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.
Highlights
Though compression ignition engines are widely used in marine propulsion due to their important advantages, especially efficiency, their pollutant emissions threaten public health
The present paper proposes a hybrid MCDM-artificial neural networks (ANNs) methodology to analyze several internal modifications to optimize both emissions and consumption from a compression ignition marine engine
Regression graphs graphs of of the the ANN. Using this hybrid MCDM-ANN model, 203,244,741 alternatives were analyzed under water to fuel ratios between 0 and 50%, exhaust gas recirculation (EGR) rates from 0 to 50%, overlap timings from 60 to 120°, intake valve closings from 510 to 570°, and cooling water temperatures from 70 to 90 °C
Summary
Though compression ignition engines are widely used in marine propulsion due to their important advantages, especially efficiency, their pollutant emissions threaten public health. Even stricter limitations imposed by the IMO (International Maritime Organization) and other organizations regulate emissions from ships [5,6,7,8]. Many NOx reduction measures have been developed along the years. These measures can be classified into primary and secondary. An important handicap is that most of these measures reduce NOx emissions at the expense of incrementing specific fuel consumption (SFC) and/or other emissions. In this regard, MCDM (multi-criteria decision-making) constitutes a formal tool for choosing between several alternatives which involve conflicting criteria. MCDM makes decision-making more effective when there are conflicting criteria, and minimizes human intervention in the decision process [9,10]
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