scholarly journals Response Surface Methodology for Boron Removal by Donnan Dialysis: Doehlert Experimental Design

Membranes ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 731
Author(s):  
Ikhlass Marzouk Trifi ◽  
Lobna Chaabane ◽  
Lasâad Dammak ◽  
Lassaad Baklouti ◽  
Béchir Hamrouni
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Removal Rate ◽  
Optimum Conditions ◽  
Boron Removal ◽  
Donnan Dialysis ◽  
Counter Ions ◽  
Factor Design ◽  
Preliminary Study ◽  
Receiver Compartment

The removal of boron by Donnan dialysis from aqueous solutions has been studied according to response surface methodology (RSM). First, a preliminary study was performed with two membranes (AFN and ACS) in order to determine the experimental field based on different parameters, such as the pH of the feed compartment, the concentration of counter-ions in the receiver compartment, and the concentration of boron in the feed compartment. The best removal rate of boron was 75% with the AFN membrane, but only 48% with the ACS membrane. Then, a full-factor design was developed to determine the influence of these parameters and their interactions on the removal of boron by Donnan dialysis. The pH of the feed compartment was found to be the most important parameter. The RSM was applied according to the Doehlert model to determine the optimum conditions ([B] = 66 mg/L, pH = 11.6 and [Cl–] = 0.5 mol/L) leading to 88.8% of boron removal with an AFN membrane. The use of the RSM can be considered a good solution to determine the optimum condition for 13.8% compared to the traditional “one-at-a-time” method.

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

2018 ◽  
Vol 49 (2) ◽  
pp. 62-81 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Removal ◽  
Removal Rate ◽  
Statistical Significance ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Chatter Index ◽  
Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

scholarly journals Enzyme optimization to reduce the viscosity of pitanga (Eugenia uniflora L.) juice

2016 ◽  
Vol 19 (0) ◽  
Author(s):  
Ricardo Schmitz Ongaratto ◽  
Luiz Antonio Viotto
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Incubation Time ◽  
Regression Models ◽  
Incubation Temperature ◽  
Correlation Coefficients ◽  
Enzyme Concentration ◽  
Optimum Conditions ◽  
Activity Time ◽  
Independent Variables

Summary The aim of this work was to separately evaluate the effects of pectinase and cellulase on the viscosity of pitanga juice, and determine the optimum conditions for their use employing response surface methodology. The independent variables were pectinase concentration (0-2.0 mg.g–1) and cellulase concentration (0-1.0 mg.g–1), activity time (10-110 min) and incubation temperature (23.2-56.8 °C). The use of pectinase and cellulase reduced the viscosity by about 15% and 25%, respectively. The results showed that enzyme concentration was the most important factor followed by activity time, and for the application of cellulase the incubation temperature had a significant effect too. The regression models showed correlation coefficients (R2) near to 0.90. The pectinase application conditions that led to the lowest viscosity were: concentration of 1.7 mg.g–1, incubation temperature of 37.6 °C and incubation time of 80 minutes, while for cellulase the values were: concentration of 1.0 mg.g-1, temperature range of 25 °C to 35 °C and incubation time of 110 minutes.

scholarly journals OPTIMIZATION OF REFLUX EXTRACTION FOR CAESALPINIA SAPPAN LINN. WOOD BY USING RESPONSE SURFACE METHODOLOGY

2020 ◽  
Vol 83 (1) ◽  
pp. 85-92
Author(s):  
Mohd Azahar Mohd Ariff ◽  
Muhammad Syafiq Abd Jalil ◽  
Noor ‘Aina Abdul Razak ◽  
Jefri Jaapar
Keyword(s):  
Particle Size ◽  
Response Surface Methodology ◽  
Drinking Water ◽  
Response Surface ◽  
Extraction Time ◽  
Percentage Error ◽  
Optimum Conditions ◽  
Caesalpinia Sappan ◽  
The Mean ◽  
Repeated Runs

Caesalpinia sappan linn. (CSL) is a plant which is also known as Sepang tree contains various medicinal values such as to treat diarrhea, skin rashes, syphilis, jaundice, drinking water for blood purifying, diabetes, and to improve skin complexion. The aim of this study is to obtain the most optimum condition in terms of the ratio of sample to solvent, particle size, and extraction time to get the highest amount of concentration of the CSL extract. In this study, the ranges of each parameters used were: ratio sample to solvent: 1.0:20, 1.5:20, 2.0:20, 2.5:20, 3.0:20, particle size: 1 mm, 500 um, 250 um, 125 um, 63 um, and extraction time: 1 hr, 2 hr, 3 hr, 4 hr, 5 hr. The concentration was analyzed using a UV-vis spectrophotometer. The optimum conditions were obtained by response surface methodology. From the design, 20 samples were run throughout this experiment. The optimized value from the RSM were 2.0:20 for ratio sample to solvent, 125 µm of particle size and 2.48 hours with the concentration of 37.1184 ppm. The accuracy of the predictive model was validated with 2 repeated runs and the mean percentage error was less than 3%. This confirmed the model’s capability for optimizing the conditions for the reflux extraction of CSL’s wood.

scholarly journals Optimising Brewery-Wastewater-Supported Acid Mine Drainage Treatment vis-à-vis Response Surface Methodology and Artificial Neural Network

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1485
Author(s):  
Enoch A. Akinpelu ◽  
Seteno K. O. Ntwampe ◽  
Abiola E. Taiwo ◽  
Felix Nchu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Acid Mine Drainage ◽  
Response Surface ◽  
Mine Drainage ◽  
Sulphate Reduction ◽  
Optimum Conditions ◽  
Acid Mine ◽  
Artificial Neural

This study investigated the use of brewing wastewater (BW) as the primary carbon source in the Postgate medium for the optimisation of sulphate reduction in acid mine drainage (AMD). The results showed that the sulphate-reducing bacteria (SRB) consortium was able to utilise BW for sulphate reduction. The response surface methodology (RSM)/Box–Behnken design optimum conditions found for sulphate reduction were a pH of 6.99, COD/SO42− of 2.87, and BW concentration of 200.24 mg/L with predicted sulphate reduction of 91.58%. Furthermore, by using an artificial neural network (ANN), a multilayer full feedforward (MFFF) connection with an incremental backpropagation network and hyperbolic tangent as the transfer function gave the best predictive model for sulphate reduction. The ANN optimum conditions were a pH of 6.99, COD/SO42− of 0.50, and BW concentration of 200.31 mg/L with predicted sulphate reduction of 89.56%. The coefficient of determination (R2) and absolute average deviation (AAD) were estimated as 0.97 and 0.046, respectively, for RSM and 0.99 and 0.011, respectively, for ANN. Consequently, ANN was a better predictor than RSM. This study revealed that the exclusive use of BW without supplementation with refined carbon sources in the Postgate medium is feasible and could ensure the economic sustainability of biological sulphate reduction in the South African environment, or in any semi-arid country with significant brewing activity and AMD challenges.

Bioremediation Condition Optimization of Hydrocarbon in Soil Using Response Surface Methodology by Microbial Consortium KL9-1

2012 ◽  
Vol 518-523 ◽  
pp. 2073-2078 ◽  
Author(s):  
Qi You Liu ◽  
Yun Bo Zhang ◽  
Dong Feng Zhao ◽  
Chao Cheng Zhao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Microbial Consortium ◽  
Ph Value ◽  
Removal Rate ◽  
Desirability Function ◽  
Nitrogen And Phosphorus ◽  
Predictive Values ◽  
Independent Variables ◽  
Condition Optimization

A response surface methodology was applied to optimize the bioremediation condition of hydrocarbon in soil by microbial consortium KL9-1. A four-level Box-Behnken factorial design was employed to study the relationship of independent variables and dependent variable by applying pH value, inoculation amount of microbial consortium KL9-1, ratio of nitrogen and phosphorus (N/P ) and surfactant (SDBS) concentration as independent variables (factors) and crude oil removal rate as dependent variable (response). Then the statistically significant model was obtained and numerical optimization based on desirability function was carried out for pH 7.0, inoculation amount 50.0 mL, N/P 2: 1 and SDBS concentration 4.0 g, and the hydrocarbon removal rate reached as high as 52.58%. The predictive values showed good agreement with the experimental values under the optimization conditions, by standard variance <1.3%. It showed that the optimal result was reliable.

Optimization of photocatalytic degradation of real textile dye house wastewater by response surface methodology

2016 ◽  
Vol 74 (9) ◽  
pp. 1999-2009 ◽  
Author(s):  
Sayed Mohammad Bagher Hosseini ◽  
Narges Fallah ◽  
Sayed Javid Royaee
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Advanced Oxidation Process ◽  
Influential Factor ◽  
P Value ◽  
Textile Dye ◽  
Optimum Conditions ◽  
Effective Parameters ◽  
Initial Ph

This study evaluates the advanced oxidation process for decolorization of real textile dyeing wastewater containing azo and disperse dye by TiO2 and UV radiation. Among effective parameters on the photocatalytic process, effects of three operational parameters (TiO2 concentration, initial pH and aeration flow rate) were examined with response surface methodology. The F-value (136.75) and p-value &lt;0.0001 imply that the model is significant. The ‘Pred R-Squared’ of 0.95 is in reasonable agreement with the ‘Adj R-Squared’ of 0.98, which confirms the adaptability of this model. From the quadratic models developed for degradation and subsequent analysis of variance (ANOVA) test using Design Expert software, the concentration of catalyst was found to be the most influential factor, while all the other factors were also significant. To achieve maximum dye removal, optimum conditions were found at TiO2 concentration of 3 g L−1, initial pH of 7 and aeration flow rate of 1.50 L min−1. Under the conditions stated, the percentages of dye and chemical oxygen demand removal were 98.50% and 91.50%, respectively. Furthermore, the mineralization test showed that total organic compounds removal was 91.50% during optimum conditions.

scholarly journals Prediction of Machining Characteristics of Hybrid Composites Using Response Surface Methodology Approach

2018 ◽  
Vol 7 (3.1) ◽  
pp. 162 ◽  
Author(s):  
Ramanan. G ◽  
Rajesh Prabha.N ◽  
Diju Samuel.G ◽  
Jai Aultrin. K. S ◽  
M Ramachandran
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Hybrid Composites ◽  
Removal Rate ◽  
Cutting Speed ◽  
Chemical Properties ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Optimal Parameters ◽  
Rsm Technique

This manuscript presents the influencing parameters of CNC turning conditions to get high removal rate and minimal response of surface roughness in turning of AA7075-TiC-MoS2 composite by response surface method. These composites are particularly suited for applications that require higher strength, dimensional stability and enhanced structural rigidity. Composite materials are engineered materials made from at least two or more constituent materials having different physical or chemical properties. In this work seventeen turning experiments were conducted using response surface methodology. The machining parameters cutting speed, feed rate, and depth of cut are varied with respect to different machining conditions for each run. The optimal parameters were predicted by RSM technique. Turning process is studied by response surface methodology design of experiment. The optimal parameters were predicted by RSM technique. The most influencing process parameter predicted from RSM techniques in cutting speed and depth of cut.   

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