The use of artificial neural networks for identifying sustainable biodiesel feedstocks

Jahirul, Mohammed I. and Brown, Richard J. and Senadeera, Wijitha and O'Hara, Ian M. and Ristovski, Zoran D. (2013) The use of artificial neural networks for identifying sustainable biodiesel feedstocks. Energies, 6. pp. 3764-3806. ISSN 1996-1073

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Abstract

Over the past few decades, biodiesel produced from oilseed crops and animal fat is receiving much attention as a renewable and sustainable alternative for automobile
engine fuels, and particularly petroleum diesel. However, current biodiesel production is heavily dependent on edible oil feedstocks which are unlikely to be sustainable in the
longer term due to the rising food prices and the concerns about automobile engine durability. Therefore, there is an urgent need for researchers to identify and develop
sustainable biodiesel feedstocks which overcome the disadvantages of current ones. On the other hand, artificial neural network (ANN) modeling has been successfully used in recent years to gain new knowledge in various disciplines. The main goal of this article is to
review recent literatures and assess the state of the art on the use of ANN as a modeling tool for future generation biodiesel feedstocks. Biodiesel feedstocks, production processes,chemical compositions, standards, physio-chemical properties and in-use performance are discussed. Limitations of current biodiesel feedstocks over future generation biodiesel feedstock have been identified. The application of ANN in modeling key biodiesel quality
parameters and combustion performance in automobile engines is also discussed. This review has determined that ANN modeling has a high potential to contribute to the
development of renewable energy systems by accelerating biodiesel research


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version made available under open access.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Date Deposited: 07 Feb 2017 05:32
Last Modified: 14 Feb 2017 04:27
Uncontrolled Keywords: renewable energy; biodiesel; Artificial Neural Networks (ANN); second generation feedstock
Fields of Research : 09 Engineering > 0913 Mechanical Engineering > 091305 Energy Generation, Conversion and Storage Engineering
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: 10.3390/en6083764
URI: http://eprints.usq.edu.au/id/eprint/30549

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