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Optimized Biodiesel production from C. innophyllum Bio-oil using Kriging and ANN predictive models

Publication Type : Journal Article

Publisher : Thermal Science Journal

Source : Thermal Science Journal

Url : https://www.researchgate.net/publication/296687523_Optimization_of_biodiesel_production_from_refined_cotton_seed_oil_and_its_characterization

Keywords : Cotton seed oil;Biodiesel;Characterization;Response surfacemethodology;Optimization

Campus : Chennai

School : School of Engineering

Department : Mechanical Engineering

Year : 2022

Abstract : Biodiesel was produced through transesterification of refined cotton seed oil with methanol and potassium hydroxide (KOH) as a catalyst using batch mode. The physicochemical properties of cotton seed oil and biodiesel as an alternative fuel for diesel engine was characterized through ASTM standards for fuel tests. The functional groups of the biodiesel were investigated using Fourier transform infrared spectroscopy. Influence of key parameters like reaction temperature, reaction time, catalyst concentration and methanol/oil molar ratio were determined using batch mode. These process parameters were optimized using response surface methodology (RSM) and analysis of variance (ANOVA). The significance of the different process parameters and their combined effects on the transesterification efficiency were established through a full factorial central composite design. The results obtained are in good agreement with published data for other vegetable oil biodiesel as well as various international standards for biodiesel fuel. An optimum yield of 96% was achieved with optimal conditions of methanol/oil molar ratio, 6:1; temperature, 55°C; time, 60min; and catalyst concentration, 0.6%. This investigation has shown that cotton seed oil from Nigeria can be used to produce biodiesel.

Cite this Research Publication : Hariram V., Goldwin J. J., Saravanan A., Vinod kumar M., Balachandar M., Johnson Samuel S., Seralathan S., K. L. Vasudev (2022) Optimized Biodiesel production from C. innophyllum Bio-oil using Kriging and ANN predictive models. Thermal Science Journal. (Impact factor 1.39)

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