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

Bu öğeden alıntı yapmak, öğeye bağlanmak için bu tanımlayıcıyı kullanınız: http://hdl.handle.net/11513/341

Başlık:	Artificial Neural Network Prediction of the Performance of Upflow and Downflow Fluidized Bed Reactors Treating Acidic Mine Drainage Water
Yazarlar:	Atasoy, Ayşe Dilek Babar, B. Şahinkaya, Erkan
Anahtar kelimeler:	Metal removal Mine water Reactor modeling Sulfate reduction
Yayın Tarihi:	2013
Yayıncı:	Mine Water Environ
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.
URI:	http://hdl.handle.net/11513/341
Koleksiyonlarda Görünür:	Çevre Mühendisliği

Bu öğenin dosyaları:

Dosya	Açıklama	Boyut	Biçim
Artificial Neural Network Prediction of the Performance-Dilek Atasoy.pdf		554.58 kB	Adobe PDF	Göster/Aç

DSpace'deki bütün öğeler, aksi belirtilmedikçe, tüm hakları saklı tutulmak şartıyla telif hakkı ile korunmaktadır.

DSpace JSPUI