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Energies 2015, 8(12), 13960-13970; doi:10.3390/en81212408

TOPSIS Multi-Criteria Decision Modeling Approach for Biolubricant Selection for Two-Stroke Petrol Engines

1
Biosystems Engineering Department, Tarbiat Modares University, Jalal Ale Ahmad Highway, P.O.Box 14115-111, Tehran 11732, Iran
2
Faculty of Engineering and Surveying, University of Southern Queensland, Toowoomba, QLD 4350, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Tariq Al-Shemmeri
Received: 15 October 2015 / Revised: 10 November 2015 / Accepted: 25 November 2015 / Published: 9 December 2015
(This article belongs to the Special Issue Energy for Agriculture)
View Full-Text   |   Download PDF [3816 KB, uploaded 9 December 2015]   |  

Abstract

Exhaust pollutants from two-stroke petrol engines are a problem for the environment. Biolubricants are a new generation of renewable and eco-friendly vegetable-based lubricants, which have attracted a lot of attention in recent years. In this paper, the applicability of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to support the process of building the scoring system for selecting an appropriate two-stroke lubricant has been analyzed. For this purpose, biolubricants (TMP-triesters) based on castor oil, palm oil, and waste cooking oil were produced and then utilized in a 200 cc two-stroke gasoline engine to investigate their effects on its performance and exhaust emissions. The results obtained from the use of the entropy technique in the TOPSIS algorithm showed that palm oil-based lubricant took up the greatest distance from the Negative Ideal Solution (NIS) and was selected as the most optimal lubricant for these types of engines. View Full-Text
Keywords: two-stroke; biolubricant; technique for order of preference by similarity to ideal solution (TOPSIS); engine oil two-stroke; biolubricant; technique for order of preference by similarity to ideal solution (TOPSIS); engine oil
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Dehghani Soufi, M.; Ghobadian, B.; Najafi, G.; Sabzimaleki, M.R.; Yusaf, T. TOPSIS Multi-Criteria Decision Modeling Approach for Biolubricant Selection for Two-Stroke Petrol Engines. Energies 2015, 8, 13960-13970.

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