Design Technology of Centrifugal Fan Impeller Based on Response Surface Methodology

2010 ◽  
Author(s):  
Changyun Zhu ◽  
Guoliang Qin
Keyword(s):  
Response Surface Methodology ◽  
Objective Function ◽  
Response Surface ◽  
Optimization Design ◽  
Second Order ◽  
Centrifugal Fan ◽  
Least Squares Regression ◽  
Optimization Strategy ◽  
Order Polynomial ◽  
Rsm Model

An optimization strategy called response surface methodology (RSM) is applied to a centrifugal fan impeller optimization design in this paper. RSM is used to generate an approximated model of objective function, for which a second-order polynomial function is chosen. The Design of experiment (DOE) technique coupled with CFD analysis is then ran to generate the database. The least-squares regression method (LS) is used to determine the coefficient of the RSM function. Finally, the Genetic Algorithms (GA) is applied to the objective function in order to obtain the optimal configuration. This paper also presents a solution to the problem of imprecise fitting of second-order RSM model by dividing the zone into several subzones which is proved to be effective in this paper. The optimization result shows that RSM is an effective and feasible optimization strategy for the centrifugal fan impeller design, and the complexity of the objective function and the overall optimization time could be significantly reduced.

scholarly journals Combined Surfactant and Enzyme-Assisted Extraction of Pectin from Hawthorn (Crataegus monogyna Jacq.) Fruits

2022 ◽  
Vol 51 (4) ◽  
pp. 733-742
Author(s):  
Anastasia Novikova ◽  
Liubov Skrypnik
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Polynomial Regression ◽  
Polynomial Equation ◽  
Second Order ◽  
Wild Fruits ◽  
Assisted Extraction ◽  
Order Polynomial ◽  
Extraction Parameters ◽  
Enzyme Assisted Extraction

Introduction. Commercial pectin is usually obtained from apples or citrus fruits. However, some wild fruits, such as hawthorn, are also rich in pectin with valuable nutritional and medical properties. The research objective was to study and improve the process of combined surfactant and enzyme-assisted extraction of pectin from hawthorn fruits. Study objects and methods. The study involved a 1% solution of Polysorbate-20 surfactant and a mix of two enzymes, namely cellulase and xylanase, in a ratio of 4:1. The response surface methodology with the Box-Behnken experimental design improved the extraction parameters. The experiment featured three independent variables – temperature, time, and solvent-to-material ratio. They varied at three levels: 20, 40, and 60°C; 120, 180, and 240 min; 15, 30, and 45 mL per g. Their effect on the parameters on the pectin yield was assessed using a quadratic mathematical model based on a second order polynomial equation. Results and discussion. The response surface methodology made it possible to derive a second order polynomial regression equation that illustrated the effect of extraction parameters on the yield of polyphenols. The regression coefficient (R2 = 98.14%) and the lack-of-fit test (P > 0.05) showed a good accuracy of the model. The optimal extraction conditions were found as follows: temperature = 41°C, time = 160 min, solvent-to-material ratio = 32 mL per 1 g. Under the optimal conditions, the predicted pectin yield was 14.9%, while the experimental yield was 15.2 ± 0.4%. The content of galacturonic acid in the obtained pectin was 58.5%, while the degree of esterification was 51.5%. The hawthorn pectin demonstrated a good complex-building ability in relation to ions of copper (564 mg Cu2+/g), lead (254 mg Pb2+/g), and cobalt (120 mg Co2+/g). Conclusion. Combined surfactant and enzyme-assisted extraction made improved the extraction of pectin from hawthorn fruits. The hawthorn pectin can be used to develop new functional products.

scholarly journals Green-extraction of essential oil of the species Ruta chalepensis L.: gas chromatography-mass spectroscopy-infra red analysis and response surface methodology optimization

2019 ◽  
Vol 6 (2) ◽  
pp. 88-109
Author(s):  
Mohamed Djermane ◽  
Abdenabi Abidi ◽  
Amani Chrouda ◽  
Noureddine Gherraf ◽  
Messaoud Ramdani ◽  
...  
Keyword(s):  
Gas Chromatography ◽  
Response Surface Methodology ◽  
Essential Oil ◽  
Response Surface ◽  
Water Flow Rate ◽  
Second Order ◽  
Operating Conditions ◽  
Mass Spectrometry Analysis ◽  
Ruta Chalepensis ◽  
Order Polynomial

Abstract The objective of the present study was the optimization of the parameters affecting the hydrodistillation of Ruta chalepensis L. essential oil using response surface design type Box-Behnken. After an appropriate choice of three parameters, 15 experiments were performed leading to a mathematical second-degree model relating the response function (yield of essential oil) to parameters and allowing a good control of the extraction process. The realization of the experiments and data analysis was carried out by response surface methodology (RSM). A deduced second-order polynomial expression was used to determine the optimal conditions necessary to obtain a better essential oil yield. These optimized operating conditions were: a granulometry of 2 mm, a condensation-water flow rate of 3.4 mL/min and an extraction time of 204 min. Analysis of variance (ANOVA) indicates that the generated second-order polynomial model was highly significant with R2=0.9589 and P<0.006. The gas chromatography-mass spectrometry analysis of essential oil extracted from the Ruta chalepensis L. aerial parts revealed the presence of 2-undecanone, 2-nonanone and 2-decanone as major components.

Optimized Formulation of APN Toothpaste with Biochemical Materials Using Response Surface Methodology

2013 ◽  
Vol 676 ◽  
pp. 108-113
Author(s):  
Ting Kong ◽  
Chao Yan Zhang ◽  
Bin Bao ◽  
Long Sha ◽  
Zhen Wang ◽  
...  
Keyword(s):  
Experimental Data ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Panax Notoginseng ◽  
Second Order ◽  
Polynomial Model ◽  
Composite Score ◽  
Optimum Formulation ◽  
Order Polynomial ◽  
Addition Amount

Response surface methodology(RSM) was used to optimize the formulation of one toothpaste with aglycone extracted from Panax notoginseng(APN). Biochemical materials are important components in toothpastes. The addition amount of APN, thickener, different ratios of humectant and friction agent were selected as three factors for the design. Our results showed that the experimental data could be adequately fitted into a second-order polynomial model. Addition amount of thickener and humectant : friction agent had a significant effect on the composite score. The optimum formulation for preparing APN toothpaste was predicted to be: APN, 0.12%; thickener, 1.58%; humectant : friction agent, 1.01.

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.

Optimization of Manufacturing Process of Traditional Algerian Jben Cheese Using Response Surface Methodology (RSM)

2018 ◽  
Vol 8 (1) ◽  
pp. 31-42
Author(s):  
M. Amimour ◽  
T. Idoui ◽  
A. Cheriguene
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Manufacturing Process ◽  
Milk Powder ◽  
Statistical Design ◽  
Polynomial Equation ◽  
Enzymatic Extract ◽  
Traditional Cheese ◽  
Order Polynomial ◽  
Predicted Values

The Aim of this study was to develop an optimized method for manufacturing process of traditional Algerian Jben cheese, using response surface methodology (RSM). In order to develop the objective method of making this traditional cheese, several factors have been studied and a Plackett-Burman statistical design was applied. The effects of the four screened factors (enrichment with milk powder, 10 - 20 g/l; pH of milk, 5.75 - 6.75, enzymatic extract dose, 0.5 - 1.5 ml and coagulation temperature 40 - 60 °C) on the response were investigated, using a Box-Behnken statistical design. Multiple regression analysis was used so that experimental data fits to a second-order polynomial equation. This multiple analysis showed that the model explains about 90.73% of the variation. Based on statistical results, it can be noticed that enrichment with milk powder and pH of milk (Ë‚0.0001***) were highly significant factor influincing cheese yield. The optimal production parame-ters that maximized cheese product (20 g/l enrichment with milk powder, 5.75 pH of milk, 1.29 ml enzymatic extract dose and 60°C coagulation temperature) and the maximal predicted cheese yield (52.68 % ) were found out through response surface methodology. Under these conditions, a verification experiment was carried out and cheese yield was found to be 49.46 %. The overall percentage of agreement for the experimental results (more than 93 % validity) with the predicted values indicates the validation of the statistical model and the success of the optimization process.

scholarly journals OPTIMIZATION OF LEVOFLOXACIN REMOVAL FROM AQUEOUS SOLUTION USING ELECTROCOAGULATION PROCESS BY RESPONSE SURFACE METHODOLOGY

2021 ◽  
Vol 52 (1) ◽  
pp. 204-217
Author(s):  
Mohammed & Mohammed-Ridha
Keyword(s):  
Aqueous Solution ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Correlation Coefficient ◽  
Iron Hydroxide ◽  
Second Order ◽  
Experimental Results ◽  
Order Kinetic ◽  
Experimental Conditions ◽  
Good Agreement

This study was aimed to investigate the response surface methodology (RSM) to evaluate the effects of various experimental conditions on the removal of levofloxacin (LVX) from the aqueous solution by means of electrocoagulation (EC) technique with stainless steel electrodes. The EC process was achieved successfully with the efficiency of LVX removal of 90%. The results obtained from the regression analysis, showed that the data of experiential are better fitted to the polynomial model of second-order with the predicted correlation coefficient (pred. R2) of 0.723, adjusted correlation coefficient (Adj. R2) of 0.907 and correlation coefficient values (R2) of 0.952. This shows that the predicted models and experimental values are in good agreement. The results of the kinetic study showed that the second-order kinetic model was in good agreement with the experimental results and suggested that the mechanism of chemisorption controlled the LVX adsorption. The experimental results indicated that the adsorption of LVX on iron hydroxide flocs follows Sips isotherm with the value of the correlation coefficient (R2) of 0.937. Sips isotherm shows that both homogenous and heterogeneous adsorption can occur.

Response surface methodology as optimization strategy for asymmetric bioreduction of (4S)-(+)-carvone by Cryptococcus gastricus

2012 ◽  
Vol 121 ◽  
pp. 290-297 ◽  
Author(s):  
Marta Goretti ◽  
Eva Branda ◽  
Benedetta Turchetti ◽  
Maria Rita Cramarossa ◽  
Andrea Onofri ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Optimization Strategy ◽  
Asymmetric Bioreduction
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