The increase of the performance of ultrafine coal flotation by using emulsified kerosene and the prediction of the flotation parameters by random forest and genetic algorithm

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ÖNEY Ö.

Archives of Mining Sciences, cilt.64, sa.1, ss.119-130, 2019 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 64 Sayı: 1
  • Basım Tarihi: 2019
  • Doi Numarası: 10.24425/ams.2019.126275
  • Dergi Adı: Archives of Mining Sciences
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.119-130
  • Anahtar Kelimeler: Emulsified kerosene, Genetic algorithm, Random forest, Ultrafine coal flotation
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Uşak Üniversitesi Adresli: Evet

Özet

In this study, emulsified kerosene was investigated to improve the flotation performance of ultrafine coal. For this purpose, NP-10 surfactant was used to form the emulsified kerosene. Results showed that the emulsified kerosene increased the recovery of ultrafine coal compared to kerosene. This study also revealed the effect of independent variables (emulsified collector dosage (ECD), frother dosage (FD) and impeller speed (IS)) on the responses (concentrate yield (C %), concentrate ash content (%) and combustible matter recovery (e %)) based on Random Forest (RF) model and Genetic Algorithm (GA). The proposed models for C %,% and e% showed satisfactory results with R2. The optimal values of three test variables were computed as ECD = 330.39 g/t, FD = 75.50 g/t and IS = 1644 rpm by using GA. Responses at these experimental optimal conditions were C % = 58.51%, % = 21.7% and e % = 82.83%. The results indicated that GA was a beneficial method to obtain the best values of the operating parameters. According to results obtained from optimal flotation conditions, kerosene consumption was reduced at the rate of about 20% with using the emulsified kerosene.