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Blends of scum oil methyl ester, alcohols, silver nanoparticles and the operating conditions affecting the diesel engine performance and emission: an optimization study using Dragon fly algorithm.

Authors :
Afzal, Asif
Ağbulut, Ümit
Soudagar, Manzoore Elahi M.
Razak, R. K. Abdul
Buradi, Abdulrajak
Saleel, C. Ahamed
Source :
Applied Nanoscience; Sep2021, Vol. 11 Issue 9, p2415-2432, 18p
Publication Year :
2021

Abstract

The effect of the addition of different proportions of silver (Ag) nanoparticles and alcohols in milk scum oil methyl ester on the performance of engine and emission are studied. B20 blend is added with 5% of ethanol, n-butanol, and iso-butanol as ternary additives for the experimental analysis from no load to full load. Furthermore, at a fixed load, operating conditions such as injection pressure (12 and 15 bar) and injection timing (23° and 26°) are varied without and with the addition of 0.8 vol% of Ag (silver) nanoparticles to the fuel blends. Also, the concentrations of Ag nanoparticles are increased from 0.2 to 1 vol% and comparisons are made with diesel and B60 blend. Mathematical models are developed for selected features of engine performance which fits with the experimental values for the purpose of optimization using the Dragon fly algorithm (DA) by considering these models as the objective functions. The concentration of nanoparticles lowers the BSFC significantly and helps in reducing the emission with an increased percentage. Using full biodiesel, 16.6% reduction in BTE was obtained, while use of alcohols prevented this reduction approximately by 5%. A highest of 4.6% improvement was obtained with the addition of Ag nanoparticles. 4.5% reduction in HC and 13% in NO<subscript>x</subscript> emission using nanoparticles are obtained. The DA algorithm provided the same optimized value at the end of 30 iterations in different cycles of execution. Nanoparticle addition and use of pressure in the range of 20 bar gives the lowest emission from the engine. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21905509
Volume :
11
Issue :
9
Database :
Complementary Index
Journal :
Applied Nanoscience
Publication Type :
Academic Journal
Accession number :
153339296
Full Text :
https://doi.org/10.1007/s13204-021-02046-5