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International Journal of Engineering Mathematics
Volume 2014, Article ID 104989, 6 pages
http://dx.doi.org/10.1155/2014/104989
Research Article

Quadratic Prediction Models for the Performance Comparison of a Marine Engine Fuelled with Biodiesels B5 and B20

1Automotive Eco-Energy and Industrial Product Standard Research Center, King Mongkut’s University of Technology North Bangkok, 1518 Pracharat 1, Wongsawang, Bangsue, 10800 Bangkok, Thailand
2Department of Automotive Engineering Technology, King Mongkut’s University of Technology North Bangkok, 1518 Pracharat 1, Wongsawang, Bangsue, 10800 Bangkok, Thailand

Received 31 May 2014; Revised 2 September 2014; Accepted 16 September 2014; Published 30 September 2014

Academic Editor: Z. X. Guo

Copyright © 2014 Chedthawut Poompipatpong. 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.

Abstract

According to Thailand’s renewable energy development plan, biodiesel is one of the interesting alternative energies. In this research, biodiesels B5 and B20 are tested in a marine engine. The experimental results are then compared by using three different techniques including (1) the conventional technique, (2) average of the point-to-point comparisons, and (3) a comparison by using quadratic prediction models. This research aims to present the procedures of these techniques in-depth. The results show that the comparison by using quadratic prediction models can accurately predict ample amounts of results and make the comparison more logical. The results are compatible with those of the conventional technique, while the average of the point-to-point comparisons shows diverse results. These results are also explained on the fuel property basis, confirming that the quadratic prediction model and the conventional technique are practical, but the average of the point-to-point comparison technique presents an inaccurate result. The benefit of this research shows that the quadratic prediction model is more flexible for future science and engineering experimental design, thus reducing cost and time usage. The details of the calculation, results, and discussion are presented in the paper.