Conference paper
Modeling of Ship Propulsion Performance
Coastal, Maritime and Structural Engineering, Department of Mechanical Engineering, Technical University of Denmark1
Department of Mechanical Engineering, Technical University of Denmark2
Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark3
Department of Informatics and Mathematical Modeling, Technical University of Denmark4
Full scale measurements of the propulsion power, ship speed, wind speed and direction, sea and air temperature, from four different loading conditions has been used to train a neural network for prediction of propulsion power. The network was able to predict the propulsion power with accuracy between 0.8-2.8%, which is about the same accuracy as for the measurements.
The methods developed are intended to support the performance monitoring system SeaTrend® developed by FORCE Technology (FORCE (2008)).
| Language: | English |
|---|---|
| Year: | 2009 |
| Proceedings: | Modeling of Ship Propulsion Performance |
| Types: | Conference paper |
| ORCIDs: | Larsen, Jan |
