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.

scholarly journals Optimization of an Ultrasound-Assisted Extraction Condition for Flavonoid Compounds from Cocoa Shells (Theobroma cacao) Using Response Surface Methodology

Molecules ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 711 ◽  
Author(s):  
Arief Md Yusof ◽  
Siti Abd Gani ◽  
Uswatun Zaidan ◽  
Mohd Halmi ◽  
Badrul Zainudin
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Ethanol Concentration ◽  
Irradiation Time ◽  
Ultrasound Irradiation ◽  
Coefficient Of Determination ◽  
Ultrasound Assisted Extraction ◽  
Assisted Extraction ◽  
Ultrasound Assisted ◽  
Experimental Values

This study investigates the ultrasound-assisted extraction of flavonoids from Malaysian cocoa shell extracts, and optimization using response surface methodology. There are three variables involved in this study, namely: ethanol concentration (70–90 v/v %), temperature (45–65 °C), and ultrasound irradiation time (30–60 min). All of the data were collected and analyzed for variance (ANOVA). The coefficient of determination (R2) and the model was significant in interaction between all variables (98% and p < 0.0001, respectively). In addition, the lack of fit test for the model was not of significance, with p > 0.0684. The ethanol concentration, temperature, and ultrasound irradiation time that yielded the maximum value of the total flavonoid content (TFC; 7.47 mg RE/g dried weight (DW)) was 80%, 55 °C, and 45 min, respectively. The optimum value from the validation of the experimental TFC was 7.23 ± 0.15 mg of rutin, equivalent per gram of extract with ethanol concentration, temperature, and ultrasound irradiation time values of 74.20%, 49.99 °C, and 42.82 min, respectively. While the modelled equation fits the data, the T-test is not significant, suggesting that the experimental values agree with those predicted by the response surface methodology models.

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.

Combined Steam-Carbon Dioxide Reforming of Methane: Modeling Using Response Surface Methodology (RSM)

2020 ◽  
Vol 20 (9) ◽  
pp. 5720-5724
Author(s):  
Cho Hwe Kim ◽  
Young Chul Kim
Keyword(s):  
Carbon Dioxide ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Coefficient Of Determination ◽  
Feed Ratio ◽  
Carbon Dioxide Conversion ◽  
Carbon Dioxide Reforming ◽  
Rsm Model ◽  
Central Composite ◽  
Good Agreement

In this paper, combined steam-carbon dioxide reforming of methane (CSDRM) on a nickel-based catalyst is investigated by using response surface methodology (RSM). Models were developed based on central composite design (CCD), conducted on methane, carbon dioxide conversion, and H2/CO ratio with feed ratio, flow rate, and temperature. In Analysis of variance analysis (ANOVA), good agreement was shown between predicted data from RSM model and experimental data as well. This indicated, high adjusted R2 (R square, coefficient of determination), F-value over 0.75, and p-value less than 0.05. CH4 and CO2 conversion were considerably improved at higher reaction temperature, because of the endothermic nature of the CSDRM. Also, H2/CO ratio was affected by feed ratio. The minutiae of development of the model, testing, etc. is presented in this study.

scholarly journals Optimisation of Reactive Black 5 dye removal by electrocoagulation process using response surface methodology

2016 ◽  
Vol 75 (4) ◽  
pp. 952-962 ◽  
Author(s):  
W. T. Mook ◽  
M. K. Aroua ◽  
M. Szlachta ◽  
C. S. Lee
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Treatment Time ◽  
Textile Wastewater ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Reactive Black 5 ◽  
Solution Ph ◽  
Initial Ph ◽  
Electrocoagulation Process

In this work, a regression model obtained from response surface methodology (RSM) was proposed for the electrocoagulation (EC) treatment of textile wastewater. The Reactive Black 5 dye (RB5) was used as a model dye to evaluate the performance of the model design. The effect of initial solution pH, applied current and treatment time on RB5 removal was investigated. The total number of experiments designed by RSM amounted to 27 runs, including three repeated experimental runs at the central point. The accuracy of the model was evaluated by the F-test, coefficient of determination (R2), adjusted R2 and standard deviation. The optimum conditions for RB5 removal were as follows: initial pH of 6.63, current of 0.075 A, electrolyte dose of 0.11 g/L and EC time of 50.3 min. The predicted RB5 removal was 83.3% and the percentage error between experimental and predicted results was only 3–5%. The obtained data confirm that the proposed model can be used for accurate prediction of RB5 removal. The value of the zeta potential increased with treatment time, and the X-ray diffraction pattern shows that iron complexes were found in the sludge.

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.

scholarly journals Modeling and Sensitivity Analysis of the Forward Osmosis Process to Predict Membrane Flux Using a Novel Combination of Neural Network and Response Surface Methodology Techniques

Membranes ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 70
Author(s):  
Jasir Jawad ◽  
Alaa H. Hawari ◽  
Syed Javaid Zaidi
Keyword(s):  
Response Surface Methodology ◽  
Experimental Design ◽  
Response Surface ◽  
Forward Osmosis ◽  
Feed Solution ◽  
Operating Conditions ◽  
Ann Model ◽  
Membrane Flux ◽  
Input Variables ◽  
Rsm Model

The forward osmosis (FO) process is an emerging technology that has been considered as an alternative to desalination due to its low energy consumption and less severe reversible fouling. Artificial neural networks (ANNs) and response surface methodology (RSM) have become popular for the modeling and optimization of membrane processes. RSM requires the data on a specific experimental design whereas ANN does not. In this work, a combined ANN-RSM approach is presented to predict and optimize the membrane flux for the FO process. The ANN model, developed based on an experimental study, is used to predict the membrane flux for the experimental design in order to create the RSM model for optimization. A Box–Behnken design (BBD) is used to develop a response surface design where the ANN model evaluates the responses. The input variables were osmotic pressure difference, feed solution (FS) velocity, draw solution (DS) velocity, FS temperature, and DS temperature. The R2 obtained for the developed ANN and RSM model are 0.98036 and 0.9408, respectively. The weights of the ANN model and the response surface plots were used to optimize and study the influence of the operating conditions on the membrane flux.

scholarly journals Efficient Removal of Levofloxacin by Activated Persulfate with Magnetic CuFe2O4/MMT-k10 Nanocomposite: Characterization, Response Surface Methodology, and Degradation Mechanism

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3583
Author(s):  
Junying Yang ◽  
Minye Huang ◽  
Shengsen Wang ◽  
Xiaoyun Mao ◽  
Yueming Hu ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Photoelectron Spectroscopy ◽  
Degradation Mechanism ◽  
Sol Gel ◽  
Combustion Method ◽  
Copper Ferrite ◽  
X Ray ◽  
Rsm Model

In this study, a magnetic copper ferrite/montmorillonite-k10 nanocomposite (CuFe2O4/MMT-k10) was successfully fabricated by a simple sol-gel combustion method and was characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), the Brunner–Emmett–Teller (BET) method, vibrating sample magnetometer (VSM), and X-ray photoelectron spectroscopy (XPS). For levofloxacin (LVF) degradation, CuFe2O4/MMT-k10 was utilized to activate persulfate (PS). Due to the relative high adsorption capacity of CuFe2O4/MMT-k10, the adsorption feature was considered an enhancement of LVF degradation. In addition, the response surface methodology (RSM) model was established with the parameters of pH, temperature, PS dosage, and CuFe2O4/MMT-k10 dosage as the independent variables to obtain the optimal response for LVF degradation. In cycle experiments, we identified the good stability and reusability of CuFe2O4/MMT-k10. We proposed a potential mechanism of CuFe2O4/MMT-k10 activating PS through free radical quenching tests and XPS analysis. These results reveal that CuFe2O4/MMT-k10 nanocomposite could activate the persulfate, which is an efficient technique for LVF degradation in water.

scholarly journals Optimization of Crude Oil and PAHs Degradation by Stenotrophomonas rhizophila KX082814 Strain through Response Surface Methodology Using Box-Behnken Design

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Praveen Kumar Siddalingappa Virupakshappa ◽  
Manjunatha Bukkambudhi Krishnaswamy ◽  
Gaurav Mishra ◽  
Mohammed Ameenuddin Mehkri
Keyword(s):  
Response Surface Methodology ◽  
Crude Oil ◽  
Response Surface ◽  
Oxygen Demand ◽  
Inoculum Size ◽  
Coefficient Of Determination ◽  
Oil Removal ◽  
Box Behnken Design ◽  
Stenotrophomonas Rhizophila ◽  
Crude Oil Removal

The present paper describes the process optimization study for crude oil degradation which is a continuation of our earlier work on hydrocarbon degradation study of the isolate Stenotrophomonas rhizophila (PM-1) with GenBank accession number KX082814. Response Surface Methodology with Box-Behnken Design was used to optimize the process wherein temperature, pH, salinity, and inoculum size (at three levels) were used as independent variables and Total Petroleum Hydrocarbon, Biological Oxygen Demand, and Chemical Oxygen Demand of crude oil and PAHs as dependent variables (response). The statistical analysis, via ANOVA, showed coefficient of determination R2 as 0.7678 with statistically significant P value 0.0163 fitting in second-order quadratic regression model for crude oil removal. The predicted optimum parameters, namely, temperature, pH, salinity, and inoculum size, were found to be 32.5°C, 9, 12.5, and 12.5 mL, respectively. At this optimum condition, the observed and predicted PAHs and crude oil removal were found to be 71.82% and 79.53% in validation experiments, respectively. The % TPH results correlate with GC/MS studies, BOD, COD, and TPC. The validation of numerical optimization was done through GC/MS studies and   % removal of crude oil.

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