UMP Institutional Repository

Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network

B., Ghobadian and P., Nematizade and G., Najafi (2012) Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network. International Journal of Automotive and Mechanical Engineering (IJAME), 5 (Jan. pp. 639-647. ISSN 2229-8648 (Print); 2180-1606 (Online)

[img]
Preview
PDF
Investigation_Of_Fossil_Fuel_And_Liquid_Biofuel_Blend_Properties_Using_Artificial_Neural_Network.pdf

Download (281kB)

Abstract

Gasoline fuel is the baseline fuel in this research, to which bioethanol, biodiesel and diesel are additives. The fuel blends were prepared based on different volumes and following which, ASTM (American Society for Testing and Materials) test methods analysed some of the important properties of the blends, such as: density, dynamic viscosity, kinematic viscosity and water and sediment. Experimental data were analysed by means of Matlab software. The results obtained from artificial neural network analysis of the data showed that the network with feed forward back propagation of the Levenberg-Marquardt train LM function with 10 neurons in the hidden layer was the best for predicting the parameters, including: Water and sediment (W), dynamic viscosity (DV), kinematic viscosity (KV) and density (De). The experimental data had a good correlation with ANN-predicted values according to 0.96448 for regression.

Item Type: Article
Uncontrolled Keywords: Fossil fuels; Biofuels; Kinematic viscosity; Density; Artificial neural network
Subjects: T Technology > TP Chemical technology
Faculty/Division: Unspecified
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 23 Nov 2012 02:45
Last Modified: 27 Apr 2016 04:28
URI: http://umpir.ump.edu.my/id/eprint/3054
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item