Dynamic modeling of fine coal separations in a hindered-bed classifier

R. Q. Honaker, K. Mondal

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


Hindered-bed classifiers have recently received significant attention for the potential of achieving effective density-based separations. Although the fundamental principles of hindered-bed classifiers are relatively simple, the complex interactions between the operating parameters provide a degree of difficulty that hinders the ability for on-line plant optimization. Thus, a dynamic population balance model was developed to evaluate and optimize the separation performance achievable on the basis of density by a hindered-bed classifier for the cleaning of fine coal. The steady-state results of the model include partition curves as a function of particle size and density as well as metallurgical data. A statistical comparison of the simulation results with those obtained from industrial units reveal a high level of accuracy with adjusted R2 values greater than 0.95. Simulation results indicate the potential for efficient density-based separations over a particle size range of 3:1.

Original languageEnglish
Pages (from-to)211-232
Number of pages22
JournalCoal Preparation
Issue number2
StatePublished - 2000

ASJC Scopus subject areas

  • Fuel Technology
  • Geotechnical Engineering and Engineering Geology


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