Biologically Fe<SUP>2+</SUP> oxidizing fluidized bed reactor performance and controlling of Fe<SUP>3+</SUP> recycle during heap bioleaching:: an artificial neural network-based model

Ozkaya B., Sahinkaya E., Nurmi P., Kaksonen A. H., Puhakka J. A.

BIOPROCESS AND BIOSYSTEMS ENGINEERING, cilt.31, sa.2, ss.111-117, 2008 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 31 Sayı: 2
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1007/s00449-007-0153-9
  • Dergi Adı: BIOPROCESS AND BIOSYSTEMS ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.111-117
  • Anahtar Kelimeler: Fe3+ production, precipitate, neural network, back-propagation algorithm, FBR
  • Marmara Üniversitesi Adresli: Hayır

Özet

The performance of a biological Fe2+ oxidizing fluidized bed reactor (FBR) was modeled by a popular neural network-back-propagation algorithm over a period of 220 days at 37°C under different operational conditions. A method is proposed for modeling Fe3+ production in FBR and thereby managing the regeneration of Fe3+ for heap leaching application, based on an artificial neural network-back-propagation algorithm. Depending on output value, relevant control strategies and actions are activated, and Fe 3+ production in FBR was considered as a critical output parameter. The modeling of effluent Fe3+ concentration was very successful, and an excellent match was obtained between the measured and the predicted concentrations. © 2007 Springer-Verlag.