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.

The Optimization of Pb(II),Cu(II),Zn(II) and Cd(II) Ions Removal by Micro-Electrolysis Using Response Surface Methodology

2013 ◽  
Vol 800 ◽  
pp. 537-545
Author(s):  
Jian Ping Xu ◽  
Zhi Huang ◽  
Yan Ling Gao
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Mine Drainage ◽  
Polynomial Equation ◽  
Interactive Effects ◽  
Quadratic Model ◽  
Design Matrix ◽  
Box Behnken Design ◽  
Operating Variables ◽  
Order Polynomial

In this study, the Box–Behnken design matrix and response surface methodology (RSM) have been applied in the experiments to evaluate the interactive effects of four most important operating variables: pH (2.0–4.0), temperature (30–40°C )，iron/carbon ratio（1/2–3/2）and iron carbon amounts (2-4) on the removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions in acid mine drainage with micro-electrolysis (ME) . The total 29 experiments were conducted in the present study for the construction of a quadratic model. The independent variables have significant value 0.0001, which indicates the importance of these variables in the ME process. The values of “Prob > F” less than 0.0500 indicate that model terms are significant for the removal of Cr (VI), Ni (II) and Zn (II) ions. The regression equation coefficients were calculated and the data fitted to a second-order polynomial equation for removal of Pb (II), Cu(II)，Zn (II) and Cd (II) ions with ME.

Optimization studies on Biosorption of Copper (II) by Crab Shell Using Response Surface Methodology(RSM)

2010 ◽  
Vol 5 (1) ◽  
Author(s):  
Sudesh S ◽  
Meenakshi M ◽  
Sheeja R.Y ◽  
Thanapalan Murugesan
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Crab Shell ◽  
Box Behnken Design ◽  
Initial Ph ◽  
Predicted Values ◽  
Experimental Values ◽  
The Individual ◽  
Maximum Removal ◽  
Good Agreement

In the present work, crab shell was used as the biosorbent to remove copper from aqueous solution. Batch experiments were performed at different initial copper concentration of copper solutions (1-40 g/l), initial pH (2-9), temperature (20-400°C), and biosorbent dosages (2-10 g/l). The maximum removal of copper using crab shell occurred at a pH of 3 and at a temperature of 400°C using an optimum biosorbent dosage of 5 g/l. A mathematical model was proposed to identify the effects of the individual interactions of these variables on the biosorption of copper. The results have been modeled using response surface methodology using a Box-Behnken design. The response surface method was developed using three levels (-1, 0, +1) with the above mentioned four factors. The second order quadratic regression model fitted the experimental data with Prob > F to be < 0.0001. The experimental values were found to be in good agreement with the predicted values, with a satisfactory correlation coefficient of R2 = 0.9999.

scholarly journals Optimizing parameters of warp fatigue life tester by response surface methodology

2019 ◽  
Vol 14 ◽  
pp. 155892501989380
Author(s):  
Min Guo ◽  
Bo Zhu ◽  
Jianli Liu ◽  
Weidong Gao
Keyword(s):  
Response Surface Methodology ◽  
Fatigue Life ◽  
Response Surface ◽  
Measurement Method ◽  
Load Capacity ◽  
Static Tension ◽  
Optimal Parameters ◽  
Box Behnken Design ◽  
Load Frequency ◽  
Experimental Values

The aim of this article was to provide an effective measurement method of the warp dynamic load capacity based on a warp fatigue life tester for sized yarns. Five parameters which affected the fatigue life of warp, respectively, namely, load frequency, warp speed, pre-tension weight, heald frame stroke, and static tension of the warp fatigue life tester, were studied. First, the influences of the five parameters on warp fatigue life were analyzed through single-factor experiments, and then, the Box–Behnken design based on the response surface methodology was adopted to optimize warp fatigue life tester parameters. The results showed that the optimum parameter conditions of the warp fatigue life tester for warp fatigue life were as follows: when heald frame stroke at 77.16 mm, load frequency of 205.49 times/min, and static tension as 6.96 cN, the optimal warp fatigue life was 1394.05 times. The theoretical and experimental values were in reasonable agreement, and the relative error was less than 1%. Verification and repeated trial results showed that the optimal parameters had good reproducibility, and the warp fatigue life tester with the optimal parameters provided an effective and reliable evaluation to the warp frictional, stretching, and buckling effects.

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.

Study on the Rice Straw Pretreated with NaOH for Biogasification

2011 ◽  
Vol 197-198 ◽  
pp. 140-146
Author(s):  
Jia You Li ◽  
Xiao Mei Ye ◽  
Jian Xing Yu ◽  
Li Ling Cai ◽  
Shan Ming Ruan ◽  
...  
Keyword(s):  
Response Surface ◽  
Rice Straw ◽  
Surface Analysis ◽  
Treatment Time ◽  
Polynomial Equation ◽  
Ftir Analysis ◽  
Sem Images ◽  
Box Behnken Design ◽  
Naoh Pretreatment ◽  
Main Factors

In this study, Box-Behnken design (BBD) and response surface analysis (RSA) methodology were employed to plan experiments and optimize the NaOH pretreatment of rice straw. Experimental results showed that concentration of NaOH (CS), treatment time (TT) and ratio of rice straw with NaOH (RS) were main factors governing the biogasification of rice straw. The polynomial equation describing the biogasification as a simultaneous function of the CS, TT and RS was confirmed. The FTIR analysis and SEM images of straws further confirmed that NaOH could disrupt the silicified waxy surface, break down the lignin-hemicellulose complex and partially remove silicon and lignin from the pretreated rice straw.

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.

Studies of kerf width and surface roughness using the response surface methodology in AA 4032–TiC composites

2021 ◽  
pp. 095440892110414
Author(s):  
TS Senthilkumar ◽  
R Muralikannan ◽  
T Ramkumar ◽  
S Senthil Kumar
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Matrix ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Kerf Width ◽  
Wire Electrical Discharge Machining ◽  
Box Behnken Design ◽  
Pulse On Time

A substantially developed machining process, namely wire electrical discharge machining (WEDM), is used to machine complex shapes with high accuracy. This existent work investigates the optimization of the process parameters of wire electrical discharge machining, such as pulse on time ( Ton), peak current ( I), and gap voltage ( V), to analyze the output performance, such as kerf width and surface roughness, of AA 4032–TiC metal matrix composite using response surface methodology. The metal matrix composite was developed by handling the stir casting system. Response surface methodology is implemented through the Box–Behnken design to reduce experiments and design a mathematical model for the responses. The Box–Behnken design was conducted at a confident level of 99.5%, and a mathematical model was established for the responses, especially kerf width and surface roughness. Analysis of variance table was demarcated to check the cogency of the established model and determine the significant process. Surface roughness attains a maximum value at a high peak current value because high thermal energy was released, leading to poor surface finish. A validation test was directed between the predicted value and the actual value; however, the deviation is insignificant. Moreover, a confirmation test was handled for predicted and experimental values, and a minimal error was 2.3% and 2.12% for kerf width and surface roughness, respectively. Furthermore, the size of the crater, globules, microvoids, and microcracks were increased by amplifying the pulse on time.

Experimental Studies Using Response Surface Methodology for Condition Monitoring of Ball Bearings

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
M. S. Patil ◽  
Jose Mathew ◽  
P. K. Rajendrakumar ◽  
Sumit Karade
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Interaction Effect ◽  
Damage Identification ◽  
Experimental Studies ◽  
Design Procedure ◽  
Defect Size ◽  
Ball Bearings ◽  
Box Behnken Design ◽  
Outer Race

The presence of defect in the bearing (outer race, inner race, or ball) results in increased vibrations. Time domain indices such as rms, crest factor, and kurtosis are some of the important parameters used to monitor the condition of the bearing. Radial load and operating speed also have an important role in bearing vibrations. The interaction between the defect size, load, and speed helps to study their effect on vibrations more effectively. Response surface methodology (RSM) is a combination of statistical and mathematical techniques to represent the relationship between the inputs and the outputs of a physical system. But so far, the literature related to its application in bearing damage identification is scarce. The proposed study uses RSM to study the influence of defect size, load, and speed on the bearing vibrations. Kurtosis is used as response factor. Experiments are planned using Box Behnken design procedure. Experiments are performed using 6305 ball bearings and the results have been presented. MINITAB statistical software is used for analysis. It is seen from the analysis of the experimental results that the defect size, interaction effect of defect size and load, and interaction effect of defect size and speed are significant. Response surface method using Box Behnken design and analysis of variance has proved to be a successful technique to assess the significant factors related to bearing vibrations.

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