Shipping is one of the most cost-effective and environmentally sustainable modes of transportation. Given that approximately 60% of a typical ship’s propulsive power is used to overcome frictional drag, implementing practices to reduce this resistance stands to yield substantial economic and environmental benefits, (Larsson & Raven, 2010). A promising drag reduction technique for a ship is air lubrication. Damen Shipyards Group is currently making this technology commercially available as the Damen Air Cavity System (DACS). The system reduces the frictional resistance of a ship by creating stable air cavities on the bottom hull of a ship. The air cavities cause a reduction in friction drag by decreasing the wetted area of a ship’s bottom. During the development of the DACS system, it was observed that air cavities also change the inflow into the propeller. Both the changed inflow and the frictional drag reduction affect the propulsive efficiency and required propulsive power of the vessel. This thesis aims to provide a better understanding of how the propulsive performance of a ship is affected by air cavities. Additionally, a key application for air lubrication systems is on inland waterway vessels, which frequently operate in shallow waters. However, the impact of shallow water conditions on the performance of the air cavity system is currently unknown. The research goals of this thesis are investigated with the help of computational fluid dynamics (CFD). A literature review identified the most feasible method to model a ship with air cavities i.e. representing the cavities as surfaces with a slip boundary condition. The influence of the air cavities on propulsive performance is investigated by studying the change in nominal wake field, thrust deduction, and propeller efficiency. Three ships were investigated: a cargo ship, a cruise ship, and an inland ship. The CFD results of the cargo ship were compared to sea trial data. Model test data was available for comparison of the cruise ship results. First, a grid convergence study and a sensitivity analysis were performed to investigate the accuracy of the numerical simulations and the power predictions. The biggest source of numerical uncertainty arose from the pressure drag. From the sensitivity analysis, it was found that the uncertainty of the power prediction is mainly affected by the uncertainty of the thrust prediction, followed by the uncertain propeller geometry for the cargo ship. For the cargo ship, it was found that the air cavities cause a significant frictional drag reduction. It was also found that the air cavities caused a decrease in pressure drag because they decreased flow separation at the stern. Furthermore, a strong decrease of the nominal wake fraction was observed for this ship, because the air cavities change the boundary layer on the bottom of the ship. A change in propeller efficiency was also observed because the propeller working point changes. The magnitude of the change was larger than for the other ships because this ship has a controllable pitch propeller running at a fixed rpm. When comparing sea trial data to the CFD results, it was found that CFD underpredicts the power, especially at higher speeds. Next to this, CFD predicted a larger reduction in power than measured during the trials. The prediction of the cavity length was identified as the most likely cause for the difference. A good comparison between model tests and CFD results was found for the cruise ship. It was found that the drag reduction and change in propulsive performance could be predicted reasonably accurately by modeling the air cavities as surfaces with a slip boundary condition. Furthermore, it was observed that the air cavities caused little change in propulsive efficiency on this ship. This is because the propellers of the cruise ship are located further away from the boundary layer of the ship and the wake field is therefore only slightly affected by the air cavities. On the inland ship, it was observed that the pressure drag and flow separation at the stern were influenced due to the air cavities. However, no comprehensive conclusions could be made due to scatter in the data. This is most likely due to the uncertainty present when modeling flow separation. Furthermore also for this ship, a decrease in propulsive efficiency was found because the air cavities decreased the wake fraction of the ship. Additionally, CFD simulations were conducted for the inland ship at varying water depths to assess how shallow water conditions impact the performance of the air cavity system. Since the ship’s frictional drag increased in shallow water, the total drag reduction from the air cavities also increased. Next to this, a change between pressure and flow separation when comparing air on and air off was observed. Also here, no strong conclusion could be made due to scatter in the data. Lastly, it was found that the change in wake field caused by the air cavities is larger in shallow water than in deep water. ii Based on the results of the three ships studied it can be concluded that an air cavity system affects the propulsive performance of a ship. It was found that an air cavity system reduces the wake fraction of a ship because it limits the growth of the boundary layer on the bottom of a ship. The reduction increases for ships with a high block coefficient and a large air-covered area. For a twin screw ship, the change of the wake field is less significant. The change in propeller efficiency depends on the resistance reduction, possible change of the wake field, and the original working point of the propeller. Furthermore, it was found that the thrust deduction effect is not affected by the air cavity system. It can also be concluded from the results of the cruise ship that the flow around a ship with air cavities can modeled reasonably accurately provided that the shape of the air layer under the ship is known. More research is recommended on how air cavities change the flow separation and pressure drag of a ship.

There exists no general method for analysing the efficiency of a shipyard layout through the mapping of building processes and employee movements. Therefore an Integrated Method for mapping shipyard layouts is developed. This is done by implementing multiple ways of analysing and optimising industrial processes, as found in the literature. Usage of the developed Integrated Method starts with the analysis of different Lean wastes. Next, it is important to get a good understanding of the shipyard’s building processes through communication with employees and Value Stream mapping. Subsequently, the found processes can be visualised on a map using Rainbow Models. Finally, these Rainbow Models are verified with data from GPS tracking. Using this combination of methods as one Integrated Method helps to get a good picture of how different shipyard processes run, where they take place and which bottlenecks are present. With this information, shipyards can be made more efficient and future-proof.

The probabilistic damage stability method offers great design freedom when used as a base of design. However, due to the complexity of the calculation and amount of parameters that influence the attained index, much of this freedom is not being harnessed by designers. This research tries to give the designer more insight in where to look when trying to comply with the regulations, by providing an initial subdivision design and create an overview of the influence of the parameters on the attained index. Many parameters have been found that either direct or indirect influence the damage stability calculation. A selection of parameters is chosen from this list as a starting point that are commonly used in the subdivision of large single hold vessels. A parameterised base ship has been made in the DELFTship program that is used for the execution of the optimisation and sensitivity analysis. The exploration for a suitable optimisation method and sensitivity analysis is based on the properties of these methods and method requirements that apply to this specific research. The most important requirement for both methods is the number of iterations needed to obtain a reasonable result, as the damage stability calculation can take up to 15 minutes. This resulted in the choice for the SACOBRA optimisation algorithm. To guarantee the effectiveness of the design, a second level to the optimisation is added where, the number of bulkheads is optimised, while simultaneously optimising the steel weight. During the research, the cargo hold volume was added as this proved to be an effective objective to ensure the efficiency of the design. This resulted in the change to the SAMO-COBRA algorithm, where the single objective SACOBRA algorithm was still used as a verification method and to investigate if it could be used for experimenting with certain design choices. For the sensitivity analysis the Morris method was chosen, mainly for its low number of sample points needed to converge. This method can be applied to a broad range of models and is characterised by its simplicity. However, this simplicity resulted in a relatively low amount of insight generated regarding the influence of the parameters on both the objectives as well as each other. A correlation matrix was added to further provide knowledge and insight. A sensitivity analysis by hand was performed to verify the results of both analysis methods.

The first optimisation stage showed to be a relatively fast way to determine the amount of bulkheads compared to the attained index that can be expected. However, a relatively large margin of error is observed in this stage and more information is needed to be able to make a decision on how many bulkheads is used to further optimise. The use of the SAMO-COBRA method in the second optimisation stage proved to be effective at providing the naval architect with a range of design proposals, where the probabilistic damage stability regulations were used as a base of design. Furthermore, it is shown that for single hold ships in general, the priority of the algorithm followed the influence of the parameters on the distance they were able to create between the cargo hold and the outer hull. The influence of the parameters, resulting from the sensitivity analyses endorse these claims. The Morris method showed the high non-linear and non-monotonic behaviour of the parameters that were investigated. This made it difficult to distinguish the level of influence between the parameters. The combination of the Morris method, Pearson correlation matrix and the sensitivity by hand proved to be sufficient for determining the behaviour of the probabilistic damage stability calculation. In the end, this research proposes a new foundation of designing a ship with the probabilistic damage stability regulations as a base of design. After the initial design from the two stage optimisation all other design requirements are implemented in the design. If the ship then fails to comply with the regulations, the knowledge and insight from this research can be used to increase the survivability of the ship in order for it to comply again.

This research considers Amels LE and SX super yachts. Bare hull, appended hull, and actuator disk simulations were performed using CFD, and compared to sea trial results. The results of the CFD are unique because they were generated after the sea trials were conducted, resulting in the ship speed in CFD and sea trial being similar. The results were compared using CF, CFD the relative error between measured sea trial and CFD computed resistance. The uncertainty was defined as a function of accuracy of precision, represented by the mean μ and standard deviation σ of CF, CFD. First, it was investigated if the uncertainty of CF, CFD could be reduced by including more physics in the simulations and what the impact of more variety in ship dimensions was. Subsequently, an investigation to the driving factors behind the uncertainty was conducted by performing a linear regression. After which it was investigated if the total uncertainty can be reduced by replacing experimental uncertainty by numerical uncertainty. Finally, a statistical correction to adjust the resistance was used to predict the power-speed relationship. Two correction factors were investigated. The first is based on the sample mean X of CF, CFD, and the second is CF, CFD derived from a CDF.

It was seen that including more physics reduced the uncertainty of CF, CFD. The uncertainty decreased whilst comparing bare hull to appended hull simulations, and it increased whilst comparing appended hull to actuator disk simulations. Thus, it was concluded that the actuator disk does not lead to a more realistic simulation of the flow. More variety in the ship dimensions lead to a larger uncertainty of CF, CFD, which was expected. The variance was found to be caused by the ship speed, the mean wave height and mean wind speed, and also by the block coefficient if different ship types are considered. By computing the hull efficiency ηH numerically instead of experimentally, the total uncertainty of CF, CFD was reduced. The power-speed relationship can be predicted accurately, but not precise with CF, CFD based on X. While the prediction with a CF, CFD derived from a CDF is not accurate and not precise.

With the use of simulation models, predicting and optimising the correct dynamic behaviour and parameters of a propulsion system of a ship can be performed cheap and safe. However, capturing the right dynamic behaviour is very difficult. Besides, building simulation models and determining the correct parameters is a time consuming process. With system identification, in- and output data of a controlled test are used to identify the parameters of the created grey box model structure, which reflects the underlying physical laws. A so called "fingerprint" is generated that imitates the behaviour of the system. The first attempt of system identification of a full-scale propulsion system showed promising results but asked for further research. This thesis further investigates if system identification is a suitable method to obtain the dynamic model- behaviour and parameters of a full-scale propulsion system in a short time, with the use of controlled tests.