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

Document Type: Research Paper

Authors

1 Catalyst Research Center, Chemical Engineering Department, Faculty of Engineering, Razi University, Kermanshah, I. R. Iran

2 Chemical Engineering Department, Faculty of Energy, Kermanshah University of Technology, Kermanshah, I. R. Iran

3 Faculty of Mechanical Engineering, Sharif University of Technology, Tehran, I. R. Iran

Abstract

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).
 

Keywords


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