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

Abstract

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.

Keywords

• Arıtma,el baskısı tekstil atıksuyu,UV/H2O2

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

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.

Keywords

• Treatment,hand-printed textile wastewater,UV/H2O2,artificial neural network

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