Abstract
The primary objective of this work was to enhance the performance and emission of the computerized variable compression ratio (VCR) diesel engine fuelled with pentanol/Calophyllum inophyllum (CI)/diesel fuel blends. Based on the prerequisite for the current research, response surface methodology (RSM), an optimization technique, was adopted for the process parameters compression ratio (CR), load and fuel blends, and the optimized responses like brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), oxides of nitrogen (NOx), carbon monoxide (CO), carbon dioxide (CO2), hydrocarbon (HC), and smoke were revealed with the help of Derringer’s desirability approach. From the results, it is notified that pentanol-fuelled engine showed better performance and emissions at 17.5 CR, P20C20 (pentanol 20%+Calophyllum inophyllum 20%+diesel 60%) blend and 2.5 bmep (brake mean effective pressure) load conditions. The observed mathematical models and validation experiments show that the VCR diesel engine exhibits maximum efficiency and minimum emissions at the optimized input parameters.
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Abbreviations
- CI :
-
Calophyllum inophyllum
- DI :
-
Direct injection
- CO :
-
Carbon monoxide
- CO 2 :
-
Carbon dioxide
- NO x :
-
Oxides of nitrogen
- NO :
-
Nitric oxide
- HC :
-
Hydrocarbon
- VCR :
-
Variable compression ratio
- P10C20 :
-
Pentanol 10%+Calophyllum inophyllum 20%+diesel 70%
- P15C20 :
-
Pentanol 15%+Calophyllum inophyllum 20%+diesel 65%
- P20C20 :
-
Pentanol 20%+Calophyllum inophyllum 20%+diesel 60%
- CI20:
-
Calophyllum inophyllum 20%+diesel 80%
- BTE :
-
Brake thermal efficiency
- BSFC :
-
Brake specific fuel consumption
- bmep :
-
Brake mean effective pressure
- CR :
-
Compression ratio
- MDS:
-
Modular diagnostic system
- RSM:
-
Response surface methodology
- ANN:
-
Artificial neural network
- DOE:
-
Design of experiments
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Ramakrishnan, P., Kasimani, R. & Peer, M.S. Optimization in the performance and emission parameters of a DI diesel engine fuelled with pentanol added Calophyllum inophyllum/diesel blends using response surface methodology. Environ Sci Pollut Res 25, 29115–29128 (2018). https://doi.org/10.1007/s11356-018-2867-4
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DOI: https://doi.org/10.1007/s11356-018-2867-4