The technological advancements in weapons and weapon systems continues to increase, and with these advancements the risk in safety increases as well. These weapons pose a great threat to naval task forces. In order to carry out missions safely, the task forces need to be equipped with defensive weapon systems. In this thesis the focus lies on air defense weapon systems. Originally, the selection of air defense weapon systems is done for a singular vessel, not taking into account the influence the other vessels in the task force may have on the operational effectiveness of the weapon systems in a group setting. This report presents an investigation into the selection and distribution process of weapon systems across a task force, while balancing the effectiveness and the costs of the weapon systems. The developed model utilizes a Weapon-Target-Allocation model in combination with the NSGA-II algorithm to generate the selection and distribution of weapon systems across the task force.

The growth of the offshore wind market is accompanied by larger wind farms, whose electricity needs to be transported to shore.
Offshore converter stations are used for combining and converting the electricity generated from the wind farm for transport to shore.
The increase in the electricity produced by wind farms has led to converter stations growing as well.
This creates an issue, as for many current lifting vessels they are becoming too heavy to lift and place offshore.
Furthermore, new wind farms are currently still being built in shallow water, so vessels should be designed taking this into account if they are to place the converter stations.
As lifting by crane is preferred in the industry, this research looks into the use of semi-submersible crane vessels for lifting converter stations, as these are the largest crane vessel category and have the greatest lifting capacity. \par

Existing semi-submersibles are designed for operating in deep water and thus with little concern for limited water depth.
Consequently, current vessels have large draughts for working in rough seas but are not able to work in the shallows.
The performance of semi-submersibles in shallow water is a little researched topic, both in terms of designing these vessels for this condition as well as operating them at limited draught.
For this reason, this research proposes a new early-stage design model that includes the fundamental limitations for lifting in shallow water and addresses the research question:
\emph{How can the design of semi-submersible crane vessels be improved to lift at least 11,000 tonne substations in shallow waters of less than 30 m in weather conditions with significant wave heights of up to 2.5 meters?}
To answer this research question, the research looks to identify trends of optimized vessel parameters for the design of semi-submersibles for use in shallow water.\par

To find optimized designs for the lifting of converter stations in shallow water, a parametric model will be made within this research, which is then optimized.
This model will make use of the IOC-SAMO-COBRA algorithm to find designs that are optimized for three conflicting objectives.
These objectives are the light weight of the vessel, the water depth that it requires to lift a representative converter station and the operability of this vessel in waves at the required draught.
Applying these objectives, Pareto optimal solutions will be calculated for this situation.
By analysing the results of the model, trends are found for the optimum configuration of the vessel parameters for lifting 11,000 tons converter stations in shallow water.

This thesis compares maintenance strategies for the Royal Netherlands Navy to optimize cost, man-hours and downtime. A decision support model was developed to evaluate different mixes of Corrective Maintenance (CM), Time-Driven Scheduled Maintenance (TDSM), and Condition-Based Maintenance (CBM) using SAP data and expert input. Results show that CBM application (~20–50%) reduces long-term costs for high-criticality systems, while man-hour efficiency sometimes favors more CM due to underreported labor in existing data. The model supports tailored, data-driven maintenance planning across vessel types and system groups.

This thesis develops and demonstrates a mission-oriented, early-stage design framework for mid-size (40–90 [m]) Offshore Patrol Vessels (OPVs). The approach integrates hybrid scaling (geometric and targeted parametric variation) with multi-objective optimisation (MOO) in a Systems Engineering / Set-Based Design (SE–SBD) workflow. A parametric parent-hull model was implemented in CAESES and varied in principal dimensions and selected hull parameters. Performance was evaluated using Holtrop–Mennen resistance, intact-stability (GZ) analysis, and strip-theory RAOs aggregated into a multi-heading Seakeeping
Index (SKI). The optimisation process combines Design of Experiments (DoE), surrogate modelling, and a MOGA-based global search. Objectives reflect key drivers (SKI, Stability Index (SI), total resistance RT , and lightweight LW T ), while feasibility is enforced through GM /B limits, roll-period (Troll), and a range constraint.
Verification through hypervolume convergence and trend analysis confirmed robust optimisation behaviour, while validation against tank, CFD, and stability booklet data for a 45 [m] reference OPV demonstrated geometric fidelity and early-stage accuracy. The framework efficiently generates Pareto sets that reveal trade-offs between endurance, comfort, stability, esistance, and weight, supporting mission-aligned design choices.
The main contribution of this work is the development of a robust, adaptive, and mission-driven optimisation framework for OPVs. It explicitly integrates nonlinear scaling effects, dynamic stability criteria, and mission requirements within a single optimisation envelope. Beyond reproducing established naval-architectural behaviour, the framework advances early-stage practice by treating SKI and SI as explicit optimisation objectives and by embedding range and Troll as feasibility constraints. Its adaptive structure allows objectives, variables, and constraints to be tailored flexibly to owner, shipyard, or designer requirements, making it a practical decision-support tool for concept design.

This thesis investigates how alternative fuels and energy reduction technologies influence the technical and economic viability of research vessels under market uncertainties and varying operational profiles. The study addresses the growing need for decarbonisation in the maritime sector, where research vessels face particular possibilities due to limited regulatory requirements and constraints due to their demanding mission requirements.

Research vessels, which are exempt from many regulatory emission frameworks, operate under highly variable mission profiles that challenge conventional decarbonisation approaches. The review identifies a significant gap in existing studies, which typically overlook the unique operational demands of these vessels.

The literature analysis evaluates a wide array of fuels - including fossil based fuels with lower carbon intensity such as LNG and LPG, renewable, diesel like fuels as HVO, hydrogen carriers as ammonia, hydrogen, and sodium borohydride, alcohol fuels as methanol, as well as metal-based fuels like iron powder -, wind assisted propulsion systems, and energy reduction methods as exhaust heat recovery and solar systems. Assessment is done on physical and chemical properties, emissions, safety, technological readiness and availability, and costs.

To handle the complex and uncertain decision environment, the study proposes the Many Objective Robust Decision Making Framework combined with an Epoch-Era Analysis that models the most important uncertainty, namely the various operational profiles. This methodological foundation allows for evaluating the technical and economic feasibility of many different propulsive combinations across a wide range of plausible futures.

The subsequent analysis shows that no single configuration is universally optimal across all conditions. Fossil and diesel-like fuels such as LNG and HVO remain technically feasible but offer only slight emission reductions. Methanol-ICE configurations emerge as the most robust low-carbon option, offering technical feasibility across all scenarios and significant emission reduction potential. Ammonia-ICE solutions perform well under lower requirements and can approach carbon neutrality if sustainably produced. The integration of energy reduction technologies such as exhaust heat recovery and wind-assisted propulsion improves performance, but effects remain context-specific and do not fundamentally alter the main trade-off’s between cost and emissions. The analysis further shows that blended fuels (e.g., grey/green methanol or ammonia) can serve as transitional pathways, enhancing economic viability while preparing vessels for a green fuel future. A design-oriented iteration of the MORDM indicate that hull form adjustments can improve robustness, however, more detailed calculations need to be done.

In conclusion, the findings underline that future-proof research vessels will need to adopt technically feasible, robust fuel strategies that enable compliance with long-term climate goals. Methanol, and to a slightly lesser extent ammonia, currently offer the most promising pathways, while fossil and diesel-like fuels cannot ensure sustainability under future conditions.

Wind assisted vessel hull optimization is more expensive than traditional vessels. This thesis tests if multi fidelity modeling may be a solution to reduce the computational cost of optimizing wind assistedvessel hulls. A Bayesian optimization framework was coded that can use both single fidelity and multi fidelity data. A surrogate test problem of a 100 meter long wind assisted vessel was created based on CFD data and an empirical model. The first experiment compared the performance of the single and multi fidelity algorithms. The second experiment evaluated the impact of a better low fidelity by using weighted averages of the CFD and empirical as the low fidelity model. In the third experiment, the resulting vessels from optimizations with CFD and empirical models were compared to validate the necessity of including CFD in the optimization of wind assisted vessels. The results of experiment one show that multi fidelity is only slightly faster, but has a larger spread meaning the slowest optimization takes longer. Experiment two showed that a better low fidelity model drastically reduces the number of iterations needed to perform an optimization. Experiment three showed that the vessels optimized using CFD differ significantly from those optimized with empirical methods. Thus, multi fidelity modeling provided very limited improvements for the optimization of a wind assisted vessel when using empirical models and CFD. Significant improvements are possible with better low fidelity models. Lastly, empirical models used for wind assisted vessels are have limited usability for optimization.

Modularity is often mentioned as a method to make a vessel’s design flexible during its lifetime. However, literature often focuses on ways to apply modularity to naval vessels instead of asking if modularity improves the vessel, or the organizational process, at all. This paper aims to build a framework to give the naval architect valuable insights into the possible benefits and the technical impact of modularity application. When a system is
deemed a feasible module, a final evaluation is performed to assess if the modular variant of the system actually improves the vessel or the organizational process.

This research presents a framework consisting of a Modular Function Deployment (MFD), Analytical Hierarchy Process (AHP), and Knowledge Based Engineering (KBE) model to assess the suitability and technical feasibility of modular systems. The MFD aims to identify high-potential modular systems based on modularity drivers defined and rated by the naval architect. Next, the AHP aims to map the most important functions of the vessel. Since modularity always comes with increased weight, the naval architect can use the AHP to ask
themselves if the system fulfills a function that is important enough to embrace the increased weight. With the KBE model, the technical impact of modular systems can be assessed in terms of weight, estimated draft, and stability. When a system scores high on the MFD, it indicates the system would benefit from modularity. When its accompanying function scores high on the AHP, it indicates the system fulfills an important function. The technical impact of making the system modular can be assessed with the KBE model. If the technical impact is
deemed acceptable, the system can be labeled as a ‘feasible’ module. The final effectiveness assessment will indicate if the feasible module actually improves the vessel’s design or the organizational process. This way, a framework will be developed which gives the naval architect valuable insights into the potential benefits and costs of modularity.

A case study will be presented on a landing platform dock and the future air defender (FuAD) of the RNLN. Results show the FuAD has higher-potential systems for modularity, so the KBE model is applied to only the FuAD. In the KBE model, an air surveillance radar and Laser-Directed Energy Weapon (LDEW) are modeled as a non-modular system and then as a modular variant. This way, the impact of making a system modular is assessed. The KBE model results in a technically feasible module for the air surveillance radar and LDEW. The final effectiveness assessment results in a preference for a non-modular air surveillance radar and a modular
LDEW. This shows that modularity does not necessarily improve the system and a structural way to approach modularity and compare it to a non-modular variant is required.

The framework can be applied to a wide variety of vessels, including commercial vessels. The framework uses generally applicable methods, and by combining them in a structural way the decision-making on whether to use modularity or not can be improved. For naval vessels, the effectiveness depends on the intentions of the end user. By qualifying the expert opinion using AHP, both by identifying the most important functions and the final evaluation, this intention is integrated into the framework. This also personalizes the outcome: based on the intentions of the end-user, completely different outcomes can be retrieved from this framework. After computing the framework for a specific vessel type, the results can partially be applied to other vessel types, within the same organization due to the end-user intentions mentioned above, as well. If a modular system is preferred over the non-modular variant, this implies the other vessel types will also benefit from this system as a module. Since this system is already defined as an HLP in the KBE model, the system can easily be imported into another
design. The hull form can be easily changed as well since this already is an external Rhino file imported into the Python file. These factors make the framework applicable to a wide variety of different vessel types.

Early-stage design is the most critical phase in a vessel’s development, as this is when many of the major decisions are made and locked in for the remainder of the design process. Most early-stage design frameworks are tailored to conventional vessels, aiming to explore a broad design space—essentially assessing numerous design variations. However, to evaluate such a wide range of design solutions, these frameworks often sacrifice accuracy in their analysis methods to allow for more design evaluations. Consequently, low-fidelity tools are typically used for early-stage design exploration.
For novel vessel designs, low-fidelity analysis methods are insufficient for accurately assessing performance, as they often fail to capture the new and sometimes complex physics involved. While increasing the fidelity of analysis methods leads to more accurate performance assessment, it also raises computational costs, making it impractical to evaluate a large number of design variations. Multi-fidelity models, which combine lower-fidelity methods with a high-fidelity analysis method, offer a promising solution for enabling higher-fidelity assessments earlier in the design process. Thus, this dissertation builds the architecture of a multi-design architectural framework for early-stage design of novel vessels...

Due to recent legislative changes and shifts in global markets, the task of ship design has grown considerably more complex. The integration of groundbreaking technologies, such as remotely controlled or autonomous vessels, poses additional challenges during the concept design phase, primarily due to a lack of familiarity and experience with these technologies. Simultaneously, these advancements make designing a vessel that can consistently meet its objectives throughout its entire life cycle increasingly difficult.

In the early stages of the design process, designers often face the challenge of making critical decisions without fully understanding their potential consequences. This situation is compounded by the increasing costs associated with these decisions and their influence on design freedom. Consequently, the conceptual design stages become especially crucial, as making changes later in the shipbuilding process can result in significant cost escalation for the project.
Considering the various factors impacting the ship design process, there arises a necessity for a novel methodology empowering designers to assess the operational capabilities and performance of conceptual designs during the early stages of ship design.

The presented report introduces the project titled 'Validating Operational Scenarios Through Simulation' and presents findings from a literature review on the utilization of simulation in early-stage design processes.
The introduction chapter begins with an initial description of the problem to be addressed, introduces the involved company, and outlines the motivation behind the project. Following the introduction, the results of the literature review are presented.
The second section aims to answer the first set of research questions by examining the current implementation of simulation software within design processes and presenting available options for software to be utilized in the project. The process of selecting the software is then outlined, along with the conclusions drawn from the research conducted.
Subsequently, the formulated methodology is described, containing all steps necessary to structure the workflow during evaluation. The following chapter details the anticipated method of introducing the formulated method into existing design processes, including the main method of evaluation through simulation and the method of integration, using a case study example.
Finally, the last chapter concludes the report by providing considerations from the entire process and presenting recommendations for potential improvements of the formulated process.

To reduce the environmental impact of the maritime sector, the International Maritime Organization (IMO) has established emission limits and ambitious sustainability targets. While superyachts are currently exempt from many of these regulations, they must align with IMO’s objectives to establish the yachting industry as a responsible sector and adapt to the increasing application of these emission limits. Focusing only on new builds is not sufficient to meet ambitious targets, and sustainable refit of existing yachts is also essential. This applies not only to motor yachts but also to sailing yachts, which face unique challenges due to limited space which further complicates integrating alternative fuels like methanol or hydrogen, given their lower energy density. Despite various studies exploring alternative energy solutions, there remains a research gap in understanding the trade-offs associated with different energy configurations installable in a refit to minimize energy demand and emissions. To address this, an assessment model that evaluate technical feasibility, emissions, docking time, and Total Cost of Ownership (TCO) for different energy configurations is developed. Results from the assessment model, applied to two Royal Huisman sailing yachts of different size across various owner profiles, reveal that integrating alternative energy solutions requires significant reductions in energy demand. Feasible configurations range from using a single fuel HVO configuration for conservative owners to hybrid solutions involving HVO and methanol for more open to changes owners. Ultimately, owners willing to implement various energy reduction methods can achieve several feasible and sustainable configurations.

Technological advancements are increasing system complexities, posing challenges for modern warship design. Early-Stage Ship Design (ESSD) is a vital stage, involving critical decision-making with limited information. The early-stage design of warships entails intricate decision-making considering temporal influences, interdependencies, external factors, trade-offs, high costs, evolving requirements, and other challenges. Developing well-defined system architectures is essential for managing these complexities. Model-Based Systems Engineering (MBSE) is pivotal for overcoming precision issues, inconsistencies, and difficulties in maintaining and reusing information associated with conventional document-centric approaches in systems engineering (SE).
Despite the growing popularity of MBSE, the maritime industry continues to rely on traditional document-centric approaches, lagging behind other sectors in adopting MBSE. These challenges stem from a lack of empirical evidence demonstrating MBSE's full benefits and confusion regarding its implementation practices. Moreover, there is a lack of comparative studies that assess how well MBSE tools are tailored for naval warship design. Thus, this research explores the value of MBSE in the early design stage of naval vessels. Specifically, the research aims to validate and demonstrate MBSE's benefits in developing systems architecture for warships, focusing on operational, functional, logical, and physical perspectives within the context of ESSD. By analyzing industry approaches and utilizing two representative modeling tools, this thesis provides practical insights, clarifies MBSE practices, and promotes its effective implementation in future naval design projects.
A structured research process is formulated to achieve the thesis objective. It begins by defining the mission, capabilities, and requirements. For illustration purposes, a hypothetical Landing Platform Dock vessel mission is chosen, necessitating the creation of fictitious capabilities and requirements. MBSE tools Capella and CDP4-COMET are then selected for this analysis. Next, a metamodel is established for a unified understanding among stakeholders, guiding decision-making throughout the design process. Once the baseline models are constructed, the validation and verification capabilities of the tools are evaluated. The baseline models are modified to simulate the dynamic nature of warship design. Finally, the tools are systematically assessed based on selected key MBSE factors: consistency, traceability, flexibility, and trade-offs.
Transitioning to conclusions, the analysis reveals that both tools effectively validate anticipated benefits. By synthesizing the knowledge gained, it is concluded that MBSE can enhance and accelerate the design process during the early design phase of warships. Capella demonstrates superior performance in the early design stages, whereas CDP4-COMET excels in the latter design stages. This emphasizes the critical role of integrating MBSE tools to enhance design outcomes, leveraging their strengths across diverse phases effectively. Thus, integrating MBSE tools and establishing a unified source of truth is one crucial aspect of advancing MBSE in ship design. Further recommendations are detailed in the thesis.

The maritime industry is progressively transitioning towards sustainable practices, with a significant focus on integrating zero-emission power generation systems. However alternative fuels and technologies implementation on large scale is still pending.
Ships and especially yachts today are designed just for their immediate needs with no future consideration taken into account. This thesis addresses the need for adaptable power room designs in superyachts, facilitating the integration of zero-emission power generation systems as technology evolves. The primary aim is to develop a design method enabling easy retrofitting and future-proofing of yacht power rooms.
The research identifies the current design methods limitation where power rooms are designed for specific scenarios without considering future adaptability. To address this gap, the thesis proposes a three-step design method: layout concepts, design rationale, and a layout evaluation model. This model evaluates power room layouts based on Connection Costs and Retrofit Costs, offering indicators to assess future-proofing capabilities of power rooms arrangements.
A future-proof road-map based on four different scenarios was identified. By applying the design method to these scenarios, various layout concepts were developed, refined based on expert opinions and then evaluated with the model. The results highlight key practices for future-proofing power rooms, such as prioritizing connections between zero emissions power generation systems and auxiliary systems, pre-arranging transport equipment, and designing access openings to facilitate easy retrofitting.
This research underscores the need for a flexible approach to power room design, ensuring superyachts can transition smoothly to zero-emission operations in the coming years.

Offshore wind stands as a crucial contributor to generating clean, renewable energy, but the limited availability of shallow water locations restrains the potential of bottom-fixed wind. To unlock the vast wind energy potential in deeper waters, a substantial reduction in the Levelized cost of energy (LCOE) of floating wind technology is necessary. Tension leg platform (TLP) floating offshore wind turbines (FOWTs) offer significant cost-saving potential, positioning them as a promising solution. However, achieving cost-effective installation of TLP FOWTs poses significant challenges. In the existing literature, this remains relatively undressed with only two studies focusing on this subject, providing partial solutions

The overachieving goal of the thesis is to address this challenge by conducting an in-depth design space exploration (DSE) of an innovative special-purpose installation vessel along with a robust installation method, offering a cost-effective solution. Floating wind represents a yet-to-be-explored market, presenting design challenges associated with managing uncertainties in operational conditions and TLP designs it intends to commission. The research is conducted within the framework of systems engineering.

During the literature phase, a needs analysis is performed to establish design requirements. The installation vessel must be capable of transporting future fully assembled TLP FOWTs. These include 20 MW wind turbines, three-legged TLPs, and an innovative TLP design with one foldable leg for efficient stacking onboard. The DSE model comprises a two-step design approach and a design evaluation based on scenario modeling. The first design step explores radically different designs using an exploration approach integrated with morphological mapping. A trade-off analysis led to the Windchanger concept featuring an installation deck (ID) integrated with the stern design, employing a winch system for FOWT lowering and recovery. In the second design step, this concept is subjected to further exploration through a parametric model, including generating the hull surface for extensive stability calculations. The key factors for scenario modeling comprise the distance to the port, the operational area, and the TLP design. By evaluating the cost-effectiveness and installation duration in each scenario, the goal is to gain insights into the optimal design ranges. This serves as the basis for establishing a design decision framework to manage the considered uncertainties.

The results of this research offer valuable insights into both the technical feasibility and the cost-effectiveness of the Windchanger concept, facilitating optimal design decisions. The model enables evaluation across diverse scenarios to identify the most suitable design within predefined parameters. This is showcased by assessing performance in two operational areas: the North Sea and the U.S. East Coast. The optimal design ranges derived from these analyses can guide further development of the Windchanger Concept, highlighting that a transport capacity of 2 emerges as the most cost-effective option based on the scenarios evaluated.

Introducing a new installation solution necessitates benchmarking against existing methods to ensure cost-effectiveness and feasibility. The results reveal that TLP foundation costs are approximately 40 percent lower than other floating foundations, confirming the anticipated cost-saving potential. Installation costs represent only a fraction, ranging from 0.5% to 1% of foundation costs, emphasizing the importance of robustness and installation time in cost-effectiveness. The model demonstrates that the Windchanger concept outperforms other TLP installation methods, with lower installation costs per FOWT and a significantly higher number of yearly installations. These findings underscore the Windchanger concept's robustness and cost-effectiveness, potentially leading to a substantial reduction in the LCOE of floating wind.

The yachting industry is embracing sustainable practices in response to global environmental concerns, particularly those outlined in the Paris Agreement, which aim to reduce greenhouse gas emissions and limit global temperature increases. Although diesel engines are most commonly used in yachts and are a major contributor to greenhouse gas emissions, efforts are being made to minimise energy consumption through the use of alternative fuels. Auxiliary systems, such as heating, ventilation and air conditioning (HVAC), are also being studied for efficiency improvements. As yachts spend a considerable amount of time at anchor or in port, these systems account for a significant percentage of the total consumption.

This thesis focuses on estimating the energy demand of HVAC systems onboard yachts. In collaboration with De Voogt Naval Architects, part of Feadship, this research uses a grey box model approach, a combination of a white box and a black box, to estimate and evaluate HVAC systems. White box models are based on first principles or physics and are transparent models. This contrasts with black box models, which model a system based solely on observed data, without any prior knowledge of the system. These models are primarily machine learning algorithms such as artificial neural networks. Black box models perform better than white box models within the range of the trained data, but white box models excel at prediction outside this range. The integration of both models can combine the advantages of both into a grey box model.

The white box model described in this report is a type of predictive model that combines theoretical knowledge with empirical data to estimate the heat load for HVAC systems on yachts. The model uses theoretical principles derived from various methods, such as an ISO heat load balance, and incorporates empirical data collected from sensors installed on yachts, including temperature and humidity measurements. This data is used to simulate the performance of the HVAC system under different weather conditions.

The heat load estimation of the white box model is used as input for the greybox model combined with various sensor data. It makes use of a perceptron artificial neural network (ANN), that can learn from the data and adjust its predictions. The hyperparameters of the ANN are chosen and validated using a kfold cross validation. The final calculations are performed with the optimal configuration.

The results of the optimal model are validated against the power consumption recorded in the voyage data. The grey box model achieves a mean absolute percentage error (MAPE) accuracy of 91.3%, which is an improvement compared to the performance of the solo black box. Specifically, the MAPE accuracy of the grey box model is 0.9% higher along with similar improvements in other metrics.

Finally, the study provides an insight on the possible application of the grey box model. The solo white and black box models can also be used apart from the grey box model. A simple extrapolation analysis is conducted to provide insights on the capabilities of the model. With the implementation of these models, Feadship can predict the heat load and energy demand for varying weather conditions and ranges of data.

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.

The development of the global COVID-19 pandemic from 2020 onward has had significant impact on the world and specifically the maritime industry. Striking examples were COVID-19 outbreaks onboard the Diamond Princess cruise vessel and the U.S.S. Theodore Roosevelt aircraft carrier at the start of the pandemic. Contagious disease management onboard large passenger ships remains a complex issue, amplified by the international character of the industry, confined environment and shared facilities. This report therefore presents an investigation into the effect of ship layout design, operational and behavioral measures on COVID-19 airborne infection risk onboard large passenger vessels. The novelty of this research lies with the integrated infection and crowd behavior model used to calculate agent-specific infection risk, incorporating guest and crew circulation through a passenger ship layout.

This thesis presents a data-driven design approach for emission reduction using bunker delivery notes (BDNs) to help support the revised IMO strategy to achieve net-zero greenhouse gas emissions by international shipping close to 2050. This research supports the Horizon Europe’s Digital Twin for Green Shipping (DT4GS) project which focuses on the development of digital twins (DTs). Part of this project involves the development of a DT-supported method for the design and retrofit of ships. DTs are a promising approach for supporting maritime decarbonization efforts due to their simulation and big data handling capability. Despite the abundance of shipping data and growing digitalization, the potential of using ship operational data for decarbonization efforts remains not fully exploited. A data-driven method such as a DT could fill this gap. However, as DTs, by definition, require real-time connection between a physical entity and the digital representation, developing a true DT for new-build alternatively fueled ship designs remains a challenge. This research thus starts by looking into retrofitting using data from existing ships.

A design framework is proposed to construct digital models to support a DT for retrofitting purpose. The proposed framework is tested on a case-study using a 300-meter bulk carrier. Since January 2019, operational ship data is collected through BDNs, a mandatory data collection method for ships of 5000 GT and above, adopted by the IMO. Constructing a DT based on BDNs is considered to be convenient as it provides a solid source of operational data in the future.

First, the available data from the BDNs is preprocessed using an adopted framework based on data science literature. The resulting 5,678 data points are used for the construction of a model representing the bulk carrier and a model representing the green ship technologies part. A fuel consumption model is constructed to represent the bulk carrier. It utilizes a gray-box modeling approach, consisting of a white-box resistance model and a black-box artificial neural network. Both models incorporate environmental-dependent inputs. The investigated green ship technologies for the potential retrofit are represented by various wind-assisted ship propulsion (WASP) systems, namely a towing kite, a DynaRig sail, and a Flettner rotor. These systems are modeled using a white-box modeling approach, together with available wind data. Using an adopted integration framework, based on the propeller-engine matching procedure, both representations are combined into one green ship digital model.

An environmental assessment is performed using the IMO's EEXI and CII assessment tools, respectively evaluating the design and operational aspects of the potential retrofit. Additionally, a financial assessment is conducted using the payback period. Results showed the design implications and emissions reduction potential of implementing such systems which will guide the retrofit decision by the ship's owner.

In 2018, greenhouse gas (GHG) emissions from shipping were estimated to account for 2.9% of global emissions, with projections indicating an increase of up to 44% by 2050 under various long-term energy and economic scenarios. In response, the International Maritime Organization (IMO) has set ambitious targets to reduce carbon intensity by at least 40% by 2030 and achieve net-zero GHG emissions around 2050. This research explores the potential and implications of integrating life cycle environmental performance evaluations into early-stage ship design, moving beyond the traditional “tank-to-wake” focus to encompass the entire life cycle of a vessel. Incorporating Life Cycle Assessments (LCA) into the design stage promises to optimize vessel design by addressing environmental and economic impacts across its full lifecycle, from construction to decommissioning. The primary objective of this report is to investigate the extent to which life cycle assessment optimization, based on cost and environmental impact, can be performed and implemented in the conceptual ship design of complex vessels, and to assess how it can support the development of new designs. This study presents an analysis of the lifecycle stages of ships and introduces Ulstein Design & Solutions B.V.’s innovative design tool, Blended. Through an extensive review of life cycle thinking methods, material and energy flow analyses, industrial ecology practices, and socio-economic impact assessments, the research establishes criteria for evaluating the applicability of these methodologies. A trade-off analysis guides the selection of an appropriate approach, leading to the development of a novel method to integrate life cycle assessments into the Blended Design tool. Key outcomes of the research include the identification of relevant life cycle assessment methodologies and their applicability to early-stage ship design. Additionally, an approach has been developed to integrate both cost- and GHG-emissions-based life cycle assessments into Blended, focusing on the shipbuilding and decommissioning phases. Furthermore, the study demonstrates how life cycle assessment integration can influence early design decisions, particularly by addressing the environmental and economic trade-offs that arise during construction and maintenance. The study emphasizes the importance of addressing lifecycle impacts in early-stage ship design to prevent burden shifting between lifecycle phases. It also highlights the need for robust data collection and the development of performance indicators tailored to specific ship designs to enable reliable assessments, despite the limited information available at the early stages of design. In conclusion, this research advances the understanding of how LCA can be applied in conceptual ship design to meet sustainability objectives. By enabling full lifecycle optimization within the Blended Design tool, it offers a pathway to creating vessel designs that balance environmental responsibility with economic viability, contributing to the maritime industry’s efforts to meet international decarbonization targets.

Due to the IMO regulations on emissions, Wind Assisted Propulsion Systems have become more and more interesting for shipowners. One of those Wind Assisted Propulsion Systems is the VentoFoil from Econowind. However, to enable the decision of the shipowner on whether and where to place VentoFoils on board, this research aimed to construct a VentoFoil Adoption model, assessing the environmental and financial consequences of specific VentoFoil placement options. With this, the main research question is: ‘What is the impact of VentoFoil placement on ships from a ship owner’s perspective?’ The VentoFoil Adoption Model for Econowind required a Technology Adoption Decision-support model that could operate within a short computational time while incorporating an adaptable weather matrix. During the literature study on the existing models regarding WASP models, a research gap was identified. The gap primarily lies in integrating low-fidelity force modelling with financial decision support.

The VentoFoil Adoption model was constructed with a baseline calculation in which no VentoFoils were placed onboard. This baseline included the hull resistance and the wind forces on the deckhouse for all possible wind directions and speeds. After that, the VentoFoils were placed on deck, for which the VentoFoil forces were added with respect to the baseline calculations. The VentoFoil forces were calculated including the interaction between the deck and the VentoFoils, using a turbulent separation layer. The interaction between the deckhouse and the VentoFoils was simulated using a triangle shape in which the wake is turbulent. Lastly, the interaction between the VentoFoils was included using a parametrized wakefield in which the apparent wind angle changed based on the distance between the VentoFoils. From the resulting polar plots, the financial and environmental benefits of VentoFoils are illustrated. Fuel savings are achieved when sailing at reference speed and lower power, and increased cargo yield is realized at higher speeds with reference power. This is dependent on the weather probability matrix.

To demonstrate the practical application and effectiveness of the model, a case study was performed using the VentoFoil Adoption Model on the Magritte, a bulk carrier currently sailing with two 16-meter VentoFoils. From a shipowner’s perspective, the conclusion was made that two 30-meter VentoFoils would in the long term be more cost-effective. For most combinations of fuel price and cargo yield, the payback time of the case at reference power and thus higher sailing speed was lower, making it the favourable operational decision.

A validation using the ‘validation square method’ was performed on the method used within the VentoFoil Adoption Model. The empirical performance validity was investigated by comparing the results from the sea trial data of the MV Sunnanvik and the results from the model. The results are within a reasonable range.

The answer to the main research question can be found with the model. Multiple placement options can be inserted, giving the benefits and costs for well-considered decision-making of the ship owner on whether and where to place VentoFoils on board.

The transition to methanol as a promising alternative fuel for maritime applications, presents unique design and material challenges, particularly in retrofitting existing integrated aluminum tanks for methanol storage. Methanol’s toxicity, flammability, and corrosive nature, particularly with respect to aluminum alloys, complicate this process. This research adopts a multi-disciplinary approach, integrating ship design and material science to address these challenges. A complete analysis of regulatory frameworks and material compatibility was conducted to explore viable solutions for converting integrated aluminum tanks, with a focus on incorporating an inner barrier that ensures both compliance with classification societies and the optimization of net volume.

Key methods used in this research include Multi-Criteria Decision-Making (MCDM) analysis and static immersion followed by tensile tests experiments. The MCDM was conducted to ascertain the most viable inner barrier solution for retrofitting integra.