Use of BDST and an ANN model for prediction of dye adsorption efficiency of Eucalyptus camaldulensis barks in fixed-bed system

BALCI B., KESKİNKAN O., AVCI M.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.38, sa.1, ss.949-956, 2011 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 1
  • Basım Tarihi: 2011
  • Doi Numarası: 10.1016/j.eswa.2010.07.084
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.949-956
  • Anahtar Kelimeler: Dyes, Adsorption columns, Tree barks, Eucalyptus camaldulensis, BDST model, neural networks, METHYLENE-BLUE, BASIC DYE, AQUEOUS-SOLUTIONS, COLOR REMOVAL, WASTE-WATER, ACTIVATED-SLUDGE, NEURAL-NETWORKS, REACTIVE DYES, BIOSORPTION, EQUILIBRIUM
  • Çukurova Üniversitesi Adresli: Evet

Özet

In this study, the Bohart and Adams' model taking into account bed depth, and influent dye concentration was studied to exhibit adsorption process of textile dyes (Basic Blue 41 - BB41 and Reactive Black 5 - RB5) in glass columns using tree barks (Eucalyptus camaldulensis). Adsorption capacity coefficient values are determined using the Bohart and Adams' bed depth service model. The model indicated that adsorption properties of E. camaldulensis barks conform for tertiary treatment for textile BB41 and RB5 containing wastewaters. An artificial neural network (ANN) based model for determining dye adsorption capability of bed system is also developed. The breakthrough curves of adsorption are also exhibited by this model. Results showed that ANN model could describe present system. Results showed that with the increases of bed height, and the decreases of influent dye concentrations, the breakthrough time was delayed. (C) 2010 Elsevier Ltd. All rights reserved.

In this study, the Bohart and Adams’ model taking into account bed depth, and influent dye concentration was studied to exhibit adsorption process of textile dyes (Basic Blue 41 –BB41 and Reactive Black 5 –RB5) in glass columns using tree barks (Eucalyptus camaldulensis). Adsorption capacity coefficient values are determined using the Bohart and Adams’ bed depth service model. The model indicated that adsorption properties of E. camaldulensis barks conform for tertiary treatment for textile BB41 and RB5 containing wastewaters. An artificial neural network (ANN) based model for determining dye adsorption capability of bed system is also developed. The breakthrough curves of adsorption are also exhibited by this model. Results showed that ANN model could describe present system. Results showed that with the increases of bed height, and the decreases of influent dye concentrations, the breakthrough time was delayed.