scholarly journals Optimization of the Fenton Oxidation of Synthetic Textile Wastewater using Response Surface Methodology

2017 ◽  
Vol 25 (0) ◽  
pp. 108-113 ◽  
Author(s):  
Maciej Thomas ◽  
Krzysztof Barbusiński ◽  
Katarzyna Kalemba ◽  
Paweł Jan Piskorz ◽  
Violetta Kozik ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Anionic Surfactant ◽  
Azo Dye ◽  
Textile Wastewater ◽  
Fenton Process ◽  
Optimal Process ◽  
Model Studies ◽  
Experimental Values

This article presents the possibility of using the classical Fenton process (Fe(II)/H2O2) to purify synthetic textile wastewater (COD=1872 mg O2/dm3, TOC=660 mg/dm3) containing azo dye Anilan Blue GRL 250% (200 mg/dm3) and Sodium Lauryl Sulphate (SLS) as anionic surfactant at a concentration of 95 mg/dm3. Model studies were carried out using RSM, obtaining a good fit of approximated values to experimental values (R2=0.9461 and R2adj=0.7379). For optimal process parameters (pH 3, Fe(II) 0.85 g/dm3, H2O2 14.5 g/dm3), complete decolourisation (<10 mg Pt/dm3) was achieved as well as a reduction in COD, TOC and SLS concentrations to 83%, 44% and 98%, respectively.

Optimization of electrohydraulic forming process parameters using the response surface methodology

2021 ◽  
Vol 63 (6) ◽  
pp. 571-580
Author(s):  
Balasubramanian Arun Prasath ◽  
Pasupathy Ganesh ◽  
Karibeeran Shanmuga Sundaram
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Standoff Distance ◽  
Optimum Process ◽  
Forming Process ◽  
Electrohydraulic Forming ◽  
Acceptable Range ◽  
Steel Aisi ◽  
Experimental Values

Abstract This work’s main objective is to determine the optimum process parameters in the electrohydraulic forming (EHF) of austenitic stainless steel AISI 304 of 0.25 mm thickness for macro and micro shape. A truncated cone with grooves in the apex is considered as macro-micro shape. The response surface methodology (RSM) was developed for process variables such as voltage and standoff distance to determine the optimum parameters. To validate the model, confirmation experiments have been conducted, i. e. for the optimum value of voltage (V) = 8.935 kV and standoff distance (SOD) = 40.60 mm, and from the experiments the forming depth predicted is 9.221 mm and depth from the experiments is 9.5 mm. The percentage deviation from the predicted and experimental forming depth is 3.025 %, an acceptable range of less than 5 % for the surface roughness, the predicted value is 0.2598 microns, and the experimentally measured value is 0.268. The percentage deviation is 3.156 % between the predicted and experimental values, an acceptable range of less than 5 %. This shows that the model is suitable for predicting both responses. The validation experiments also found that the sheet fills one of the grooves and partially fills the other, which shows the capability of the electrohydraulic forming process. Confirmation experiments have been conducted.

Application of response surface methodology on COD removal from textile wastewater by anodic chlorination and cathodic electro-Fenton process

2018 ◽  
Vol 108 ◽  
pp. 144-151
Author(s):  
Mei-Hui Chung ◽  
Chih-Ta Wang ◽  
Jian-Wen Wang ◽  
Wei-Lung Chou ◽  
Yi-Ming Kuo
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Textile Wastewater ◽  
Cod Removal ◽  
Fenton Process

Prediction of Optimal Process Parameters in Tribocorrosion Inhibition of Steel Pipes Using Response Surface Methodology

2021 ◽  
Vol 69 (2) ◽  
Author(s):  
Jitendra Narayan Panda ◽  
Edwin Yanez Orquera ◽  
Brandon Christopher Wong ◽  
Philip Egberts
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Optimal Process ◽  
Steel Pipes

A Modelling Study by Response Surface Methodology (RSM) on Turbidity Removal Optimization using Nanocellulose Filter Paper (Neolamarckia Cadamba)

2021 ◽  
Vol 02 (02) ◽  
Author(s):  
Nurul Aienna Ismail ◽  
◽  
Nor Hazren Abdul Hamid ◽  
Keyword(s):  
Response Surface Methodology ◽  
Predictive Model ◽  
Response Surface ◽  
Filter Paper ◽  
Initial Temperature ◽  
Textile Wastewater ◽  
Coefficient Of Determination ◽  
Turbidity Removal ◽  
Experimental Values ◽  
Rsm Model

This study observed the influence of initial turbidity, pH and initial temperature on the turbidity removal from the textile wastewater using nanocellulose filter paper from Neolamarckia Cadamba. Response Surface Methodology (RSM) model was employed to optimize and create a predictive model to evaluate the turbidity removal performance on the nanocellulose filter paper. The performance of the RSM model was statistically evaluated in terms of coefficient of determination, R2. The optimum value of turbidity removal of 99.39% were found at 66 NTU, pH 6.4 and 35.9°C. The value of prediction that obtained from modelling (RSM) was in agreement with the experimental values with R2 = 88.23%, AAD = 6.87% and RMSE = 0.18 towards the efficiency of turbidity removal.

Optimisation of the Oil Extraction from Nigella sativa Seeds Using Response Surface Methodology

2017 ◽  
Vol 68 (2) ◽  
pp. 331-336
Author(s):  
Gabriela Isopencu ◽  
Mirela Marfa ◽  
Iuliana Jipa ◽  
Marta Stroescu ◽  
Anicuta Stoica Guzun ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Nigella Sativa ◽  
Polynomial Equation ◽  
Herbaceous Plant ◽  
Box Behnken Design ◽  
Pareto Analysis ◽  
Black Cumin ◽  
Mediterranean Countries ◽  
Experimental Values

Nigella sativa, also known as black cumin, an annual herbaceous plant growing especially in Mediterranean countries, has recently gained considerable interest not only for its use as spice and condiment but also for its healthy properties of the fixed and essential oil and its potential as a biofuel. Nigella sativa seeds fixed oil, due to its high content in linoleic acid followed by oleic and palmitic acid, could be beneficial to human health. The objective of this study is to determine the optimum conditions for the solvent extraction of Nigella sativa seeds fixed oil using a three-level, three-factor Box-Behnken design (BBD) under response surface methodology (RSM). The obtained experimental data, fitted by a second-order polynomial equation were analysed by Pareto analysis of variance (ANOVA). From a total of 10 coefficients of the statistical model only 5 are important. The obtained experimental values agreed with the predicted ones.

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