2014
DOI: 10.1016/j.supflu.2014.07.023
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Response surface optimization of Smyrnium cordifolium Boiss (SCB) oil extraction via supercritical carbon dioxide

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Cited by 55 publications
(23 citation statements)
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“…Response surface methodology (RSM), which is a combination of mathematical and statistical techniques, is widely applied for analyzing the influence of various factors on one system (Liu et al, 2015a;Sodeifian et al, 2014;Kirmizakis et al, 2014). To explore the relationship between the borehole radius (X 1 ), the initial pressure (X 2 ), the original permeability (X 3 ) and gas drainage effects, a mathematical model was designed using Design Expert 8.0.5b software.…”
Section: Response Surface Methodologymentioning
confidence: 99%
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“…Response surface methodology (RSM), which is a combination of mathematical and statistical techniques, is widely applied for analyzing the influence of various factors on one system (Liu et al, 2015a;Sodeifian et al, 2014;Kirmizakis et al, 2014). To explore the relationship between the borehole radius (X 1 ), the initial pressure (X 2 ), the original permeability (X 3 ) and gas drainage effects, a mathematical model was designed using Design Expert 8.0.5b software.…”
Section: Response Surface Methodologymentioning
confidence: 99%
“…There was only a 0.01% chance that a large "Model F value" could occur due to noise. Values of "Prob > F" less than 0.0500 indicate that the model terms are significant (Sodeifian et al, 2014). In this case A, B, C, B 2 are significant model terms.…”
Section: Analysis Of Variance (Anova)'mentioning
confidence: 96%
“…Response surface methodology (RSM), a collection of mathematical and statistical techniques, has been found to be a functional aid in exploring the interactions of multiple factors on the response of a system (Kirmizakis et al, 2014;Sodeifian et al, 2014;Yuan et al, 2015). During an analysis, it is very important to select an appropriate method that can evaluate the influence of independent variables and their coupled effects on the dependent variable with fewer experiments.…”
Section: Response Surface Methodologymentioning
confidence: 99%
“…During an analysis, it is very important to select an appropriate method that can evaluate the influence of independent variables and their coupled effects on the dependent variable with fewer experiments. RSM provides a great deal of information with only a small number of tests to monitor the interactions among variables on the response (Sodeifian et al, 2014;Kirmizakis et al, 2014).…”
Section: Response Surface Methodologymentioning
confidence: 99%
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