An investigation of the recovery and kinetics during the flotation of residual petroleum coke in lime calcination exhaust tailings


Vaziri Hassas B., Guven O., Hassanzadeh A.

INTERNATIONAL JOURNAL OF COAL PREPARATION AND UTILIZATION, cilt.41, sa.9, ss.617-627, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 41 Sayı: 9
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1080/19392699.2018.1498337
  • Dergi Adı: INTERNATIONAL JOURNAL OF COAL PREPARATION AND UTILIZATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Chemical Abstracts Core, Communication Abstracts, Compendex, Environment Index, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.617-627
  • Anahtar Kelimeler: Reagent optimization, flotation rate constant, flotation kinetic model, petroleum coke, BUBBLE-SIZE, AIR, OPTIMIZATION, ROUGHNESS, PARTICLES
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Flotation is one of the feasible separation methods suggested for recovery of petroleum coke from the tailings of lime calcination furnaces. In this study, analyses of ash content and calorific value of petroleum coke in lime calcination tailings were used to measure its floatability and product quality. In addition, seven most common flotation kinetics models were fitted to the obtained experimental data. Based on the maximum recovery, minimum ash content, and maximum calorific value of the flotation products, optimum dosages for collector (kerosene) and frother (MIBC) were found 30 g/t and 60 g/t, respectively. Regarding the flotation kinetic modeling and the obtained sum of squared errors (SSEs), Agar and Klimpell models were found to have the best and the poorest fits to the experimental data, respectively. Finally, it was concluded that new statistical concepts such as information criteria (IC) and non-linear generalized least squares estimation (NLGLSE) must be applied to the process of model selection owing to consideration of goodness of fit, complexity of a model and model consistency.