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

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...

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Main Authors: B., Ghobadian, P., Nematizade, G., Najafi
Format: Article
Language:English
Published: Universiti Malaysia Pahang 2012
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/3054/1/Investigation_Of_Fossil_Fuel_And_Liquid_Biofuel_Blend_Properties_Using_Artificial_Neural_Network.pdf
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author B., Ghobadian
P., Nematizade
G., Najafi
author_facet B., Ghobadian
P., Nematizade
G., Najafi
author_sort B., Ghobadian
collection UMP
description 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.
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spelling UMPir30542016-04-27T04:28:35Z http://umpir.ump.edu.my/id/eprint/3054/ Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network B., Ghobadian P., Nematizade G., Najafi TP Chemical technology 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. Universiti Malaysia Pahang 2012 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/3054/1/Investigation_Of_Fossil_Fuel_And_Liquid_Biofuel_Blend_Properties_Using_Artificial_Neural_Network.pdf 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). (Published)
spellingShingle TP Chemical technology
B., Ghobadian
P., Nematizade
G., Najafi
Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network
title Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network
title_full Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network
title_fullStr Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network
title_full_unstemmed Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network
title_short Investigation of Fossil Fuel and Liquid Biofuel Blend Properties Using Artificial Neural Network
title_sort investigation of fossil fuel and liquid biofuel blend properties using artificial neural network
topic TP Chemical technology
url http://umpir.ump.edu.my/id/eprint/3054/1/Investigation_Of_Fossil_Fuel_And_Liquid_Biofuel_Blend_Properties_Using_Artificial_Neural_Network.pdf
work_keys_str_mv AT bghobadian investigationoffossilfuelandliquidbiofuelblendpropertiesusingartificialneuralnetwork
AT pnematizade investigationoffossilfuelandliquidbiofuelblendpropertiesusingartificialneuralnetwork
AT gnajafi investigationoffossilfuelandliquidbiofuelblendpropertiesusingartificialneuralnetwork