Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor
In this research, photocatalytic degradation method has been introduced to clean up Spent Caustic of Olefin units of petrochemical industries (neutralized Spent Caustic by means of sulfuric acid) in the next step, adaptable method and effective parameters in the process performance have been investi...
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| Format: | Article |
| Language: | English |
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Iranian Association of Chemical Engineering (IAChE)
2018-02-01
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| Series: | Iranian Journal of Chemical Engineering |
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| Online Access: | https://www.ijche.com/article_63122_756662460f778e52e8a2a58d70adb82f.pdf |
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| author | A. Ahmadpour A. Haghighiasl N. Fallah |
| author_facet | A. Ahmadpour A. Haghighiasl N. Fallah |
| author_sort | A. Ahmadpour |
| collection | DOAJ |
| description | In this research, photocatalytic degradation method has been introduced to clean up Spent Caustic of Olefin units of petrochemical industries (neutralized Spent Caustic by means of sulfuric acid) in the next step, adaptable method and effective parameters in the process performance have been investigated. Chemical oxygen demand (COD) was measured by the commercial zinc oxide that synthesized with precipitation synthesis method in a two-shell photoreactor. The percent of reduction of COD in the photocatalytic process was modeled using Box–Behnken design and artificial neural network techniques. It was concluded that the ANN was a more accurate method than the design of experiment. The effect of important parameters including oxidant dosage, aeration rate, pH, and catalyst loading was investigated. The results showed that all of the parameters, except pH, had positive effects on increasing COD removal. According to the obtained results, adsorption and photolysis phenomena had a negligible effect on COD removal. |
| format | Article |
| id | doaj-art-9fdf80795c4f430982da9af0234c4eb2 |
| institution | OA Journals |
| issn | 1735-5397 2008-2355 |
| language | English |
| publishDate | 2018-02-01 |
| publisher | Iranian Association of Chemical Engineering (IAChE) |
| record_format | Article |
| series | Iranian Journal of Chemical Engineering |
| spelling | doaj-art-9fdf80795c4f430982da9af0234c4eb22025-08-20T02:25:08ZengIranian Association of Chemical Engineering (IAChE)Iranian Journal of Chemical Engineering1735-53972008-23552018-02-01151467263122Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactorA. Ahmadpour0A. Haghighiasl1N. Fallah2Faculty of Chemical, Gas and Petroleum Engineering, Semnan University, Semnan, IranFaculty of Chemical, Gas and Petroleum Engineering, Semnan University, Semnan, IranChemical Engineering Department, Amirkabir University of Technology, Tehran, IranIn this research, photocatalytic degradation method has been introduced to clean up Spent Caustic of Olefin units of petrochemical industries (neutralized Spent Caustic by means of sulfuric acid) in the next step, adaptable method and effective parameters in the process performance have been investigated. Chemical oxygen demand (COD) was measured by the commercial zinc oxide that synthesized with precipitation synthesis method in a two-shell photoreactor. The percent of reduction of COD in the photocatalytic process was modeled using Box–Behnken design and artificial neural network techniques. It was concluded that the ANN was a more accurate method than the design of experiment. The effect of important parameters including oxidant dosage, aeration rate, pH, and catalyst loading was investigated. The results showed that all of the parameters, except pH, had positive effects on increasing COD removal. According to the obtained results, adsorption and photolysis phenomena had a negligible effect on COD removal.https://www.ijche.com/article_63122_756662460f778e52e8a2a58d70adb82f.pdfannrsmcodznophotocatalytic removal |
| spellingShingle | A. Ahmadpour A. Haghighiasl N. Fallah Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor Iranian Journal of Chemical Engineering ann rsm cod zno photocatalytic removal |
| title | Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor |
| title_full | Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor |
| title_fullStr | Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor |
| title_full_unstemmed | Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor |
| title_short | Investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor |
| title_sort | investigation of spent caustic wastewater treatment through response surface methodology and artificial neural network in a photocatalytic reactor |
| topic | ann rsm cod zno photocatalytic removal |
| url | https://www.ijche.com/article_63122_756662460f778e52e8a2a58d70adb82f.pdf |
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