Early Stage Fouling Effects Prediction for Yacht Design

Early Stage Fouling Effects Prediction for Yacht Design: A grey-box model approach using operational voyage data

de Haas, Matthew (TU Delft Mechanical, Maritime and Materials Engineering)

Kana, A.A. (mentor)
El Mouhandiz, Abdel-Ali (mentor)
Coraddu, A. (graduation committee)
Charisi, N.D. (graduation committee)
Lourenço Baptista, M. (graduation committee)

Delft University of Technology

Marine Technology

2022-07-05

In this thesis a grey-box model is developed to predict the power increase over time due to marine biofouling. Biofouling is known as the undesired adverse effect of living organisms growing on submerged surfaces. Fouling creates roughness on the hull and propeller and thus additional frictional resistance and loss of propeller efficiency, also referred to as an additional sea margin for ships due to biofouling. The International Maritime Organization (IMO) identified marine biofouling as one of the primary problems from both economic and ecologic points of view. Biofouling threatens the ecological balance of world seas by transferring invasive aquatic species and it causes a reduction in hydrodynamic performance of ships, which in turn increases fuel costs and greenhouse gas (GHG) emissions. A white-box model is first developed to predict biofouling growth together with resulting roughness, and compute increase in frictional resistance, loss of propeller open water efficiency, and change in wave resistance. With this a physical modelled prediction can be made for increase in power. This increase is then used in a data-driven model together with all other used parameters, to improve the prediction and output of the model. With the developed model, relevant questions have been answered from both a research and industry perspective. For Feadship, the developed model was applied for their yachts to give insight in power increase, fuel increase, maintenance increase, speed loss, range loss and added cost due to biofouling. With implementation of the proposed grey box and white box models, predictions can be made for ships varying in all ranges of available data. With an indication of ship profile and parameters, biofouling and its resulting sea margin can be estimated with high accuracy in early stage ship design.

Biofouling
Grey-box modelling
Machine learning
Ship design
Yachting

http://resolver.tudelft.nl/uuid:a8b798d2-e6a5-4fd5-89ea-e2bc75a249b3

Student theses

master thesis

© 2022 Matthew de Haas