the molten bath (superheat), decreasing the particle size, increasing the stirring conditions and by increasing the metallization of DRI. The authors previously reported 38) that in order to maximize superheat, the optimum injection position for DRI feeding is in the center of the delta in the EAF.…”

Section: Introductionmentioning

confidence: 99%

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Mathematical Modeling of the Melting Rate of Metallic Particles in the EAF under Multiphase Flow

2015

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The sponge iron or Direct Reduced Iron (DRI) is an important feedstock in the Electric Arc Furnace (EAF). The main sources of iron units for the EAF can be steel scrap, DRI, hot metal and combinations of these materials. The EAF has become a melting reactor and its melting rate plays a key role in furnace productivity. In this work, the melting rate of porous metallic particles is analyzed employing CFD tools, having the computational domain of an industrial size EAF. The molten pool is comprised of two liquid phases, steel and slag. In order to compute the melting rate as a function of particle size and arc length, three sub-models were developed, one computes the instantaneous power delivery as a function of arc voltage and arc length, the second one computes the velocity and temperature fields and finally the third sub-model computes the melting rate. Comparisons of melting rates when the particles are immersed in its own melt and the case where immersion is carried out in the steel/slag system is included in the analysis. A contribution from this work is a more realistic approach to compute the convective heat transfer coefficient using the estimated values of the velocity fields.

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Section: (10)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling of the Melting Rate of Metallic Particles in the EAF under Multiphase Flow

2015

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“…It has been reported that the melting rate increases with DRI of higher metallization, 7,8) lower gangue content, 8) DRI particles of higher density, 9) smaller particle size, 2,[10][11][12][13][14] higher temperature of the solid particles, [10][11][12][13][14] increasing the temperature of liquid steel (higher superheat), [10][11][12][13][14][15] higher stirring conditions 7,[12][13][14]16) and a slag composition with a binary basicity ratio between 0.8 and1.2 17,18).…”

Section: Mathematical Modeling Of the Melting Of Sponge Iron In A Batmentioning

confidence: 99%

“…However, the modeling approach is the same in all of them. Their difference lies in the method used to solve the equation of the second law of Fourier, some researchers have used numerical solutions, 9,10,13,16,18,20,23,24) and others have developed analytical solutions. 10,11,25) Table 1 summarizes the mathematical models on the melting of particles in a metal bath.…”

Section: )mentioning

confidence: 99%