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Comparison of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) in Optimization of Aegle marmelos Oil Extraction for Biodiesel Production

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Abstract

Non-edible feedstock is attaining importance due to authentic concerns behind the utilization of food crops for fuel production. Aegle marmelos seed is one such feedstock with high oil content portraying a better entrant among other non-edible feedstock. In this study, optimization of oil extraction, and biodiesel production from Aegle marmelos seeds had been reported. Oil extraction performed with n-hexane was optimized by response surface methodology (RSM) and artificial neural network (ANN). The influence of five parameters on oil extraction, namely particle size, acid concentration, solvent-to-seed ratio, extraction time and temperature were investigated. A comparison of performance evaluation between RSM and ANN was executed. The lower value of coefficient of determination (\(R^{2} = 0.998\)), root mean square error (\({ RMSE} = 0.2784\)), standard error of prediction (\({ SEP} = 0.7068\)) and absolute average deviation (\({ AAD} = 0.3425\)) for ANN compared to those of \(R^{2}\) (0.9769), RMSE (0.5349), SEP (1.3326) and AAD (1.1072) for RSM showed the prediction competence of the ANN was much better than RSM. Among the process parameters studied, solvent-to-seed ratio was the most influential variable on oil yield. The maximum oil yield of 45.99 wt% was obtained at optimum conditions, with an acid value of 18.92 mg KOH \(\hbox {g}^{-1}\). Hence, a dual-stage acid-base transesterification was employed to produce biodiesel. It was followed by \(^{1}\)H NMR spectroscopy study and fuel properties analysis. The highest conversion of 98% was ascertained using \(^{1}\)H NMR spectroscopy, and the biodiesel fuel properties were found to comply with ASTM standards.

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Authors and Affiliations

  1. Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, 620015, India

    S. Sindhanai Selvan, P. Saravana Pandian, A. Subathira & S. Saravanan

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  1. S. Sindhanai Selvan
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  3. A. Subathira
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  4. S. Saravanan
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Correspondence to S. Saravanan.

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Selvan, S.S., Pandian, P.S., Subathira, A. et al. Comparison of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) in Optimization of Aegle marmelos Oil Extraction for Biodiesel Production. Arab J Sci Eng 43, 6119–6131 (2018). https://doi.org/10.1007/s13369-018-3272-5

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