Using of neural network to simulation of the biodiesel production process from waste oil.

Author

Abstract

This study deals with artificial neural network (ANN) modeling of a biodiesel production using waste cooking oil to predict the biodiesel purity. developed ANN was a feed forward back propagation network with one input, one hidden and one output layers. The input parameters for the ANN were methanol/oil molar ratio (3:1–9:1), temperature (45–65â€‌â€‌â€‌â€‌â€‌â€‌â€‌â€‌â€‌‫‪‭ °C), and mixing intensity (200–600 rpm) and the output parameter was biodiesel purity. The biodiesel with best purity was produced at methanol/oil molar ratio, of 6:1 mixing intensity, of 600 rpm and reaction temperature of 65 °C. Different transfer functions and several rules were used to assess the percentage error between the desired and the predicted values. It was observed that the ANN model can predict the biodiesel yield quite well with correlation coefficient (R) 0.99966. We can conclude that ANNs can be used to predict the biodiesel yield from used waste cooking oil.

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1-      غضنفری، م و ارکات، ج.(1383). "شبکه ای عصبی(اصول و کارکردها) ". انتشارات دانشگاه علم و صنعت. تهران. ایران.
2-      کیا، م. (1387). "شبکه های عصبی در مطلب". انتشارات کیان رایانه سبز. تهران. ایران.
3-       Canakci, M., Ozsezen, A.N., Arcaklioglu., E., Erdil, A.(2009). "Prediction of performance and exhaust emissions of a diesel engine fueledwith biodiesel produced from waste frying palm oil". Expert Systems with Applications 36 (2009) 9268–9280
4-       Gerpen, J. V., Shanks, B., and Pruszko, R. (2004). "Biodiesel Production Technology". National Renewable Energy Laboratory, N.R.E.L.
5-       Meher, L.C., Vidya Sagar, D. and Naik, S.N. (2005). "Optimization of alkali-catalyzed  transesterification of Pongamia pinnata oil for production of biodiesel". Bioresource Technology, 97: 1392–1397.
6-       Morris, R.E., Pollack, A. K., Mansell, G. E., Lindhjem, Y. Jia, and Wilson, G. (2003). "Impact of Biodiesel Fuels on Air Quality and Human Health", National Renewable Energy Laboratory, N.R.E.L.
7-       Ghobadian, B., Rahimi, H., Nikbakht, A.M., Najafi, G., Yusaf, T.F.(2009). "Diesel engine performance and exhaust emission analysis using waste cooking biodiesel fuel with an artificial neural network". Renewable Energy 34 (2009) 976–982.
8-       Rajendra, M., Jena, P.C., Raheman, H.(2009). "Prediction of optimized pretreatment process parameters for biodiesel production using ANN and GA". Fuel 88 (2009) 868–875.
9-       Wang, Y., Ou, S., Liu, P., Xue, F., Tang, S. (2006). "Comparison of two Different Processes to synthesize biodiesel by waste cooking oil". Journal of Molecular Catalysis A: Chemical, 252:107-1.
10-   Zenouzi, A and Ghobadian, B. (2007). "Design and Fabrication of a Multifunction Biodiesel processor. International Congress on Biodiesel". The Science and Technologies 5-7 November 2007.Vienna, Austria
11-   Zhang, Y. (2002). "Design and Economic assessment of Biodiesel Production from waste Cooking oil", M.A.Sc. Thesis, Department of chemical engineering, University of Ottawa.