Predictive Modelling and Surface Analysis for Optimization of Production of Biofuel as A Renewable Energy Resource: Proposition of Artificial Neural Network Search

Murthy Sri Krishna; Goyal Ankit; Rajasekar N.Pareek KapilNguyen Thoi TrungGarg A.

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Predictive Modelling and Surface Analysis for Optimization of Production of Biofuel as A Renewable Energy Resource: Proposition of Artificial Neural Network Search

机译：Predictive Modelling and Surface Analysis for Optimization of Production of Biofuel as A Renewable Energy Resource: Proposition of Artificial Neural Network Search

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The present study undertakes the research problem on the optimization of production of biodiesel as a renewable energy resource from the transesterification of soybean oil and ethanol. Predictive modelling and surface analysis techniques were applied based on the artificial neural network search algorithm to correlate the yield of ethyl ester and glycerol and the input parameters. The formulated models accurately predicted the yield of the products with a high coefficient of determination. When the reaction time is low, the ester yield decreases with an increase in temperature and the maximum yield of obtained biodiesel at a very low value of time of reaction and temperature. Plots based on parametric and sensitivity analysis reveals that the yield of ethyl ester can be maximized and that of glycerol minimized at an integrated condition with lower ethanol/oil molar ratio, higher temperature value, higher catalyst concentration value, and longer time of reaction. The global sensitivity analysis reveals that the catalyst concentration and temperature of the reaction influence the yield of ethyl ester the most. In addition, an optimal ethyl ester yield of 95 can be achieved at specific input conditions. Moreover, according to the results of global sensitivity analysis, the catalyst concentration is found to be most significant for both the glycerol and ethyl ester yield.

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《Mathematical Problems in Engineering: Theory, Methods and Applications》 |2020年第26期|4065964.1-4065964.13|共13页
作者
Murthy Sri Krishna; Goyal Ankit; Rajasekar N.Pareek KapilNguyen Thoi TrungGarg A.;
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Natl Univ Singapore, Dept Chem & Biomol Engn, Singapore 117576, Singapore;

Univ Amsterdam, Inst Phys, Sci Pk 904, Amsterdam, Netherlands;

VIT Univ, Sch Elect Engn, Solar Energy Res Cell, Vellore, Tamil Nadu, IndiaMalaviya Natl Inst Technol, Ctr Energy & Environm, Jaipur 302017, Rajasthan, IndiaTon Duc Thang Univ, Inst Computat Sci, Div Computat Math & Engn, Ho Chi Minh City 700000, Vietnam|Ton Duc Thang Univ, Fac Civil Engn, Ho Chi Minh City 700000, Vietnam;

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Predictive Modelling and Surface Analysis for Optimization of Production of Biofuel as A Renewable Energy Resource: Proposition of Artificial Neural Network Search

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