Journal
OCEAN ENGINEERING
Volume 130, Issue -, Pages 351-370Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2016.11.058
Keywords
Naval propulsion plant; Fuel consumption; Trim optimisation; Ship efficiency; Sensors data collection; Numerical models; Data analytics; White Box Models; Black Box Models; Gray Box Model
Ask authors/readers for more resources
In this paper the authors investigate the problems of predicting the fuel consumption and of providing the best value for the trim of a vessel in real operations based on data measured by the onboard automation systems. Three different approaches for the prediction of the fuel consumption are compared: White, Black and Gray Box Models. White Box Models (WBM) are based on the knowledge of the physical underling processes. Black Box Models (BBMs) build upon statistical inference procedures based on the historical data collection. Finally, the authors propose two different Gray Box Model (GBM) which are able to exploit both Mechanistic knowledge of the underlying physical principles and available measurements. Based on these predictive models of the fuel consumption a new strategy for the optimisation of the trim of a vessel is proposed. Results on real world operational data show that the BBM is able to remarkably improve a state-of-the-art WBM, while the GBM is able to encapsulate the a-priory knowledge of the WBM into the BBM so to achieve the same performance of the latter but requiring less historical data. Moreover, results show that the GBM can be Used as an effective tool for optimising the trim of a vessel in real operational conditions.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available