Iron Ore Granulation Model Supposing the Granulation Probability Estimated from Both Properties of the Ores and Their Size Distributions.

Sakamoto, Noboru

doi:10.2355/isijinternational.42.834

Cited by 17 publications

(10 citation statements)

References 5 publications

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“…8) Disk pelletizer and high speed mixer are effective pretreatment equipment to improve the granulation property of fine particles. Regarding the granulation behavior, various researches were reported so far such as matrix analysis, 9) theoretical analysis of optimum operating conditions, 10) DEM (discrete element method) 11) and so on. In terms of high speed mixer, Matsumura and Kawaguchi 12) introduced the concept of limiting moisture which is necessary for adhering fine powder.…”

Section: Influence Of Agitating Conditions On Agglomeration and Collamentioning

confidence: 99%

“…Time dependence of size distribution was analyzed using matrix model. 9) Assuming that the collapse/granulation system follows a simple Markov process, the particle size distribution vector, G N , during mixing is expressed by Eq. 5:…”

Section: Evaluation Of Agglomeration and Collapse Process By Populatimentioning

confidence: 99%

“…The matrix B is expressed by the sum of B G and B D as shown in Eq. (9). The coefficients of B G matrix mean the degree of residual to the same grain size, and degree of migration of adhered powder from finer grain components.…”

Section: Evaluation Of Agglomeration and Collapse Process By Populatimentioning

confidence: 99%

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Influence of Agitating Conditions on Agglomeration and Collapse of Iron Ore Mixture

Higuchi¹,

Takehara²,

Hirosawa³

et al. 2018

ISIJ Int.

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The influence of agitating conditions on agglomeration and collapse of wet iron ore mixture was investigated in the view of kinetics and matrix model analysis. At the initial stage of mixing behavior, it was found that average particle size was dependent on the mixing rate constant defined as the deviation degree of particle size and water distribution from initial state. Mixing rate constants of powder and water were almost consistent with each other and expressed by power function of Froude number of impeller. It was presumed that the water and fine particle moved together as wet granules during mixing at a given water level. According to the analysis of entire mixing behavior based on matrix model, it was found that the collapse indexes defined by matrix parameters increased as particle size and impact force increased. Minimum particle size at initial mixing state decreased as collapse index increased and the size of long term mixing state was expected by intrinsic increasing rates defined by maximum eigenvalue of matrix parameters.

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Section: Influence Of Agitating Conditions On Agglomeration and Collamentioning

confidence: 99%

Section: Evaluation Of Agglomeration and Collapse Process By Populatimentioning

confidence: 99%

See 1 more Smart Citation

Influence of Agitating Conditions on Agglomeration and Collapse of Iron Ore Mixture

Higuchi¹,

Takehara²,

Hirosawa³

et al. 2018

ISIJ Int.

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“…In order to properly control the granulation process, it is necessary to understand the motion of the materials in the mixer/granulator. Several studies have performed so far to predict granulation growth rate theoretically [1][2][3][4] and experimentally. [5][6][7][8] In addition, the effects of rotational speed and particles charge ratio on the movement of particles have been investigated theoretically.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Granules Behavior in Continuous Drum Mixer by DEM

et al. 2009

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Fig. 1. Principle of the simulation model. model for granulation should be discussed. There are two models for the simulation of granulation process. One is trace movement of all particles. The other is trace movement of granulated particle only as one particle. The former might be better to analyze granulation mechanism. However, it is not realistic to simulate them because particles traced are enormous and it would take a long time to simulate the behavior of granules. Therefore the latter is adopted in this work. The assumptions in this simulation model are follows; 1) Granules are treated as one particle. 2) Particle shape is sphere. 3) Particle diameter is uniformly. 4) Particle diameter and other parameter is fixed in the simulation. 5) Effect of moisture is ignored.Physical constants and simulation conditions are shown in Table 1. Figure 2 shows the schematic diagram of a continuous drum mixer used in the simulation. Table 2 lists the size of drum mixer. Drum length and gradient angle were changed to investigate their effects on the granule behavior. The granules are fed at the extreme right of the drum mixer and granules drop from the extreme left (Fig. 2). Feeding rate is fixed at 100 kg/min. Continuous Drum Mixer Determination of ParametersThe simulation parameters are needed to be determined so that the granules behavior simulated correspond to the experimental results. Particularly the frictional coefficient has to be determined carefully since it strongly affects granules behavior. The simulation of granules behavior was performed to investigate the frictional coefficient on the behavior. The snapshots are shown in Fig. 3. The granules behavior is influenced by the frictional coefficient and a rising angle increases with an increase in the frictional coefficient. The rising angle was defined as shown in Fig. 4(a) to evaluate the granule behavior and to compare to experimental results. Figure 4 (b) shows relationship between the friction coefficient used in the simulation and the rising angle. The rising angle obtained from the experiment was also shown in Fig. 3. The rising angle increases with an increase in the ISIJ International, Vol. 49 (2009) frictional coefficient until the coefficient is 0.5, and then, the rising angle is going to be constant value about 100 degrees. The frictional coefficient was determined as 0.7, at which the rising angle obtained from the simulation is the closest to experimental one, although the rising angle obtained from the simulation does not agree with experimental results completely. This difference between them could be due to the assumption of sphere in the granules. The reason of this difference will be investigated more detail in the future. ExperimentGranulation experiment has been performed by using the continuous dram mixer. Granulator consists of rotating drum mixer, water nozzle and feed hopper (Fig. 5). The raw materials used in the actual process are supplied continuously at the extreme right of the drum mixer. Water is sprinkled by a nozzle, and ...

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“…Among them, we have focused on the third factor and discussed in this paper. Several researches have performed so far to predict granulation size of iron ores and its distribution and granulation growth rate theoretically [1][2][3][4] and experimentally. [5][6][7][8] In addition, the effects of rotational speed and particles charge ratio on the movement of particles have been investigated theoretically.…”

Section: Introductionmentioning

confidence: 99%