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.
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Abbreviations
- AHP:
-
analytical hierarchy process
- AM:
-
Aegle marmelos
- ANOVA:
-
analysis of variance
- ASTM:
-
American society for testing and materials
- A10:
-
AM 10% + diesel 90%
- A20:
-
AM 20% + diesel 80%
- AC30:
-
AM 20% + diesel 80% + CuO 30 ppm
- AG30:
-
AM 20% + diesel 80% + GON 30 ppm
- AC15G15:
-
AM 20% + diesel 80% + CuO 15 ppm + GON 15 ppm
- BSFC:
-
brake specific fuel consumption
- BTE:
-
brake thermal efficiency
- CI:
-
consistency index
- CN:
-
cetane number
- CO:
-
carbon monoxide
- CO2 :
-
carbon dioxide
- CR:
-
consistency ratio
- CuO:
-
copper oxide
- CV:
-
calorific value
- D:
-
density
- DF:
-
degrees of freedom
- FAHP:
-
Fuzzy Analytical Hierarchy Process
- GON:
-
graphene oxide nano sheet
- GRA:
-
grey relational analysis
- GRC (δi):
-
grey relational coefficient
- GRG (ɸi):
-
grey relational grade
- HC:
-
hydro carbons
- i:
-
test number
- IC:
-
internal combustion
- k:
-
comparability sequence
- KV:
-
kinematic viscosity
- MCDM:
-
multi-criteria decision making
- mf:
-
membership function
- n:
-
matrix size
- NOx:
-
oxides of nitrogen
- OA:
-
orthogonal array
- ‘P’ value:
-
probability value
- ppm:
-
parts per million
- RCI:
-
random consistency index
- TFN:
-
triangular fuzzy numbers
- w:
-
Eigen vector
- WC:
-
water content
- λmax:
-
Eigen value
-
: -
distinctive coefficient
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Acknowledgements
The authors would like to express their gratitude to Dr.Mini Shaji Thomas, Director, National Institute of Technology, Tiruchirappalli-620015, for her support.
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BP considered the research concept, designed the research methodology, and wrote the original draft of this manuscript. KS contributed to exploring the result outcomes, providing supervision for research performance, and editing this manuscript’s draft.
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Paramasivam, B., Somasundaram, K. Selection of smart fuel opus for diesel engine depending on their fuel characteristics: an intelligent hybrid decision-making approach. Environ Sci Pollut Res 28, 62216–62234 (2021). https://doi.org/10.1007/s11356-021-14928-w
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DOI: https://doi.org/10.1007/s11356-021-14928-w