 The optimized operational conditions for biodiesel production from soybean oil and application of artificial neural networks for estimation of the biodiesel yieldG.R. Moradi, S. Dehghani, F. Khosravian and A. Arjmandzadeh Renewable Energy, 2013, vol. 50, issue C, 915-920 Abstract: In this study, transesterification of soybean oil to biodiesel using KOH in different process conditions were studied. The investigated conditions were the molar ratio of methanol/oil, catalyst amount and reaction temperature. Optimal conditions were found to be methanol/oil molar ratio, 9:1; catalyst amount, 1 wt%; reaction temperature, 60 °C. Biodiesel yield for these conditions was obtained 93.2% in 1 h. In addition, the artificial neural network has been applied to estimate the biodiesel yield. The multilayer feed forward neural network with three inputs and one output has been trained with different algorithms and different numbers of neurons in the hidden layer. The accuracy of the proposed model was found to agree nearly with the experimental results over a wide range of experimental conditions. The results clearly depict that the neural network is a powerful tool to estimate the reaction rate and the designed neural network can be used instead of approximate and complex analytical equations. Keywords: Biodiesel; Soybean oil; Artificial neural networks; Basic catalyst (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:50:y:2013:i:c:p:915-920 DOI: 10.1016/j.renene.2012.08.070 Access Statistics for this article Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides More articles in Renewable Energy from Elsevier |
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