Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks

Lamas, M.I.; Telmo Miranda, Javier; Rebollido Lorenzo, José Manuel; Caccia, Claudio Giovanni

Use this link to cite:

http://hdl.handle.net/2183/29422

Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks

Files

ijerph-18-12823.pdf (1.62 MB)

Identifiers

URI: http://hdl.handle.net/2183/29422

DOI: 10.3390/ijerph182312823

Publication date

2021-12

Authors

Lamas, M.I.

Telmo Miranda, Javier

Rebollido Lorenzo, José Manuel

Caccia, Claudio Giovanni

Bibliographic citation

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

Abstract

[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.