Artificial Neural Network Prediction of the Performance of Upflow and Downflow Fluidized Bed Reactors Treating Acidic Mine Drainage Water

Atasoy A., Babar B., Sahinkaya E.

MINE WATER AND THE ENVIRONMENT, cilt.32, sa.3, ss.222-228, 2013 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 3
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1007/s10230-013-0232-x
  • Dergi Adı: MINE WATER AND THE ENVIRONMENT
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.222-228
  • Anahtar Kelimeler: Metal removal, Mine water, Reactor modeling, Sulfate reduction
  • Marmara Üniversitesi Adresli: Hayır

Özet

The performance of fluidized bed reactors treating synthetic acid mine drainage were predicted using an artificial neural network (ANN). The developed model gave satisfactory fits to the experimentally obtained sulfate, COD, alkalinity, and sulfide data; R-values were within 0.92 and 0.98. ANN can be effectively used to predict the performance of these complex systems and, with the proposed model-based applications, it is possible to reduce operational costs and risks. © 2013 Springer-Verlag Berlin Heidelberg.