Using Artificial Neural Network for Estimation of Density and Viscosities of Biodiesel–Diesel Blends

نویسندگان

  • Bita Karami Catalyst Research Center, Chemical Engineering Department, Faculty of Engineering, Razi University, Kermanshah, I. R. Iran
  • Gholamreza Moradi Catalyst Research Center, Chemical Engineering Department, Faculty of Engineering, Razi University, Kermanshah, I. R. Iran
  • Majid Mohadesi Chemical Engineering Department, Faculty of Energy, Kermanshah University of Technology, Kermanshah, I. R. Iran
  • Ramin Moradi Faculty of Mechanical Engineering, Sharif University of Technology, Tehran, I. R. Iran
چکیده مقاله:

In recent years, biodiesel has been considered as a good alternative of diesel fuels. Density and viscosity are two important properties of these fuels. In this study, density and kinematic viscosity of biodiesel-diesel blends were estimated by using artificial neural network (ANN). A three-layer feed forward neural network with Levenberg-Marquard (LM) algorithm was used for learning empirical data (previous studies data and this study empirical data). Input data for estimating density and kinematic viscosity includes components volume fraction, temperature and pure component properties (pure density at 293.15 K and pure kinematic viscosity at 313.15 K). Results of neural network simulation for density and kinematic viscosity showed a high accuracy (mean relative error for density and kinematic viscosity are 0.021% and 0.73%, respectively).  

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عنوان ژورنال

دوره 49  شماره 2

صفحات  153- 165

تاریخ انتشار 2015-12-01

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