Investigation of petrochemical industries spent caustic wastewater photocatalitic treatment using DOE & ANN methods

Document Type : Research paper

Abstract

In this study, photocatalytic treatment was used to treat spent caustic wastewater of olefin petrochemical plants which is one of industrial wastewater with high total dissolved solids (TDS). For this purpose, by using the synthetic photocatalyst of ZNO and measuring the parameter of the chemical oxygen demand (COD), this parameter decrease percentage in the Photocatalyst process has been evaluated by means of Box-Behnken (BBD) design of experiment (DOE) and the artificial neural network (ANN) in a double-cylindrical-shell photo-reactor. According to the implemented calculations, it can be resulted that the artificial neural network is more suitable method than the experimental design in modeling and forecasting the amount of COD removal. Modeling of this research showed that increasing the concentration of photocatalyst in a state of neutral pH, lead to enhance the COD removal till the optimal amount of 1.8 g/L without restrictions and 2 g/L with restrictions in the rate of 79% and 68%, respectively.

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References

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Journal of Separation Science and Engineering
Volume 9, Issue 1
September 2017
Pages 33-45

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