DATA-BASED PREDICTION OF SOOT EMISSIONS FOR TRANSIENT ENGINE OPERATION
Global vessel traffic is one of the origins responsible for air pollution. Annex VI of the IMO International Convention for the Prevention of Pollution from Ships (MARPOL) focusses on air pollution. Air pollution accrues mainly from energy conversion in combustion engines especially during transient engine operation. One significant pollutant is soot. It represents impure carbon substances in various sizes due to an incomplete combustion of hydrocarbons. This paper focusses on the data-based modelling of soot for transient engine operation in order to predict air pollution in the context of a sophisticated manoeuvring assistance system. In a first step, a stationary approach is investigated and extended for transient engine operation. If one knows about the consequences of his actions, then the role of the human is enforced to decide on energy efficient and emission reduced ship operation, especially during ship manoeuvres.
ship emissions; data processing; predictive models
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