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Biologically Fe2+ oxidizing fluidized bed reactor performance and controlling of Fe3+ recycle during heap bioleaching: an artificial neural network-based model

Bestamin Ozkaya, Erkan Sahinkaya

2007enbioleachingneural networkFe3+ productionfluidized bedbioprocess

Abstract

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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 Fe3+ 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.

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Cite This Work

@article{012a57b9-9aae-478b-ae5b-d56a00c40cff,
  title={Biologically Fe2+ oxidizing fluidized bed reactor performance and controlling of Fe3+ recycle during heap bioleaching: an artificial neural network-based model},
  author={Bestamin Ozkaya and Erkan Sahinkaya},
  year={2007},
  language={en}
}
TY  - JOUR
TI  - Biologically Fe2+ oxidizing fluidized bed reactor performance and controlling of Fe3+ recycle during heap bioleaching: an artificial neural network-based model
AU  - Bestamin Ozkaya
AU  - Erkan Sahinkaya
PY  - 2007
LA  - en
ER  -

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