Abstract
The current study deals with the maximization of NaOH conversion using step-wise regression analysis in a CSTR. The dependence of temperature, volume, agitation rate, and feed rate on reactor performance is examined as well as interaction outcome of the operating parameters. The concentration of the reactants was fixed at 0.1 M. The steady state conversion with respect to NaOH is analyzed to find the process performance. Step-wise regression analysis is used to remove an insignificant factors. The agitation rate (X2) and feed rate (X3) proved to have an insignificant influence on the reaction conversion at a significant level (α) of 5%. Consequently, the temperature (X1) and reaction volume (X4) were found to have significant effect on the reaction conversion using step-wise regression. The temperature and volume dependence on steady state NaOH conversion were described by a polynomial model of 2nd and 3rd order. A maximal steady state conversion equal to 63.15% was obtained. No improvement was found in reaction conversion with 3rd order polynomial, so the second order polynomial is considered as the optimum reaction conversion modal. It may be recommended that 2nd order regression polynomial model adequately represents the experimental data very well.
Highlights
Stepwise regression is a prevailing technique to forecast unidentified predicted variables from predictor variables
The 2nd order polynomial model was chosen for regression analysis using optimum factors
Moderate positive correlation (r = 0.599) was observed between volume and conversion, which states that 100% increase in volume results in 59.9% surge in reaction conversion
Summary
Stepwise regression is a prevailing technique to forecast unidentified predicted variables from predictor variables. A factorial design was applied to study the optimization of ethyl acetate [21,22]. A parametric study for ethyl acetate saponification was performed using a batch reactor and the impact of temperature, volume, rate of agitation, and initial reagents concentration was examined [24]. The batch reactor performance was studied using regression analysis for saponification of ethyl acetate [25] and maximal conversion of 0.995 realized under optimum conditions reactant concentration and agitation rate. The multiple regression was applied for examining the CH3COOC2H5 hydrolysis using continuous stirred tank reactor (CSTR). The novelty of the current work is that it optimizes the formation of sodium acetate and ethanol, applying step-wise regression applying polynomial models. Studies [10,11,12,18] have explicitly concentrated reaction mechanics and kinetics of hydrolysis of ethyl acetate
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