Optimization of some parameters on agglomeration performance of Zonguldak bituminous coal by oil agglomeration

Aslan N., Unal I.

FUEL, cilt.88, sa.3, ss.490-496, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 88 Sayı: 3
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.fuel.2008.10.039
  • Dergi Adı: FUEL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.490-496
  • Anahtar Kelimeler: Oil agglomeration, Coal, RSM, Modeling, Optimization, RESPONSE-SURFACE METHODOLOGY, COMPOSITE ROTATABLE DESIGN, MULTI-GRAVITY SEPARATOR, BOX-BEHNKEN DESIGN, HIGH-RANK COALS, VEGETABLE-OILS, OPERATING VARIABLES, WVO
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

In this study, the optimization of some parameters on agglomeration performance of Zonguldak bituminous coal by oil agglomeration was discussed. A three-level Box-Behnken design combining with a response surface methodology (RSM) and quadratic programming (QP) were employed for modeling and optimization some operations parameters on oil agglomeration performance. The relationship between the responses, Le., grade and recovery, and four process parameters, i.e., amount of oil, agitation time, agitation rate and solid content were presented as empirical model equations for both grade and recovery on oil agglomeration. The model equations were then optimized individually using the quadratic programming method to maximize both for grade and recovery within the experimental range studied. The optimum conditions were found to be 14.61% for amount of oil, 8.94 min for agitation time, 1554 rpm for agitation rate and 5% for solid content to achieve the maximum grade. The maximum model prediction of 0.650 grade at these optimum conditions is higher than any value obtained in the initial tests conducted. Similarly, the conditions for maximum recovery were found to be 20.60% for amount of oil, 5 min for agitation time, 1800 rpm for agitation rate and 19.48% for solid content with a prediction of 96.90% recovery, which is also higher than any other recovery obtained in the initial tests conducted. (C) 2008 Elsevier Ltd. All rights reserved.