Offshore wind farms are increasing in size and moving further from shore. Service operation vessels (SOVs) are used for offshore wind operation and maintenance (O&M) at these large far offshore sites. These large vessels typically have a smaller daughter craft (DC) on board that can assist them. This DC is however too small to provide the seakeeping capabilities needed at most far offshore sites, causing it to become essentially unusable. Previous studies at Siemens Gamesa Renewable Energy (SGRE) have looked into improving the capabilities of the DC while considering the constraints of the SOV, this was deemed insufficiently possible by Brans (2021). The second study looked at increasing the size of the DC, which saw significant improvements (Kamerbeek, 2022).

The work of Kamerbeek (2022) however raises new questions such as what is the optimum number of these larger DCs? Would another type of craft serve as a better mothership or DC? Is having the mothership perform maintenance the most efficient? SGRE is therefore interested in exploring mother-daughter concepts to perform offshore wind farm O&M activities at large far offshore wind farms, to see if these can outperform the status quo. A mothership is the home of the technicians offshore and the daughters are the craft that bring the technicians from the mothership to and from the turbines. The main research question is therefore:

What method can best be used to explore the design-space of mother-daughter
concepts for offshore wind farm O&M?

This research first focuses on understanding offshore wind farm O&M and finding the most important restrictions and challenges that need to be taken into account within a model. This has been done through a literature review and discussions with experts from SGRE. The work then focuses on selecting a modeling method and explaining the proposed method. This method is validated using a comparison with a real-life wind farm. A case study is done at the end using a dummy wind farm to demonstrate the workings of the method. The method uses a discrete-event simulation that simulates the transport of technicians to and from the turbines to estimate the performance of the concepts. Any wind farm, turbine failure rates, or fleet can be inserted into the model for analysis to ensure a wide range of applications. The performance of the fleets is assessed based on the estimated downtime/availability and emission estimates that the model produces. The financial and technical feasibility should be evaluated in the next stage when a selection of promising solutions has been made based on this first logistical analysis of the fleets. The visits are planned within the model based on the weather conditions, number of available technicians, craft availability, and the evacuation requirement.

The design space of mother-daughter concepts should be explored by running the model using the exploratory set of fleet configurations and inputting various wind farm layouts with varying realistic visit agendas and weather conditions. The output of each of these cases should then be analyzed by dividing all the fleet configurations into groups based on the craft each fleet contains. This grouping allows the performance of each type of fleet to be compared to one another, while the performance difference within the groups shows the effects of different transfer limits. The analysis should then focus on identifying cross-over points between different configurations and on selecting specific fleets based on performance and expected configuration cost.

Maritime transport represents one of the main means of product delivery and passenger transportation across the world but its impact on climate change has positioned it among the world's biggest CO2 pollutants. One of the most impacted regions in the world by maritime transport emissions is the South Pacific Region. Studies show that if climate change is not mitigated, then the increase in temperatures could lead to droughts, changes in intensity, frequency and duration of cyclone seasons, sea rise and effects on ecosystems, food security, and economy in the region. Thus, the goal within this century is to keep the global mean temperature to 1.5°C.
With this idea in mind, the regional goal of the Pacific nations was set for a decrease in carbon dioxide emissions from shipping by 40% until 2030 and complete decarbonization until 2050. A possible solution proposed by the local organizations such as USP and MCST is the implementation of Wind assisted ship propulsion (WASP) on existing and new built vessels. In that regard, a collaboration was initiated between TU Delft and the University of South Pacific to assist by developing a methodology and a practical tool that can assess the technical performance and environmental, economic, and societal impact of WASPs. For this reason, this thesis investigates the applicability of WASPs in the South Pacific Maritime Transport using a proven vessel, Sailing Vessel Kwai, as the main case study.
The method employed for the overall research was an adaptation of the Life Cycle Impact Assessment (LCIA). The LCIA encompasses the environmental impact from cradle to scrap of a certain product. The present study considered only the operational cycle of the vessel's hybrid propulsion and its impact on the triple-bottom-line items. Aspects such as the impact of manufacturing, scraping, painting or machinery waste have not been included and need further research to conclude the LCIA. The conceptualized methodology represented the theoretical foundation for the development of a practical Excel tool that assesses the technical performance of the hybrid propulsion, fuel and emissions output, norms compliance and ship finances. The novelty of the research stands in the assessment of SV Kwai from an academic perspective. Empirical methods and frameworks were used for the impact on society, ship finances and the environment. The results of the case study are promising for the future of shipping in the South Pacific region. Even though SV Kwai has the hull of a 71 years old fishing vessel and is retrofitted with sails and an oversized engine, it still accomplishes tremendous fuel reduction of around 37% per voyage. The calculations have shown that a similar trend line is encountered for the CO2 and SOx emissions. From an environmental and policy-making perspective, SV Kwai fits within the international emissions EEDI chart, CII chart mile and in the CATCH index. EEDI and CII parameters were calculated with regard to reference line formulas provided by the IMO for general cargo vessels.
Overall, the present research is an indication of an early-stage WASP design performance and its impact on the local South Pacific region. Several conclusions have been drawn with regard to the future of WASP technology in the region and its applicability.

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.