Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks
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http://hdl.handle.net/2183/29422
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- GI-SISTER - Artigos [37]
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Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural NetworksData
2021-12Cita bibliográfica
Galdo, M.I.L.; Miranda, J.T.; Lorenzo, J.M.R.; Caccia, C.G. Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks. Int. J. Environ. Res. Public Health 2021, 18, 12823. https://doi.org/10.3390/ijerph182312823
Resumo
[Abstract] The present work proposes several modifications to optimize both emissions and consumption in a commercial marine diesel engine. A numerical model was carried out to characterize the emissions and consumption of the engine under several performance parameters. Particularly, five internal modifications were analyzed: water addition; exhaust gas recirculation; and modification of the intake valve closing, overlap timing, and cooling water temperature. It was found that the result on the emissions and consumption presents conflicting criteria, and thus, a multiple-criteria decision-making model was carried out to characterize the most appropriate parameters. In order to analyze a high number of possibilities in a reasonable time, an artificial neural network was developed.
Palabras chave
Máquinas marinas
Motores marinos
Motores diésel marinos
Motores marinos
Motores diésel marinos
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Atribución 4.0 Internacional
ISSN
1660-4601