Separation density prediction of geldart A dense medium in gas-solid fluidized bed coal beneficiators

Chenyang Zhou, Chengguo Liu, Yue Yuan, Zhijie Fu, Jesse Zhu, Chenlong Duan

Research output: Journal PublicationArticlepeer-review

1 Citation (Scopus)

Abstract

Gas-solid Fluidized Bed Coal Beneficiator (GFBCB) process is a crucial dry coal beneficiation fluidization technology. The work employs the GFBCB process alongside a novel Geldart A dense medium, consisting of Geldart A magnetite particles and Geldart C ultrafine coal, to separate small-size separated objects in the GFBCB. The effects of various operational conditions, including the volume fraction of ultrafine coal, the gas velocity, the separated objects size, and the separation time, were investigated on the GFBCB's separation performance. The results indicated that the probable error for 6∼3 mm separated objects could be controlled within 0.10 g/cm3. Compared to the traditional Geldart B/D dense medium, the Geldart A/A dense medium exhibited better size-dependent separation performance with an overall probable error 0.04∼0.12 g/cm3. Moreover, it achieved a similar separation accuracy to the Geldart B/D dense medium fluidized bed with different external energy for the small-size object beneficiation. The work furthermore validated a separation density prediction model based on theoretical derivation, available for both Geldart B/D dense medium and Geldart A/A dense medium at different operational conditions.

Original languageEnglish
Pages (from-to)251-262
Number of pages12
JournalParticuology
Volume92
DOIs
Publication statusPublished - Sept 2024
Externally publishedYes

Keywords

  • GFBCB
  • Geldart A dense medium
  • Prediction model
  • Separated objects size
  • Separation density

ASJC Scopus subject areas

  • General Chemical Engineering
  • General Materials Science

Fingerprint

Dive into the research topics of 'Separation density prediction of geldart A dense medium in gas-solid fluidized bed coal beneficiators'. Together they form a unique fingerprint.

Cite this