Concurrent Optimization of Decolorization, COD Removal, and Their Costs in Response to Photocatalytic Degradation Integrating Experimental Designs, Artificial Immune System, and Empirical Modeling

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dc.authorid0000-0001-6841-6457en_US
dc.authorid0000-0003-1099-4363en_US
dc.authorid0000-0002-7035-7078
dc.contributor.authorBüyükada, Musa
dc.contributor.authorEryiğit, Miraç
dc.contributor.authorEvrendilek, Fatih
dc.date.accessioned2021-06-23T19:49:45Z
dc.date.available2021-06-23T19:49:45Z
dc.date.issued2018
dc.departmentBAİBÜ, Mühendislik Fakültesi, Kimya Mühendisliği Bölümüen_US
dc.description.abstractThis study aims at the quantification of color and chemical oxygen demand (COD) removal of methylene blue by TiO2-assisted photocatalytic degradation, and associated costs based on various designs of experiment (DOEs). For this purpose, effects of seven explanatory variables of catalyst dose (CD, g.TiO2.L-1), initial dye concentration (IDC, mg.L-1), initial pH (pH), temperature (T, degrees C), lamp type (LT), aeration (AR, mL.min(-1)), and reaction time (RT, min) were investigated on the related response variables. Experimental results demonstrated that CD, AR, IDC, and RT were significantly effective on the response variables. Novelty of the study lies in simultaneously optimizing these four responses based on DOEs, and Artificial immune System (AIS) optimization. Taguchi Orthogonal Array (TOA) as the best optimization DOE led to complete decolorization (> 99%) and 95.1% COD removal with UV-C lamp whose costs corresponded to 6.5 and 41.4 USD, respectively, under aeration rate of 20 mL.min(-1), initial dye concentration of 10 mg.L-1, TiO2 concentration of 4 g.L-1, and reaction time of 20 min. AIS optimization yielded complete decolorization and 96.4% COD removal under the same TOA experimental conditions, with their corresponding costs of 0.5 and 3.1 USD, respectively. D-optimality and Box-Behnken designs were found as the second best DOEs for decolorization and COD removal, and their costs, respectively.en_US
dc.identifier.endpage1470en_US
dc.identifier.issn0125-2526
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage1460en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12491/9608
dc.identifier.urihttps://epg.science.cmu.ac.th/ejournal/journal-detail.php?id=9153
dc.identifier.volume45en_US
dc.identifier.wosWOS:000432774600024en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorBüyükada, Musa
dc.institutionauthorEvrendilek, Fatih
dc.institutionauthorEryiğit, Miraç
dc.language.isoenen_US
dc.publisherChiang Mai Univ, Fac Scienceen_US
dc.relation.ispartofChiang Mai Journal Of Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectData-driven Modelingen_US
dc.subjectMultiple Responses Optimizationen_US
dc.subjectWater Qualityen_US
dc.subjectArtificial intelligence systemsen_US
dc.titleConcurrent Optimization of Decolorization, COD Removal, and Their Costs in Response to Photocatalytic Degradation Integrating Experimental Designs, Artificial Immune System, and Empirical Modelingen_US
dc.typeArticleen_US

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