Journals / Uludağ Üniversitesi Mühendislik Fakültesi Dergisi / 2017 / Cilt: 22 - Sayı: 3

Investigation of the Treatability of Hand-printed Textile Wastewaters by UV/H2O2 Using Artificial Neural Networks

EL BASKISI İŞLETMELERİNDEN KAYNAKLANAN TEKSTİL ATIKSULARININ UV/H2O2 PROSESİYLE ARITILABİLİRLİĞİNİN YAPAY SİNİR AĞLARI İLE ARAŞTIRILMASI

Pages
201–212
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

According to the results, pH is the predominant variable, and the reaction mean time and H2O2 volume are the less influential variables.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the photooxidation of pollutants such as COD and color present in hand-printed textile wastewaters has been carried out in the presence of hydrogen peroxide (H2O2), using 256 nm UV light (15 W), and the results of the treatment has been presented.
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Key Findings & Data:The obtained data has been successfully tested through a NeuroSolutions 5.06 model.
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Conclusion & Impact:According to the results, pH is the predominant variable, and the reaction mean time and H2O2 volume are the less influential variables.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Arıtma · el baskısı tekstil atıksuyu · UV/H2O2

Abstract

In this study, the photooxidation of pollutants such as COD and color present in hand-printed textile wastewaters has been carried out in the presence of hydrogen peroxide (H2O2), using 256 nm UV light (15 W), and the results of the treatment has been presented. The obtained data has been successfully tested through a NeuroSolutions 5.06 model. Each sample has been characterized by three independent variables (i.e., pH, H2O2 concentration, and time of operation) and two dependent variables (i.e., color and COD). According to the results, pH is the predominant variable, and the reaction mean time and H2O2 volume are the less influential variables. The neural model obtained presented coefficients of correlation of 99% for COD and 99% for color, indicating the prediction power of the model and its character of generalization.

Özet

Bu çalışmada, el baskısı işletmelerinden kaynaklanan tekstil atıksularındaki KOİ ve renk gibi kirleticilerin fotooksidasyonu, UV/H2O2 prosesi ile 256 nm dalga boyunda, 15 W’lık lambaların kullanımıyla gerçekleştirilmiş ve arıtma sonuçları sunulmuştur. Veriler NeuroSolutions 5.06 model ile başarılı bir şekilde test edilmiştir. Her bir örnek, üç bağımsız değişken (pH, H2O2 konsantrasyonu, işletme süresi) ve iki bağımlı değişken (renk ve KOİ) ile karakterize edilmiştir. Sonuçlar, pH’ın baskın değişken olduğunu, reaksiyon süresi ile H2O2 konsantrasyonunun daha az etkili değişkenler olduğunu göstermiştir. Model, KOİ için %99 ve renk için %99 korelasyon katsayıları sunarken, modelin tahmin gücünü ve genellemenin karakterini belirtmektedir.

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Cite This Article

KILIÇ, M. Y., YONAR, T. (2017). Investigation of the Treatability of Hand-printed Textile Wastewaters by UV/H2O2 Using Artificial Neural Networks. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, Cilt: 22 - Sayı: 3, 201–212. https://ajindex.com/articles/329931

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References (10)

  1. Akbostancı, İ. (2004) Anadolu’da yazmacılık sanatı, Skylife, 246, 100-107.
  2. AlHamedi, F.H., Rauf, M.A. and Ashraf, S.S. (2009) Degradation studies of Rhodamine B in the presence of UV/H2O2, Desalination, 239, 159-166. doi:10.1016/j.desal.2008.03.016 Anonim (2011) Su Kirliliği Kontrol Yönetmeliğinde Değişiklik Yapılmasına Dair Yönetmelik, http://www.resmigazete.gov.tr/eskiler/2011/04/20110424-9.htm (erişim tarihi: 31.01.2017)
  3. Anonim (2017) Hand painted textiles http://www.turkishculture.org/pages.php?ParentID=14&ID=109, (erişim tarihi: 31.01.2017)
  4. APHA-AWWA-WEF (1998) Standard Methods for the Examination of Water and Wastewater, 20th ed.; American Public Health Association: Washington D.C. Arslan, I. and Akmehmet Balcioglu, I. (1999) Degradation of commercial reactive dyestuffs by heterogenous and homogenous advanced oxidation processes: a comparative study, Dyes Pigments, 43, 95-108. PII: S0143-7208(99)00048-0
  5. Azbar, N., Yonar, T. and Kestioğlu, K. (2004) Comparison of various advanced oxidation processes and chemical treatment methods for COD and color removal from a polyester and acetate fiber dyeing effluent, Chemosphere, 55, 35-43. doi:10.1016/j.chemosphere.2003.10.046 Behnajady, M.A., Modirshahla, N. and Shokri, M. (2004) Photodestruction of Acid Orange 7 (AO7) in aqueous solutions by UV/H2O2: Influence of operational parameters, Chemosphere, 55,129-134. doi:10.1016/j.chemosphere.2003.10.054 Bilinska, L., Gmurek, M., Ledakowicz, S. (2015) Application of advanced oxidation technologies for decolorization and mineralization of textile wastewaters, Journal of Advanced Oxidation Technologies, 18(2), 185-194. doi.org/10.1515/jaots-2015-0202.
  6. Clarke, N. and Knowles, G. (1982) High purity water using H2O2 and UV radiation, Effluent Water Treatment Journal, 23, 335-341.
  7. Correira, V.M., Stephenson, T. and Judd S.J. (1994) Characterizastion of textile wastewater- a review, Environmental Technology, 15 (10), 917-929. doi.org/10.1080/09593339409385500 Crittenden, J.C., Hu, S., Hand, D.W. and Gren, S.A. (1999) A kinetic model for H2O2/UV process in a completely mixed batch reactor, Water Research, 33, 2315-2328.
  8. Çokay Çatalkaya, E., Bali, U. and Şengül, F. (2004) Fenol’ün fotokimyasal yöntemlerle parçalanması ve mineralizasyonu, Su Kirlenmesi Kontrolü Dergisi, 14(3), 31-41.
  9. Dabek, L., Ozimina, E. and Picheta-Oles, A. (2013) Research on removal of coloured organic compounds from textile industry wastewater, Rocznik Ochrona Srodowiska, 15, 1164-1176.
  10. De Melo, C.F., d