Analysis of the Pre-Injection System of a Marine Diesel Engine Through Multiple-Criteria Decision-Making and Artificial Neural Networks

Abstract The present work proposes several pre-injection patterns to reduce nitrogen oxides in the Wärtsilä 6L 46 marine engine. A numerical model was carried out characterise emissions and consumption of Several quantities, durations, starting instants were analysed. It found that can be noticeably reduced but at expense increasing as well other such carbon monoxide hydrocarbons. According this, a multiple-criteria decision-making (MCDM) established select most appropriate parameters. Besides, an artificial neural network (ANN) developed complement results analyse huge quantity alternatives. This hybrid MCDM-ANN methodology proposed constitutes useful tool design new engines.