Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system
Catalysis, Kinetics and Reaction Engineering|Updated:2026-01-06
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Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system
Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system
中国化学工程学报(英文版)2020年28卷第7期 页码:1847-1859
Affiliations:
Project Management and Civil Infrastructure Systems, The University of Trinidad and Tobago, San Fernando Campus, Tarouba Link Road San Fernando, WI, Trinidad and Tobago
Beverly S. Chittoo, Clint Sutherland. Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system[J]. 中国化学工程学报(英文版), 2020,28(7):1847-1859.
Beverly S. Chittoo, Clint Sutherland. Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system[J]. Chinese Journal of Chemical Engineering, 2020, 28(7): 1847-1859.
Beverly S. Chittoo, Clint Sutherland. Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system[J]. 中国化学工程学报(英文版), 2020,28(7):1847-1859.DOI: 10.1016/j.cjche.2020.02.022.
Beverly S. Chittoo, Clint Sutherland. Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system[J]. Chinese Journal of Chemical Engineering, 2020, 28(7): 1847-1859.DOI: 10.1016/j.cjche.2020.02.022.
Column breakthrough studies for the removal and recovery of phosphate by lime-iron sludge: Modeling and optimization using artificial neural network and adaptive neuro-fuzzy inference system
Increases in the treatment of water to meet the growing water demand ultimately result in unmanageable quantities of residuals
the handling
and disposal of which is a major environmental issue. Consequently
research into beneficial reuse of water treatment residuals continues unabated. This study investigated the applicability of lime-iron sludge for phosphate adsorption by fixed-bed column adsorption. Laboratory-scale experiments were conducted at varying flow rates and bed depths. Fundamental and empirical models (Thomas
Yan
Bohart-Adams
Yoon-Nelson
and Wolboroska) as well as artificial intelligence techniques (Artificial neural network (ANN) and Adaptive neuro-fuzzy inference system (ANFIS)) were used to simulate experimental breakthrough curves and predict column dynamics. Increase in flow rate resulted in reduced adsorption capacity. However
adsorption capacity was not affected by bed depth. ANN was superior in predicting breakthrough curves and predicted breakthrough times with high accuracy (
R
2
0.9962). NaOH (0.5 mol·L
-1
) was successfull
y used to regenerate the adsorption bed. After nine cyclic adsorption/desorption runs
only a marginal decrease in adsorption and desorption efficiencies of 10% and 8% respectively was observed. The same regenerate NaOH solution was reused for all desorption cycles. After nine cycles the eluent desorbed a total of 1550 mg phosphate exhibiting potential for further reuse.
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