The ongoing pursuit of efficiency in the shipping industry is driven by both economic and environmental objectives. While historically focused on reducing fuel consumption to enhance market competitiveness, recent regulations such as the International Maritime Organisation’s Energy Efficiency Design Index (EEDI) and Energy Efficiency Existing Index (EEXI) have emphasized the need to minimize harmful emissions. To achieve these goals, Simulation-Based Design (SBD) and Computational Fluid Dynamics (CFD) have become essential tools for optimizing ship design. This research aims to develop and implement an optimization strategy to minimize the propeller power required for a vessel to maintain a constant speed by refining the aftbody shape while accounting for propeller-hull interaction effects.

The study addresses a critical gap in current methodologies, where many existing optimization strategies neglect propeller effects and studies including propeller effects use too computationally intensive methods to be used in an optimisation strategy. The research explores strategies to reduce computational load, ensuring a balance between accuracy and efficiency. Key questions include determining the optimal geometrical parameters for aftbody design, refining CFD procedures to be computationally light yet accurate, incorporating propeller effects efficiently, and identifying the most effective optimization algorithm.

The research findings reveal that by varying specific geometrical parameters, such as the aft arc angle and transom angle, an approximately 10\% reduction in required propeller power can be achieved. The study also evaluates different strategies for reducing computational load, including a grid refinement study and the exclusion of free surface effects, while noting the trade-offs in accuracy. The use of the virtual disk method to model propeller effects is identified as the most practical approach given computational constraints. Among the optimization algorithms tested, the NSGA-III algorithm is found to be the most effective, offering significant improvements with fewer computational resources compared to alternatives.

Overall, the research demonstrates that the proposed optimization setup can lead to a significant reduction in propeller power, contributing to the development of more efficient ship designs. However, further research is needed to refine the exclusion and estimation of free surface effects to ensure broader applicability across different vessel designs.

To reduce the greenhouse gas emissions of ships, hybrid power systems are becoming more common. Hybrid systems combine power generation with energy storage. The energy storage enables the power generating components to run at more efficient operating points. A well known combination is that of a diesel genset and a battery. The ideal combination of the type, size, and amount of power system components depends highly on the operating profile of the vessel. However, this operating profile can vary greatly between voyages, or during the lifetime of a vessel, thus changing the ‘ideal’ power plant. A modular power system (MPS) can provide the solution: a reconfigurable power plant, where components can be added, removed, or replaced.
To control the power-split between the different components an energy management system (EMS) is required. Most EMSs are designed and optimized for a single power plant configuration. This means they are not capable of dealing with an MPS. For this thesis an EMS was developed which is capable of dealing with an MPS: an MPS EMS. The developed EMS was made for ships with electric propulsion. An additional requirement was for the EMS to be real-time capable, so it can be used outside of a simulated environment, i.e. in a real ship. The objective of the EMS would be to minimize fuel consumption.
It was investigated which EMS control strategy would be suited for an MPS EMS. The equivalent consumption minimization strategy (ECMS) combined with the dual decomposition method was found to be suited for this purpose.
The developed EMS can automatically adapt all parameters responsible for stable control of the system. It does this based on the properties of the installed components. Most important of these properties are: minimum and maximum power output, maximum ramp-rate, and the efficiency curve.
The EMS was tested with four different combinations of installed components, and two different operating profiles. Additionally, the effect of a component failure during a voyage was tested. A rule based (RB) EMS and a mixed integer linear programming (MILP) global optimization were used as benchmarks for the fuel consumption. The results show that the developed EMS is capable of controlling various power plant configurations in different conditions, while keeping all components within their allowed operating ranges. For one of the tested operating profiles the fuel consumption using ECMS was 1.9-4.0% higher than when using the global optimization, which is comparable to the results found in literature. However, for the other tested operating profile the developed EMS was outperformed by even the RB EMS, by 1.1-2.1%. This was caused by inaccuracies of the approximation used for the efficiency curve of the gensets. In the simulations where one of the gensets fails during the voyage the EMS was able to automatically adapt to optimize fuel consumption using only the remaining components. Fuel consumption did increase slightly compared to no failures, as expected.

In recent years, the offshore wind energy industry has been facing significant barriers, ranging from supply chain disruptions to financial challenges due to rising commodity prices and increasing inflation. To keep offshore wind energy competitive, more efforts towards reducing costs and accelerating project timelines are needed. The optimization of load calculation processes, which are central services in the development of any wind energy project, would significantly contribute to the achievement of these goals.

Conventionally, load calculations are performed using high-fidelity numerical models that simulate the dynamic response of the turbine or wind farm. Although this approach is highly reliable, it is computationally intensive. For applications requiring a large number of load evaluations, this translates into high costs and long project timelines. Load response models have been developed as a data-driven alternative to the high-fidelity numerical models, offering sufficiently reliable load estimates at a cheaper computational cost. However, currently-existing load response models suffer from key limitations pertaining to their applicability to modern offshore wind farms.

This thesis aims to develop a load catalogue, consisting of a database of fatigue loads that can serve as a foundation for a load response model, that better represents the loading conditions in modern offshore wind farms. The database is constructed by running dynamic simulations for a variety of operating conditions tailored to represent those observed in offshore sites. In addition, the thesis seeks to use the catalogue to study the impact of employing the different wind and wake models recommended by the IEC 61400-1 standard on calculated loads. Specifically, it does so by comparing the 90th percentile and Weibull distribution turbulence intensity models, the Mann and Kaimal turbulence models, and the Frandsen and DWM wake models with respect to annual equivalent fatigue loads.

The analysis reveals that using a 90th percentile for the turbulence intensity overestimates the annual fatigue loads obtained when sampling the turbulence intensity from a Weibull distribution by an average of 20% for tower base loads and 6% for blade root loads. Moreover, it shows that the Kaimal and Mann turbulence models lead to significantly different fatigue load estimates. Furthermore, it finds that Frandsen's effective turbulence model consistently predicts higher loads than the DWM model for inter-turbine spacings smaller than 5 rotor diameters, but it can predict lower loads for inter-turbine spacings exceeding 5 rotor diameters.

The study concludes that using a 90th percentile turbulence intensity might lead to overly conservative designs, which can be avoided by using a Weibull distribution that accurately characterizes site turbulence. Also, it suggests that a combined modeling approach to long-term fatigue calculations that selectively toggles between the Kaimal and Mann turbulence models based on the short-term environmental conditions is expected to yield more accurate load estimates compared to employing a single model exclusively. Lastly, it implies that the effective turbulence model might not always be conservative, especially for wind farms with large inter-turbine spacings.

Ultimately, this research culminates in the delivery of a valuable instrument, the load catalogue, that enhances decision-making in the preliminary stages of project development and facilitates the development of better load response models. Additionally, it enriches the theoretical understanding of load calculation methodologies, paving the way for the development of better load calculation techniques.

New methods of ship propulsion are required to meet the targets for reducing global emissions of greenhouse gases. Hydrogen-powered fuel cells can be used to greatly reduce emissions, facilitating renewable shipping. Fuel cell durability is recognised as a large barrier to widespread fuel cell application. The goal of this graduation project is to develop a model which can be used to examine the trade-off between hydrogen consumption and degradation in the operation of a fuel cell/battery hybrid ship. The main research question is defined as follows:

”How does incorporating fuel cell degradation in the energy management system of a hybrid marine propulsion system affect the resulting fuel consumption and degradation?”

An optimisation approach is used to develop an energy management system. A quadratic mathematical model is constructed using the fuel cell’s polarisation curve as its basis. Linear relations for a fuel cell’s current-voltage relation are used to describe the fuel cell power as a quadratic current-power relation. Fuel cell degradation is included in the model by defining various operating conditions and relating them to degradation rates reported in the literature. In turn, the degradation influences the polarisation curve, thereby limiting the fuel cell’s performance. This quadratic approach to modelling the interplay between fuel cell degradation and the fuel cell’s performance is the main contribution to the literature.
The proposed energy management system is used to determine a vessel’s optimal operation, depending on the objective function applied. Two objectives are defined: minimisation of fuel consumption and minimisation of fuel cell degradation. Besides testing these single objectives, a weighted-sum approach to multi-objective optimisation is carried out using hydrogen and fuel cell system costs.
The optimal operation of the vessel is analysed based on key performance indicators such as fuel consumption, fuel cell degradation and operating costs. Incorporating fuel cell degradation in the energy management system leads to a reduction in degradation of up to 33% for the long-term simulation of the case study applied in this thesis when compared to the results for the minimisation of fuel consumption. A large increase (50%) in fuel cell lifetime can be accomplished with a very limited increase in hydrogen consumption (0.5%).
This research contributes an intuitive modelling method for the interplay between fuel cell degradation and the fuel cell’s performance. It provides insight into the considerations between fuel cell degradation and hydrogen consumption while operating a hybrid vessel, addressing a small part of a technical solution to mitigating emissions.

The development of biofouling on ship hulls is known to be deeply damaging for the overall performance of the vessel. The real effects of soft fouling, especially due to biofilms and diatoms, are however not yet understood and precisely defined. The current work numerically assesses the influence of an increase in surface roughness due to soft biofouling over the hydrodynamic performance of a containership. The simulations are carried out through MARIN’s in-house software ReFRESCO. Unsteady free-surface computations are used to evaluate both the resulting frictional drag, and the wave profile modification for different input surface roughness values. The results show that frictional resistance at 14 knots is increased of up to 45% for a limit equivalent sand-grain roughness height ks = 300 μm, correspondent to biofilms. Residuary resistance at the same speed suffers decreases of maximum 2.5% in the same range. These consist in hull pressure variations in the aft and transom areas of the vessel, and in small height differences in the wave pattern. A dataset obtained from monitoring of the containership for five years is used to study the added frictional resistance evolution due to roughness. Holtrop & Mennen
procedure integrated with environmental variables show a maximum increase of ΔCF = 1.4 · 10−3. The methodology proves useful to identify potential drydocking periods, and to provide an overview
of the added resistance trend. It should however be implemented with Machine Learning models to improve accuracy, in case the precise influence needs to be assessed. A novel comprehensive soft
fouling growth model is created to assess the surface roughness ks and ΔCF time evolution. This constitutes one of the few attempts in the literature to create a model that simultaneously considers the
effect of multiple environmental and operational variables based on the GPS position. Light intensity, sea surface temperature, draft and concentration of nutrients. Increases of up to 100 kN in resistance
and of ΔCF = 0.001 are observed if only diatoms are considered are integrated. Temperature and nutrients result to be more relevant for growth, in comparison to light intensity and draft. A sensitivity
study is also carried out to prove the small dependence on the choice of the analytical approach. A comparison of the growth model + CFD results with data processing show that the analytical procedure
provides a good indication on the growth trend, while added resistance intensity is underestimated in the order of ΔCF = 4.65 · 10−4.

Chain belt conveyors have become a popular choice for transporting materials in diverse industries. The primary driving force behind these conveyors is the gearmotor, which is composed of an electric motor and a gear unit. The industrial electric motor market is estimated to be 21 billion USD and consumes up to 70\% of the electricity by the industry. However, research on chain belt conveyors systems remains limited, leading to poor maintenance strategies and inadequate understanding of their efficiency. The aim of this paper is to develop a digital twin for condition monitoring, applicable to industrial gearmotor-driven chain belt conveyor systems. To achieve this, the current state-of-the-art and industry practices were analysed, focusing on SEW Eurodrive as a representative for industrial industry. A literature review was conducted to explore predictive maintenance, digital twins and condition monitoring in the context of chain belt conveyors. Consequently, this has culminated in the development of a novel chain belt conveyor model, based on fundamental mechanical analysis of the chain belt conveyor, while also acknowledging the limitations associated with industrial settings. In order to accomplish this objective, parameter estimation was performed for system identification using data collected from physical chain belt conveyor systems. Additionally, various methods have been proposed for anomaly detection, which include the utilization of estimated parameter thresholds, frequency domain analysis, statistical residual analysis and the assessment of the transport loss factor. Verification and validation have been performed using data from a chain belt conveyor system. Eventually, a case study was conducted with promising results in terms of robustness and accuracy. In the industrial setting, dynamic weighing attained a benchmark accuracy of 95\%. Further research, with data over longer periods of time, is required to establish degradation patterns and optimize the model for broader applications.

Over the coming decades the worldwide fleet of ships will have to change to reduce emissions. Hybridisation of the propulsion system is a stepping stone to full electrification, which is required to reduce emissions of the maritime sector to zero. In hybrid propulsion systems, clutches are used to switch between drive engines when transitioning between operational modes. The operation of clutches is indicated to generate significant disturbances in propulsion systems, however, this impact is overlooked in hybrid propulsion simulation studies in the scientific literature. The identified research gap is addressed in this thesis by simulating propulsion mode transition in a hybrid propulsion system and analysing the impact of clutch operation, using a model developed for this purpose. A hybrid propulsion system is defined by introducing multi disk wet friction clutches in a reference propulsion system consisting of a 9.1 MW diesel engine in parallel with a 3 MW electric motor. A broad scope of impact measures, that includes the electric load on the power system and the temperature development of the clutch, is defined and the system is thoroughly modelled to enable evaluation of these measures. The transmission system is modelled with a higher fidelity than typically applied in propulsion system simulation studies to enable assessment of the basic vibratory behaviour of the transmission system. The considered propulsion modes transitions are between diesel and electric propulsion. To enable these transitions, three transition control approaches with an increasing degree of sophistication are implemented. The developed model is used to perform simulations, from which it is concluded that torsional vibrations, gear hammer and a drop in propeller speed characterise the significant impact of clutch operation on hybrid propulsion systems in propulsion mode transitions. It is also concluded that the impact of clutch operation can be limited by implementing an appropriate propulsion control approach for the transition. A torque controlled handover of drive torque between engines is identified as a suitable approach. However, the induction machine switching from torque to speed control introduces power peaks in the load profile that have the potential to severely disrupt the stability of the ships power system. It is finally concluded that the temperature development of the clutch during the propulsion mode transitions is not significant. It is shown in this thesis that there can be a significant impact on the propulsion system as a result of the operation of clutches in propulsion mode transitions. Therefore, this impact has to be taken into consideration when designing hybrid propulsion systems. The model described in this thesis can be used to predict the impact of clutch operation in the early stages of the design process. Furthermore, the model can be used to develop and evaluate propulsion mode transition control approaches.

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.

Floating photovoltaic (FPV) is an emerging concept. Potential is recognized in combining FPV and off­ shore wind farms to create an offshore wind and solar farm. One of the remaining uncertainties around the potential of an offshore wind and solar farm is the value of the operations and maintenance cost. As one of the main contributing factors to operations and maintenance costs of offshore wind farms is the accessibility, integration of the transport for maintenance of the wind turbines and solar units can minimize the costs. By means of a route and scheduling optimization tool the optimal route and sched­ ule of maintenance support vessels for a virtual OWSF is investigated. The research indicates that the optimal route and schedule of maintenance support vessels for a virtual OWSF does not include integration of the transport. The main reason is the low costs of an RHIB compared to the cost of a CTV or SOV. However, the optimal route and schedule is very case dependent. Thus recommended is to apply the model to multiple case studies to form a general conclusion.

In this thesis, a simulation cost model is presented that can be used to assess the cost-effectiveness of a selection of PdM programs. The proposed model combines a discrete event simulation (DES) model with a cost model. It is specifically designed to analyse the PdM programs for the vacuum compressor pumps at Duyvis. All the PdM programs proposed will work with vibration analysis to detect bearing failure. The simulation model will focus on the sample frequency and detect-ability of a PdM program. The sample frequency is related to maturity levels, and the detect-ability is related to detecting the different stages of bearing damage. The goal is to use the proposed simulation cost model to assess a selection of PdM programs on their overall cost and reliability.

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.

Vessel platform automation developed notably categorizable in two behaviors: reconfiguration and collaborative motion control. This work explores integration of both behaviors in a single system. Fundamental system characteristics of both behaviors are analyzed to create understanding of the varying design approaches. A multi-vessel platform model approximation is proposed that expresses all module models in one generalized platform coordinate while retaining directional dependent effects. Automated reconfiguration and collaborative, coordinated dynamic positioning are implemented within a single framework. The multi-robot control stucture consists of guidance, navigation & control layers, rather than single systems, where topology changes with platform configuration.

Wave run-up is the vertical water uprush that occurs when an incident wave impacts on a surface-piercing body. This phenomenon is particularly relevant when waves of high steepness interact with large structures as a result of significant nonlinear interactions between incident and diffracted wave fields. The extent can be further amplificated in the presence of appreciable motions of the structure as radiated waves take part in the network of wave-wave interactions.

Underprediction of the run-up height exposes ships and offshore platforms to severe localised structural damages. A sufficient deck elevation proves to be mostly effective in overcoming these issues. Over the last decades, sustained research has been produced on wave run-up by fixed structures. However, a complete understanding of the effects of wave radiation by moving structures on the run-up flow is still far from being achieved.

In the wake of a recent publication dealing with the presence of the surge motion, this graduation project aims to take a further step forward in the research by evaluating the wave run-up amplification due to heave. With this purpose, a validated numerical wave tank is established in ComFLOW and the case study of a two-dimensional rectangular structure is addressed.

As a side objective, a piston-type wavemaker based on second-order wave generation theory is first implemented in ComFLOW. The performance of the wave board wave generation method is thoroughly discussed with regard to accuracy, propagation stability, numerical dissipation and dispersion in the context of nonlinear regular waves.

The use of fossil fuels and their impact on humans and nature is becoming a bigger concern worldwide. An interesting concept to lower polluting emissions coming from maritime engines is the combined use of a dual-fuel engine and an underwater exhaust system. In the dual-fuel engine natural gas is used as the main fuel type. It is seen as a cleaner alternative to the traditional fossil fuels that are being used. In order to ignite the air-gas mixture in the cylinder a small amount of diesel fuel (pilot fuel) is used, therefore making it a dual-fuel engine. Some advantages of using an underwater exhaust system are no direct emissions into the atmosphere, increased space on decks and reduced noise from the exhaust. However the downside is that such a system causes back-pressure effects which can deteriorate engine performance. So far research on these back-pressure effects on a dual-fuel type engine is lacking, therefore this thesis focuses on the static back-pressure effects on a dual-fuel engine.
For this purpose experiments were performed on a constant pressure turbocharged, 4-stroke dual-fuel engine. Engine performance and emissions were recorded for load points along the propeller and generator curve for three cases of back-pressure. The back-pressure was controlled by a butterfly valve in the exhaust pipe of the engine. Due to the fact that this butterfly valve could only be controlled manually, the back-pressure during the experiments could not be kept at a constant level. Also the engine experienced an absolute back-pressure of 1.15 bar with the valve fully open which was already quite high. And in the natural gas that was used a substantial amount of hydrogen was present. An existing diesel engine model (DE-B) that was developed at the TU Delft was then adapted to turn it into a dual-fuel engine model. It is a mean value first principle (MVFP) model. This dual-fuel MVFP model was then matched to the tested engine by using the experimental data. After the matching the model was used to test levels of back-pressure that could not be reached experimentally, due to engine limits, to see the effect on engine performance at these levels. The results were then analysed to see what the critical engine parameters are for the limits of the engine.
The experimental results showed that at low power more pilot fuel is needed to combust the gaseous fuel. It was also clear that there was a changing combustion efficiency for the gaseous fuel along the propeller curve. For the part load conditions the combustion efficiency was lower than at low or high power. For the generator curve the total efficiency was more constant, but always lower than the efficiency of the propeller curve. The results also showed that with increasing back-pressure the fuel consumption decreased for both the pilot and gaseous fuel, with the exception of the gaseous fuel flow at part load for the propeller curve. The recorded emissions showed lower levels of O2, CO and unburned hydrocarbons and higher levels of CO2 and NOx with increased back-pressure. Looking at the emissions in combination with the fuel flows, they showed signs of improved combustion efficiency with increased back-pressure. Increasing the back-pressure caused lower pressures and temperatures at the inlet side of the engine and higher pressures and temperatures at the outlet side. So for the thermal loading of the engine the outlet side is the critical one. The tested dual-fuel engine had a waste-gate installed. The model runs with higher levels of back-pressure showed that the pressure on the inlet side could become so low, that the pressure at which this waste-gate becomes active is no longer reached. This causes high pressures and temperatures before the turbine and high temperatures of the exhaust valve. The model also showed that at high levels of back-pressure the flow through the turbine becomes too low and not enough air is being put into the engine, so the air-excess ratio becomes too low, making the air-excess ratio also an important parameter for the engine limits. Finally it was shown how the dual-fuel MVFP model can be used to define acceptable limits of back-pressure for the air-excess ratio, exhaust valve and outlet receiver temperature.
The main recommendation for further research is to investigate the combustion efficiency of the gaseous fuel. Both the fact that at part load the efficiency was at it worst and the lower fuel consumption when back-pressure was increased need to be looked at. This will also help with improving the current dual-fuel MVFP model. Next to that it would be interesting to see what happens with different types of gaseous fuel and how the engine performs under a fluctuating back-pressure as induced by waves.