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Optimization of Cooling Process of Iron Ore Pellets Based on Mathematical Model and Data Mining

  • Metallurgy and Metal Working
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Abstract

Cooling process of iron ore pellets in a circular cooler has great impacts on the pellet quality and systematic energy exploitation. However, multi-variables and non-visualization of this gray system is unfavorable to efficient production. Thus, the cooling process of iron ore pellets was optimized using mathematical model and data mining techniques. A mathematical model was established and validated by steady-state production data, and the results show that the calculated values coincide very well with the measured values. Based on the proposed model, effects of important process parameters on gas-pellet temperature profiles within the circular cooler were analyzed to better understand the entire cooling process. Two data mining techniques—Association Rules Induction and Clustering were also applied on the steady-state production data to obtain expertise operating rules and optimized targets. Finally, an optimized control strategy for the circular cooler was proposed and an operation guidance system was developed. The system could realize the visualization of thermal process at steady state and provide operation guidance to optimize the circular cooler.

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Abbreviations

A :

Gas/pellet apparent contact area, m2/m3

C g :

Heat capacity of gas, kJ/(kg•K)

C p :

Heat capacity of pellet, kJ/(kg•K)

C O2 :

Oxygen concentration in gas phase, kg/m3

C e O2 :

Equilibrium oxygen concentration needed for reaction, kg/m3

d p :

Pellet diameter, m

D O2 :

Diffusivity of oxygen within pellet, m2/s

G :

Superfcial gas fow rate, kg/(m2•s)

h eff :

Effective heat transfer coeffcient, J/(m2•s•K)

k g :

Thermal conductivity of gas, J/(m•s•K)

k′m:

First order oxidation rate of magnetite, m/s

k O2 :

Mass transfer coeffcient in oxygen gas, m/s

Nu :

Nusselt number

Pr :

Prandtl number

r m :

Radius of unreacted magnetite core, m

r p :

Radius of single pellet, m

Re p :

Reynoldʹs number of pellet

R m :

Rate of oxidation of magnetite, kg/(m ∙s)

t :

Moving time of pellets, s

T g :

Gas temperature, K

T p :

Pellet temperature, K

z :

Bed height, m

σ:

Standard deviation

λ:

Fraction of heat from oxidation

∆Hm:

Enthalpy of oxidation, kJ/kg

ρb:

Bulk density of pellet bed, kg/m3

ρm:

Density of magnetite, kg/m3

εb:

Void fraction of pellet bed

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Authors and Affiliations

  1. School of Minerals Processing and Bioengineering, Central South University, 410083, Changsha, Hunan, China

    Gui-ming Yang (Doctor Candidate), Xiao-hui Fan (Professor), Xu-ling Chen, Xiao-xian Huang & Xi Li

Authors
  1. Gui-ming Yang
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  2. Xiao-hui Fan
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  3. Xu-ling Chen
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  4. Xiao-xian Huang
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  5. Xi Li
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Corresponding authors

Correspondence to Gui-ming Yang or Xiao-hui Fan.

Additional information

Foundation Item: Item Sponsored by National Natural Science Foundation of China (51174253)

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Yang, Gm., Fan, Xh., Chen, Xl. et al. Optimization of Cooling Process of Iron Ore Pellets Based on Mathematical Model and Data Mining. J. Iron Steel Res. Int. 22, 1002–1008 (2015). https://doi.org/10.1016/S1006-706X(15)30103-5

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  • DOI: https://doi.org/10.1016/S1006-706X(15)30103-5

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