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

Year 2017, Volume: 22 Issue: 3, 201 - 212, 31.12.2017

Melike Yalılı Kılıç , Taner Yonar

https://doi.org/10.17482/uumfd.320528

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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