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Selection of smart fuel opus for diesel engine depending on their fuel characteristics: an intelligent hybrid decision-making approach.

Authors :
Paramasivam B
Somasundaram K
Source :
Environmental science and pollution research international [Environ Sci Pollut Res Int] 2021 Nov; Vol. 28 (44), pp. 62216-62234. Date of Electronic Publication: 2021 Jun 29.
Publication Year :
2021

Abstract

Internal combustion engines are the inevitable prime movers in the contemporary engineering era. The suitability of proper bio-fuel and their blends plays a vital role in engine behaviour. This study aims to select smart fuel opus depending on Aegle marmelos (AM) fuel properties with nano additive blends for diesel engines by using intelligent hybrid decision-making tools. Physicochemical properties of CuO and novel graphene nano sheets added bio-oil combinations were studied. The assessment of an appropriate blend depends on the analysis of fuel properties. The Fuzzy Analytical Hierarchy Process (FAHP) integrated with Grey relational analysis (GRA) was employed for optimum fuel blend selection. The FAHP model was used to identify the criteria weights, whereas GRA was hired to rank alternative fuel blends. Pairwise analysis and ranking of the alternatives were compared to get the optimum fuel blend through FAHP and GRA amalgamation. The addition of nanoparticles enhanced engine performance and reduced emission. The obtained ascending order of preference of the bio-oil blends from FAHP and GRA analysis is AC15G15>AG30>AC30>A10>A20. From FAHP, GRA, and engine test results, it is observed that AC15G15 opus is the most suitable fuel blend for diesel engines. Lower fuel consumption (0.37 kg/kW hr) and emissions (CO level of 0.21%, which is 0.34% for diesel, HC value of 134 ppm, which is 184 ppm for diesel) of AC15G15 aids in contributing towards a green and clean environment.<br /> (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Details

Language :
English
ISSN :
1614-7499
Volume :
28
Issue :
44
Database :
MEDLINE
Journal :
Environmental science and pollution research international
Publication Type :
Academic Journal
Accession number :
34184231
Full Text :
https://doi.org/10.1007/s11356-021-14928-w