Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural Networks
The wide range of today's industry increases the diversity of pollutants in the wastewater characteristics. In particular, the wastewater of the textile industry is highly colored. Different techniques are used for color removal of dyes from wastewater. In this work, the removal efficiency of t...
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Sakarya University
2020-08-01
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| Series: | Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi |
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| Online Access: | https://dergipark.org.tr/tr/download/article-file/1210069 |
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| author | Bediha Oyar Beytullah Eren Abdil Özdemir |
| author_facet | Bediha Oyar Beytullah Eren Abdil Özdemir |
| author_sort | Bediha Oyar |
| collection | DOAJ |
| description | The wide range of today's industry increases the diversity of pollutants in the wastewater characteristics. In particular, the wastewater of the textile industry is highly colored. Different techniques are used for color removal of dyes from wastewater. In this work, the removal efficiency of the textile dye (Reactive Black 5) at different current densities (48.5 A/m2, 97.18 A/m2, 194.36 A/m2, 291.5 A/m2, 388.7 A/m2) was investigated by electrocoagulation method. The dye concentration of wastewater prepared in the laboratory scale was adjusted to 100 mg/L. Two iron electrodes and 3 g NaCl were used in the electrocoagulation system. The samples which taken periodically were measured after the centrifugal processes with the UV spectrophotometer. The experimental results were also modelled with artificial neural networks (ANNs). As a result of the experiments, approximately 90-100% color removal efficiency was obtained. According to the modelling study, the ANNs can predict the color removal efficiency with coefficient of determination (R2) between the experimental and predicted output variable reached up to 0.99. |
| format | Article |
| id | doaj-art-b9c5afa4cd5c4a90824600a83a70c7d8 |
| institution | OA Journals |
| issn | 2147-835X |
| language | English |
| publishDate | 2020-08-01 |
| publisher | Sakarya University |
| record_format | Article |
| series | Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi |
| spelling | doaj-art-b9c5afa4cd5c4a90824600a83a70c7d82025-08-20T02:31:51ZengSakarya UniversitySakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi2147-835X2020-08-0124471272410.16984/saufenbilder.69814628Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural NetworksBediha Oyar0https://orcid.org/0000-0003-1683-5531Beytullah Eren1https://orcid.org/0000-0001-6747-7004Abdil Özdemir2https://orcid.org/0000-0002-0900-0221SAKARYA UNIVERSITYSAKARYA UNIVERSITYSAKARYA UNIVERSITYThe wide range of today's industry increases the diversity of pollutants in the wastewater characteristics. In particular, the wastewater of the textile industry is highly colored. Different techniques are used for color removal of dyes from wastewater. In this work, the removal efficiency of the textile dye (Reactive Black 5) at different current densities (48.5 A/m2, 97.18 A/m2, 194.36 A/m2, 291.5 A/m2, 388.7 A/m2) was investigated by electrocoagulation method. The dye concentration of wastewater prepared in the laboratory scale was adjusted to 100 mg/L. Two iron electrodes and 3 g NaCl were used in the electrocoagulation system. The samples which taken periodically were measured after the centrifugal processes with the UV spectrophotometer. The experimental results were also modelled with artificial neural networks (ANNs). As a result of the experiments, approximately 90-100% color removal efficiency was obtained. According to the modelling study, the ANNs can predict the color removal efficiency with coefficient of determination (R2) between the experimental and predicted output variable reached up to 0.99.https://dergipark.org.tr/tr/download/article-file/1210069wastewaterelectrocoagulationtextile dye (reactive black 5(rb5))colorartificial neural network |
| spellingShingle | Bediha Oyar Beytullah Eren Abdil Özdemir Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural Networks Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi wastewater electrocoagulation textile dye (reactive black 5(rb5)) color artificial neural network |
| title | Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural Networks |
| title_full | Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural Networks |
| title_fullStr | Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural Networks |
| title_full_unstemmed | Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural Networks |
| title_short | Removal of Reactive Black 5 from Polluted Solutions by Electrocoagulation: Modelling Experimental Data Using Artificial Neural Networks |
| title_sort | removal of reactive black 5 from polluted solutions by electrocoagulation modelling experimental data using artificial neural networks |
| topic | wastewater electrocoagulation textile dye (reactive black 5(rb5)) color artificial neural network |
| url | https://dergipark.org.tr/tr/download/article-file/1210069 |
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