International Journal of Chemical and Process Engineering Research

Published by: Conscientia Beam
Online ISSN: 2313-0776
Print ISSN: 2313-2558
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No. 3

Modeling and Optimization of Transesterification of Beniseed Oil to Beniseed Methylester: A Case of Artificial Neural Network versus Response Surface Methodology

Pages: 30-43
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Modeling and Optimization of Transesterification of Beniseed Oil to Beniseed Methylester: A Case of Artificial Neural Network versus Response Surface Methodology

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DOI: 10.18488/journal.65/2015.2.3/65.3.30.43

Citation: 1

Adepoju T. F. , Okunola A. A.

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Adepoju T. F. , Okunola A. A. (2015). Modeling and Optimization of Transesterification of Beniseed Oil to Beniseed Methylester: A Case of Artificial Neural Network versus Response Surface Methodology. International Journal of Chemical and Process Engineering Research, 2(3): 30-43. DOI: 10.18488/journal.65/2015.2.3/65.3.30.43
In this research work, statistical approach (ANN and RSM) were used to optimize the transesterification of beniseed oil to beniseed methyl ester (BME). Analyses of an heterogeneous catalyst (Mangifera indica powdered) obtained from unripe Mangifera indica peels showed that the powder consist  macro elements such as K (59.85%), Si (30.53%), Cl (4.58%), Al (3.05%) and Ca (1.05%) and micro elements such as P (0.196%), S (0.593%), Mn (0.043%), Fe (0.037%), Zn (0.008%), Rb (0.042%) and Sr (0.032%). ANN predicted optimal condition for Beniseed methyl ester produced was X1= 60.0 min, X2 = 1.0 wt.%, X3= 57 0C and X4 = 6.0. The predicted BME (94.40% (w/w)) under this condition was validated to be of 93.80 % (w/w). Meanwhile, RSM predicted 94.20% (w/w) at the following condition X1= 62.0 min, X2 = 0.9 wt. %, X3= 60 0C and X4 = 6.5 was validated as 92.80 % (w/w). The results obtained showed the superiority of ANN over RSM owing to its higher values of predicted value, RMSE, AAD, R2 and R2Adj. The fatty acid profile and the physicochemical properties of the BME indicated that, BME can serve as alternative fuel for conventional diesel.
Contribution/ Originality
This study contributes in the existing literature to the process conversion of oil to diesel.This study uses new estimation methodology in the use of heterogeneous catalyst obtained from agricultural waste. This study originates new way of using statistical software (ANN and RSM) to improve the yield of biodiesel. This study is one of very few studies which have investigated the use of heterogeneous catalyst to produced biodiesel. The paper contributes the first use of Mangifera indica (Mango) peels as heterogeneous base catalyst.The paper’s primary contribution is finding that biodiesel can be obtained by the use of biomass waste. This study documents economic impact of using Mangifera indica (Mango) peels as heterogeneous base catalyst to produce biodiesel.