Dredging projects are capital-intensive, complex, and exposed to high uncertainty from weather, soil conditions, technical reliability, and logistics. During early tender bidding, contractors must estimate project duration, costs, and emissions with limited time, data, and engineering capacity. Detailed studies are rarely feasible, yet bidders must anticipate which uncertainties drive outcomes. Existing methods provide detailed analyses of individual aspects but require resources unavailable at this stage. What is missing is a structured, rapid way to identify and prioritize the most critical risks.

This thesis develops a rapid risk-assessment methodology that combines expert judgment with Discrete Event Simulation (DES). The approach enables contractors to focus scarce resources on uncertainties that matter most for project success. The open-source platform OpenCLSim was chosen for its layered structure (activity, sequence, asset, project), flexibility, and suitability for dredging logistics.

Inputs are expert estimates of risk likelihood and impact, grouped into four categories: workability, technical, logistical, and environmental/social. These are mapped to the correct project layer and encoded through a custom Risk & Uncertainty extension using occurrence models and impact distributions. Risks are thus represented at appropriate levels—activity variability, sequence delays, or project-wide interruptions.

Outputs are probabilistic KPIs for project duration, costs, and emissions, obtained via Monte Carlo simulation and reported at the industry-accepted P80 level. This provides risk-aware estimates under uncertainty. The method also includes mitigation evaluation, where updated risk parameters are simulated with countermeasures. Comparing mitigation costs with reductions in time, cost, and emissions highlights which measures are financially viable and where engineering capacity should be allocated.

The method shows how risks at different layers interact: delays off the critical path may be absorbed in project duration, but still cause idle costs and emissions. Thus, time buffering and cascading impacts diverge, clarifying risk importance for different KPIs.

Applied to the Malmporten case, expert elicitation identified three risks: mooring-time uncertainty, a sequence-level backhoe breakdown, and project-wide turbidity exceedance. Simulations revealed that the backhoe breakdown had the greatest impact by delaying dependent assets; turbidity exceedance mainly raised costs and emissions; mooring-time uncertainty had modest operational effects. Mitigation analysis showed sequence-critical risks offered the highest leverage: on-site spare parts sharply reduced repair durations and had the best benefit–cost ratio, while silt screens and experienced captains offered smaller, complementary benefits.

Conclusion: The methodology provides a structured, time-efficient decision-support tool for early tendering. By combining expert judgment with DES, it delivers probabilistic insights into which risks matter most and which countermeasures are justified. Though demonstrated in one case, the method can be generalized to other dredging project types and extended with advanced failure models, calibrated inputs, and broader KPI frameworks. It equips contractors to make more reliable, risk-informed decisions under the constraints of early tendering.

Sea locks are a barrier between sea water and fresher inland water, allowing for control of inland water levels. They help maintain navigability for vessels, ensuring the connection of hinterland ports to the global shipping network. At the same time, they ensure the continued availability of drinking water, fresh water for agriculture and industry, and contribute to ecological stability by regulating water quality. However, the locking operations needed for vessel passings lead to salt intrusion and thus a reduction in the water quality of the inland waters. With climate change, longer periods of drought and an increase in sea water levels are expected, which increases the salt intrusion. And the growth of the global vessel industry means larger locks are needed to ensure navigability of the increasing vessel sizes, which increases the salt intrusion even more. We observe that measures taken by governments to reduce salt intrusion around locks require insight into both shipping impacts and salt exchange effects. Currently there seem no methods available to quantify how operational measures to reduce salt intrusion around locks impact both the shipping performance and salt levels behind the lock. This thesis investigates how we can overcome this gap in literature.

A first step is to identify how vessels pass shipping locks. We identify the important events that make up the entire lock passage procedure of a ship. Specifically we distinguish: approach, doors open, sailing in, doors closing, levelling, doors opening, sailing out and doors closing again. Next, we identify how the hydrodynamic processes that occur during the locking process influence salt intrusion. The most impactful hydrodynamic processes that occur are taking place between doors opening and closing, and during levelling.

Next we investigate what models are available to simulate both the shipping events and the salt exchange events. While there are several modelling concepts out there, we conclude that for the challenge at hand it is most suitable to use the mesoscopic agent-based traffic simulation model OpenTNSim to simulate vessel passages through locks. We couple this with the semi-empirical salt exchange model called the Zeesluisformulering. The main reason to choose this combination is that a discrete event agent based nautical traffic model captures exactly those events that drive the salt exchange estimates of the Zeesluisformulering. By combining both methods we get a new method that allows us to quantify how salt intrusion mitigation measures affect shipping performance and salt levels intrusion through the lock.

To determine how well the proposed combination of models works in practice we apply it to a real world case. For this thesis we select as our case location the Sea Lock IJmuiden, which at this point is the largest sea lock in the world. The lock complex in IJmuiden is suitable as a case, in February and March of 2023 salt intrusion measurements have been taken by Deltares and Rijkswaterstaat. During this period we also know what ships passed the locks, based on records taken by maritime students of the Amsterdam University of Applied Sciences. Based on these data sources we can test if the combination of models is capable of reproducing the observed behaviour...

In recent years, costs in the offshore wind energy sector have risen significantly. Rising interest rates, shortage of skilled labour and a supply chain which is under pressure due to the ever increasing size of offshore wind turbines all cause costs to increase. At the same time, the pressure to realise sustainable energy continues to grow. The installation phase is one of the most expensive and resource-intensive parts of offshore wind projects. Reducing the installation duration could aid in significantly reducing the installation costs, and make offshore wind farms more economically feasible.

The Slipjoint is a novel connection method developed by Delft Offshore Turbine (DOT), that aims to reduce offshore installation time, and therefore installation cost, by removing the need for bolting or grouting connections between wind turbine parts. When coupled with a complete pre-assembly strategy, it enables installation of offshore wind turbines with a single lift.

This paper presents a Discrete-Event Simulation (DES) model that compares traditional and Slipjoint-based wind turbine installation methods in terms of time, cost, and weather sensitivity. The model gives insight into how weather, vessel characteristics, and campaign timing influence installation performance of both the standard and Slipjoint-based installation methods. A multi-year simulation is run over a range of weather datasets, to give insight into installation performance as a function of start date. The multi-year model is applied to two case studies: the Ecowende wind farm in the North Sea, and the Star of the South wind farm off the coast of mainland Australia, near Tasmania. The standard installation method is compared to the Slipjoint method. The Slipjoint method is run with two values for the capacity to investigate the impact of the capacity on performance. Results show that the Slipjoint can reduce installation duration by 30 to 60\%. Increased vessel dayrate and mobilisation costs, caused by the need for Heavy-Lift Vessels for the Slipjoint method, partially offset the economic gain from the reduction in installation time. Still, a cost reduction of 0 to 30\% can be achieved, depending on the vessel capacities which can be achieved. Furthermore, the Slipjoint methods are shown to have a higher weather workability, meaning they are less affected by bad weather conditions than the standard installation method. This enables them to have a wider envelope in which the installation campaigns can start. These results show the potential of the Slipjoint to change the way offshore wind farms are installed, in order to make offshore wind energy more economically feasible.

Sand utilization has increased over the past decades and is getting a scarce resource globally. In Singapore, no sand is available for construction purposes or land reclamation projects. The increasing scarceness of ''suitable'' sandy building materials around the world forces the dredging industry to consider the usage of alternative ''complex'' materials for land reclamation purposes. However, working with these kinds of ''complex'' materials introduces operational and technical challenges on the estimation of project duration and costs, due to their low permeability, high compressibility and complex consolidation behaviour of this slurry material.

The main involved departments on land reclamation projects are the production department and the geotechnical department. The production department is responsible for ''Production Estimation'' and estimates the rate of which soil can be produced by transporting it from the dredging area to the reclamation area, considering specific equipment choices and costs. The geotechnical department is responsible for ''Reclamation Engineering'' and handles the engineering of the soil brought in by production to be formed into a soil which is eventually usable for the client.

Two reclamation projects of the past; the ''Scandinavia'' and ''Black Sea'' project have proven that Production Estimation and Reclamation Engineering are closely connected when working with ''complex'' material. While working with ''suitable'' sandy materials primarily focuses on minimizing project costs through optimizing Production Estimation, the effects of Reclamation Engineering optimizations increases significantly when dealing with ''complex'' materials. This is due to their long duration of consolidation and the potentially high costs of soil improvements required before the asset can be delivered to the client.
In this context, optimizing Production Estimation by dredging at low initial density comes at the expense of Reclamation Engineering as low initial density often results in longer and more costly consolidation, and vice versa. Therefore, it can be concluded that a trade-off exists in optimizing for Production Estimation and Reclamation Engineering in minimizing project costs.

It becomes evident from the literature review that no specific research is dedicated to investigating the effect of the trade-off between optimizing Production Estimation or Reclamation Engineering in minimizing project costs. Therefore, the main research objective of this thesis is to answer the question:

''How can project costs be minimized by explicitly balancing the trade-off between optimizing for Production Estimation and Reclamation Engineering?''

This thesis provides a new framework for evaluating the effects of the trade-off between Production Estimation and Reclamation Engineering optimizations on total project costs, in order to answer the main research question. This framework couples production estimation models to geotechnical estimation models by OpenCLSim and a large-strain consolidation model. This integral approach enables the simulation of the continuous reclamation construction process, including filling, self-weight consolidation and long-term consolidation under the effect of ground improvement methods. The proposed framework is subjected to a case-study to asses how optimizations on Production Estimation and Production Engineering affect consolidation behaviour and project costs. In this analysis optimizations are implemented by varying initial density coming with hydraulic and mechanical dredging work methods. This thesis evaluates these optimizations in three stages; single production cycle, production - self-weight consolidation analysis, and a full scale case study including long-term consolidation under the effect of ground improvement methods. The full-scale case study is evaluated using a hydraulic work method of 1100 kg/m3 and a mechanical work method of 1300 kg/m3. The production and reclamation models are calibrated by the material characteristics from the case-study, whereas the large-strain consolidation method is calibrated and validated by physical samples from the project site.

Results from the full scale case-study show that utilizing a mechanical method at 1300 kg/m3 (aimed at optimizing Reclamation Engineering) results in a 1,86 more expensive project than using a hydraulic method at 1100 kg/m3 (aimed for optimizing Production Estimation). Almost no differences occur between Reclamation Engineering costs for the two dredging work methods as the case-study material quickly consolidates and converges to a similar compaction profile within a similar time-frame. Consequently, the potential advantage of achieving a higher initial density using the mechanical method is diminished by its lower production rates and high costs. By converging to a similar compaction state within the same duration creates no significant differences between the ground improvement methods needed to force the profile to comply to design requirements. This will lead to almost no differences in costs for Reclamation Engineering. As a result, only optimizations in Production Estimation can lead to minimization of the project costs for the considered case-study material.

Nevertheless, it can be concluded that it is possible to get insights on how to minimize project costs based on the trade-off between Production Estimation and Reclamation Engineering when using a framework which couples their interactions through self-weight (large-strain) consolidation and OpenCLSim. The existence of the trade-off and its magnitude on minimizing project costs depends on the soil type used in the project. ''Complex'' materials that tend towards relatively ''well-consolidating'' seem to reduce the magnitude of the trade-off, while it is believed that more ''poor-consolidating'' materials enhance the magnitude of the trade-off. Therefore, the predictability of the trade-off between Production Estimation and Reclamation Engineering optimizations is closely related to the understanding of production effects (varying initial density and varying duration between layer stacking) on the consolidation behaviour of the slurry material.

The proposed framework in this thesis is believed to be a first step in estimating project costs and duration based on a physics-based approach, compared to the current ''empirical estimations'' that are used to represent physical processes such as large-strain consolidation. The proposed framework could lead to a more integrated understanding between Production Estimation and Production Engineering when using ''complex'' material and more insights on how optimizations between the two departments can minimize project costs.

In the coming decades, the shipping sector is facing various challenges, requiring adaptations for achieving sustainable shipping, against climate change consequences, for facilitating alternative activities at sea, and for transitioning towards more autonomous shipping. Several incidents related to these challenges force us to take a good look at how the system can keep performing its function conditional to these changes. Scientific studies hereby regard the collective of (interacting) shipping activities as a system. Outcomes of data analyses and models are intended to support decision makers in designing effective improvement measures. However, the usefulness of the outcomes to the decision makers can be better, amongst others due to poor communication between science and decision makers, due to analysis objectives not being achieved, and due to unrealistic data requirements.

At the foundation of the analysis is often a disciplinary approach, or \textit{way of thinking}, which determines which solution space is considered, and which input sources are accepted. Looking from multiple \emph{perspectives} can broaden this, and thereby improve the formulation of analysis objectives and the identification of relevant input data. Besides determining which perspectives are relevant for a specific problem, the remaining challenge is related to how these alternative perspectives can be merged into an integrated whole. The aim of this thesis is to design a framework for an early integration of multiple perspectives in the analysis of shipping systems to improve their usefulness in the decision-making process. The first ambition for the framework is to provide a formulation of analysis objectives and data requirements in view of multiple perspectives, and the second ambition is to develop a data-structure concept to merge the perspectives.

For the first ambition, a literature study into systems with similar characteristics as a shipping system revealed that the analyses of these systems are mostly performed from one or several of the perspectives regarding its objectives, that we refer to as: (1) \textbf{scales}, addressing the ``where'' and ``when'' of system performance, uncovering spatial patterns and temporal variations, (2) \textbf{conditions}, considering the connection between system performance and its underlying physical processes and environment, (3) \textbf{behaviour}, considering the influence of individual or collective behaviour on the system performance and (4) \textbf{dependencies}, identifying causal relationships and sensitivities within the system. For each of the distinguished perspectives, based on the data sources and analysis types of the relevant studies, specifications could be formulated about the highest detail level on one hand, and the information required to aggregate to higher levels, up to the system level, on the other.

The second ambition, regarding a concept for merging these multi-perspective requirements, was obtained by introducing a new data structure referred to as an \emph{event table}. In this data structure, inspired by the existing concepts of moving features and event logs, each row represents a distinct event, and each column indicates a characteristic of the event. A single event is defined by the highest-detail-level specifications for each perspective. Besides some columns that form the unique event definition, the \emph{attributes} provide additional information about each event. Filtering and aggregation operations on the event table allow zooming in and zooming out, offering flexibility to investigate global patterns in detail, or to assess the impact of detail level processes, thereby fulfilling the second ambition for the framework.

The framework outlines the relationship between the availability of input materials and the ambition of the analysis goals. Hence, developments in the field of data science, analysis techniques, and computational facilities increase the scope, detail level, and modeling complexity captured in the analysis goals. By parallelising and scaling-up computations, the scope and detail level of analyses can be increased. By joining multiple spatially and temporally varying data sources, environmental influences can be determined. By applying dimension-reduction and outlier detection techniques, many characteristics of vessel behaviour can be assessed to determine anomalous behaviour. By labelling known behaviour, cause and effect can be coupled to improve the predictive capabilities. Applying these developments to the monitoring activities regarding nautical safety demonstrated how these developments can extend the ambition level of the analysis.

The framework was applied to two shipping-related cases. The first case considered nautical safety risks at the North Sea imposed by the potential event that vessels get adrift while being surrounded by offshore infrastructure, like wind parks. Based on the formulated multi-perspective objectives, the event table was constructed, whereby each event was defined by combination of a vessel of particular type and size (indicated by a category), to be present at a particular location at sea (indicated by a cell, part of a grid), under particular environmental conditions (a combination of wind direction, wind speed, wave height-period combination, wave direction, and current profile). For each event, the probability of occurrence could be determined, and conditional to this, using a drift path prediction tool, the probability that the vessel would drift into a wind park after $n$ hours in case of technical problems. Filtering and aggregation operations on the table revealed how a single analysis can support location specific design of barriers between wind parks and shipping lanes, as well as evaluation of strategies for emergency response vessels.

The second case considered shipping emissions on Dutch inland waterways. Based on the framework, analysis objectives were formulated for three perspectives; scales, conditions and behaviour. This resulted in an event table whereby each event corresponded with a single vessel, sailing a single waterway section on the Dutch fairway network. For each event, based on the sailed trajectory, the vessel properties, and the environmental characteristics, the energy use as well as the associated emissions could be estimated. The entire collection of events in the table represented all vessels travelling on the Dutch inland waterway network over the course of four months. Filtering and aggregation operations on the table revealed how emissions are impacted by river currents, and that a large share of the emissions is caused by waiting, idling, and manoeuvring vessels.

Both cases demonstrated how application of the framework can lead to an improved understanding of how the shipping system performs and responds to varying conditions and external changes. More importantly, they showed that the event table concept was capable of supporting formulation of promising improvement measures. This offers policy makers better support when making decisions. Owing to the versatility of the event-table concept, it is possible to anticipate on unseen or unforeseen perspectives in the future.

This dissertation is triggered by the prevalent observation of conflicting stakeholder interests in highly urbanised deltas. These are coastal areas containing estuaries - i.e., water bodies where river water meets and mixes with seawater - which can form open or closed systems, and which can be natural or (highly) modified (e.g., trained, dredged or closed-off channels and canals). In these deltas, many stakeholders, including local communities, agriculture, shipping, and ecology, rely on estuarine services such as water safety, freshwater availability, deep and calm waters, and natural dynamics. Due to climate change and socioeconomic developments, many of these estuaries have become increasingly pressured, meaning that during extreme conditions, such as droughts, the variety of stakeholder interests can no longer be simultaneously satisfied. Consequently, system modifications to improve one stakeholder's interest may come at the expense of other stakeholders' interests, requiring complex trade-off decisions.

Here, waterborne transport is a key player. To facilitate the movement of goods and people, water transport entrepreneurs employ ever-larger vessels that call at ports ever more frequently. To accommodate this trend, waterways have been deepened and new lock complexes have been constructed. While such system modifications have brought beneficial effects to regional and (inter)national economies, they have also exacerbated saltwater intrusion, which negatively impacts freshwater availability during droughts. A framework to quantify a fair trade-off between the interests of waterborne transport and other estuarine user functions is currently absent. Instead, policy and decision-makers rely on qualitative analyses based on oversimplified models, hindering rational policy and decision-making. This problem particularly holds for the impact of physical system changes on waterborne transport performance, which are often not quantified.

Consequently, interventions aimed at improving waterborne transport often neglect the potential negative impacts on other stakeholders, leading to suboptimal and non-integrated solutions that may be ineffective in the long run.

The objective of this dissertation is, therefore, to assemble a methodological framework that can rationally quantify the trade-offs between impacted stakeholder interests for interventions in systems where waterborne transport plays a significant role. To achieve this, a two-step approach is followed. First, a method is developed to quantify the impact of system modifications in estuaries on waterborne transport performance. Second, this quantification method is included in a framework that can evaluate multi-stakeholder interests for an intervention in the estuary. This framework results in a trade-off curve between the impacts on the stakeholders' key performance indicators.

As a result of the first step, this dissertation found that vessel waiting times are the key performance indicator for quantifying the impact of system modifications on water transport. These waiting times are primarily caused by the cascading effects of downtime and congestion, which are currently not quantified by any existing method. To include these effects, this dissertation identified the open-source simulation library OpenTNSim to be the most suitable for further development. Additional modules were developed and added to this library to resolve the aforementioned `cascading effects of downtime and congestion' for both open and closed estuarine systems. The proposed quantification method was validated by its implementation as a nautical traffic model in a real-world case study of seagoing vessels calling at a liquid bulk terminal in the Port of Rotterdam. In this case, the nautical traffic model was considered valid when a sufficient part of observed waiting times could be reproduced and explained. One year of AIS data was analysed to obtain a representative fleet in the model with realistic origins, destinations, speeds, turning times, and laytimes at the terminal and anchorage areas. In addition, geospatial data and one year of hydrodynamic data were used to derive model input. Together with the actual maintained bed levels, port layouts, and tidal accessibility policies, the model resolves tidal downtime and infrastructure congestion. Analysis of the model results reveals that the nautical traffic model was able to unravel 73.4\% of the observed non-excessive vessel waiting times. Moreover, the unresolved excessive waiting times are believed to be caused by other processes that are not related to the system's state. Hence, the implemented method is considered valid to quantify waterborne transport performance as a function of the physical system.

In the second step, the now-validated quantification method for waterborne transport performance was included in a developed framework to evaluate trade-offs between the stakeholders' interests. The framework entails a train of models that link state indicators of the physical system to performance metrics for stakeholder interests. The model results are used to quantify the trade-off between port performance and freshwater availability as a function of bed-level variations in the open system of the Nieuwe Waterweg (NWW) in the Rhine-Meuse Delta. The resulting impact curves are insightful; they reveal how waterborne transport performance and freshwater availability compete as the bed level of the NWW changes. Freshwater availability improves when the bed level is raised, albeit at the expense of water transport performance, while water transport performance improves when the NWW bed level is lowered, albeit at the expense of freshwater availability elsewhere in the estuary. By adding valuation functions to each of the performance curves, stakeholders can express how important they find certain levels of performance loss. Ultimately, the framework leads to an optimal depth, although this decision remains a political process.

In conclusion, this dissertation enables a more rational trade-off between stakeholder interests in estuaries where water transport plays an important role. The underlying agent-based nautical traffic modelling method, implemented in the OpenTNSim library, and trade-off framework can be further expanded and applied. For this, further validation of the modules is recommended, particularly for closed systems, as they were only validated for open estuaries, with a specific focus on tidal windows and salt intrusion effects. Furthermore, to extend the applicability of the proposed quantification method for water transport performance, this dissertation recommends considering the incorporation of additional physical factors that affect downtime and additional sources that contribute to congestion. This may require the incorporation of additional datasets and the involvement of additional computing power. Moreover, to extend the applicability of the trade-off framework, it is advised to incorporate additional stakeholder interests and to involve stakeholders in constructing realistic valuation functions. With these additions, the proposed approach becomes more widely applicable, opening the door to its application to other estuaries around the world.

The Dutch system of waterways, of which the River Waal is the largest, allows for transport of cargo via inland navigation. Inland navigation as a transport mode contributes to the Dutch GDP and is indispensable for the Dutch strategic position in international world trade. Because inland navigation is river-based, it is dependent on natural conditions. Recent periods of drought, such as in 2018, have led to major financial impacts in the Netherlands and Germany. Due to climate change, periods of drought are expected to be more frequent, longer and more extreme in the future. Given the importance of inland navigation, measures are sought after to counteract these effects of climate change. Canalization of the River Waal is a last resort infrastructural measure to gain control over water levels on the river. To date, it is unclear whether climate change will eventually make it necessary to canalize the river for the benefit of inland navigation. In addition, it is unknown on the basis of what considerations such a decision should be made. This research attempts to answer these questions.

To investigate the necessity of canalization due to climate change, first the impact of climate change on inland shipping is determined on three different levels. First the hydrological development including occurrence of (low) discharges and corresponding water depths. Second the impact on individual vessel's loaded draught and loading rate, based on least available water depths on the River Waal in climate scenarios. Third the corridor cargo transport capacity, based on the occurrence of (low) discharges and the cargo transport performance of inland shipping in the past 10 years during similar discharge events. The development of these elements are the considerations in the debate on necessity of canalization of the River Waal from a shipping perspective. Whether these developments support the necessity of canalization is studied by means of limits which, if exceeded, may argue canalization. For the river's navigation function, requirements on navigability were identified based on prevailing international waterway management regulations (CCNR and TEN-T) as well as on previous Dutch canalization projects on the River Meuse and Lower-Rhine. The limits are projected on the analysed future development of the River Waal under climate change, to identify if and when they are met.

The hydrological development of the River Waal is assessed based on future discharge projections at Lobith under climate change. A range in scenario's is described, with a low emission and wet climate scenario 'Ln' on one side and a high emission and dry scenario 'Hd' on the other. In an Ln scenario, the future occurrence of days with low discharges (<1800 m3/s) on average per year is similar to that of the reference scenario (past 30 years, 1990 - 2020). In contrast, an Hd scenario shows a steady increase in the days of low discharges until 2100 after which the trend stabilizes. Extreme low discharges <600 m3/s appear. Furthermore, the lowest annual discharge (generally speaking during summer) lowers to 1000 m3/s by 2150, which is 750 m3/s lower than in the reference scenario.

At Rhine Kilometer 885 near Nijmegen the lowest water depths occur. In an Ln scenario the number of days with low water depth (<2.8 meter) is similar to the reference scenario with 40 days, independent of time. In the Hd scenario the number of days with low water depth increases where <2.8 meter occurs up to 3x more as in the reference scenario and outliers of <1.6 meters appear, up to 10 days. The long term average lowest discharge during the year drops from 3.5 meters in the reference scenario to 3 meters in 2050 and <2.5 meters after 2100.

The analysis of discharges and water depths is used to describe the development of the transport function of the River Waal. The location with the lowest water depth on a route of a vessel determines the loading rate. The combination of loading rate and active fleet determines the total amount of cargo carried on a corridor. In an Ln scenario, there is little deviation from the reference scenario, but nonetheless, a large vessel 135x17.4 meter CEMT Class VI+ has a restricted loading rate for 7 months per year with a minimum of 50% of the maximum vessel loading capacity. In an Hd scenario the loading rate of vessels decreases and the period lasts longer. For a most common vessel 110x11.4 meter CEMT Class Va, an annual average minimum is observed of 60% in 2050 to 40% in 2150. The duration of restricted loading doubles and the steepest decline is observed between 2050 and 2100.

Based on historical performance (2010-2020) of inland navigation, linked to the occurrence of discharges, a first-order indication of the development of transport performance over the River Waal corridor under climate change is made. No absolute numbers can be determined on this basis, but a sense of trends can be obtained.

Assuming no changes in the current fleet, the annual total weight that can be transported will decrease regardless of the climate scenario. The severity does depend on the climate scenario. Zooming in on cargo type does show a varying picture, where for dry bulk cargo there is an annual decrease of -3.0% cargo transport capacity in the most severe 2150 Hd scenario, while for liquid bulk cargo there is a steady decrease to -12.0% cargo transport capacity in 2150. This difference is explained by the number of trips made, where for dry cargo this theoretically rises to +25% in 2150 Hd, while for liquid cargo it can only increase +3%. Redundancy in the fleet can thus partially counteract the effects of climate change.

To reason the necessity of canalization, limits on navigability are identified, based on current navigational requirements and previous canalization practice. For the river's transport function, no clear limits where found, as a result of which no development could be identified that necessitates canalization. There are two regulations that apply to the navigability of the River Waal. TEN-T is a transport policy of the European Union and sets requirements for the quality of its network. On the River Waal, a guaranteed draught of 2.5 meters is required year-round. This is not met in the present (20 days undershoot in an average year) and will not improve in any climate scenario (up to 80 days in 2150 Hd). The CCNR is an association of five countries that is committed to the safety and interests of inland navigation on the Rhine. CCNR guidelines are leading for river management in the Netherlands. On the River Waal, 'OLR' (Agreed Low River Level) conditions require a water depth of 2.8 meters in the fairway, per definition a water depth that is undershot on average 20 days a year. This is not met in the present (40 days undershoot in an average year) and will not improve in any scenario in the future (>100 days in 2150 Hd).

Conditions on the River Meuse (1920) and Lower-Rhine (1960) before canalization were projected onto the present River Waal. If, as on the River Meuse, one want to accommodate a normative vessel CEMT VIc 6-barge push barge, there is at least 180 days of loading rate restrictions, now and in the future under all considered climate scenarios. The Lower-Rhine is canalized for the purpose of navigability of Lower-Rhine and River IJssel and to control freshwater distribution. Both Lower-Rhine and River IJssel did not meet the navigability requirements set at the time. The River Waal also does not meet its current stated navigability requirements (CCNR 2.8m: 40 days), but even in the extreme 2150 Hd scenario this is roughly only half (100) of the days as on the River IJssel and Lower-Rhine (2.7m: 190 and 225). The navigability requirements of that time did fit better with the draught of a most common vessel. The current most common vessel 110x11.4 meter CEMT Va experiences as many days (160) of insufficient water depth as on the River IJssel in all dry climate scenarios between 2033 and 2050. Compared to the Lower-Rhine, this is the case in an Hd scenario between 2050 and 2100 (180 days).

This research concludes is that from the inland shipping perspective there are two overarching considerations in the decision on canalization of the River Waal, the perspective of the navigability of the river and the perspective of its capacity to allow cargo transport. The navigability, described in (low) discharges and water depth, deteriorates due to climate change. Clear thresholds as TEN-T and CCNR requirements are not met and there is not sufficient water depth to accommodate the normative vessel CEMT VI+ year round. Taking action in the form of canalization would guarantee these requirements to be met now and in the future. Uncertainty in climate conditions causes that no clear predictions can be given on how severe the impact on the transport function is. Furthermore the transport function is more complex, since it describes a spread of individual vessels, different cargo types and a corridor. It is not inconceivable that adjustments within the 'transport function', like alterations in the logistical chain or improvement of the fleet, could (partially) counteract the negative impacts of climate change, which subvert the necessity of canalization. Apart from that, this research concluded that for the transport function there are no uniform quantified goals. Goals mentioned are the added value to Dutch GDP, the role in other sectors, the model shift and (military) strategic. Since these goals are broadly formulated, but not well quantified, it is difficult to identify limits in the performance of the system under climate change which could argue the necessity of canalization. To make a deliberate decision on canalization based on its capacity to allow cargo transport, it should first be defined and quantified what achievements should be made with the River Waal.

To stay on track for the 1.5°C pathway of the Paris Agreement, an accelerated energy transition is essential. Efficient offshore energy infrastructure planning, incorporating novel methods, is crucial and requires transparent, industry-wide discussion. However, two main challenges emerge: (i) the often-overlooked integration of energy islands in literature and (ii) the lack of a standardized techno-economic comparison method. A comprehensive review of offshore wind supply chain feasibility studies highlighted the need for explicit implementation of standardization, syntax and semantics in model development. Detailed assessment of international and industry standards revealed that no single standard fully covers the study's scope. Nevertheless, one ISO standard showed significant similarities in component definitions, with which this study's component definition is maximally aligned. The developed open-source model enables automated supply chain configuration generation, eventually calculating economic metrics such as the Levelized Cost of Hydrogen (LCOH). Applying the developed techno-economic model to the 19.5GW case study hub North in the North Sea Energy programme demonstrated its applicability and the techno-economic advantages of integrating an offshore energy island. The key finding is that island-based configurations are economically more efficient for hydrogen production compared to platform or onshore setups. Comparison with other studies on hydrogen import indicates that the calculated LCOH range of 8.54 - 10.40 €/kg has the potential to compete with hydrogen imports, which often have overly optimistic estimates ranging from 4 to 9 €/kg. Ultimately, in this way, a standardized, transparent method for industry-wide collaboration is presented.

On Saba, an island located in the Caribbean, a new harbour will be constructed. To protect coral reefs in the vicinity from light attenuation and sedimentation, it is important to monitor and predict the turbidity stresses caused by the dredging operation. In the early stages of such projects involving dredging operations, a common approach is to estimate the turbidity stresses in a simplified way using stationary source terms and the exclusion of important physical processes as tidal and wind-forcing. This research focused on the development of a representative approach to simulate the turbidity effects from dredging activities by backhoe dredgers in the vicinity of Caribbean islands, by building on existing methods by Becker et al. (2015) and Tuinhof (2014). The Black Rocks harbour project on Saba was used as a case study to test the effectiveness of the new method approach.

First, the local physical processes were identified and their influence on the turbidity stresses and dispersion of the sediment plumes were discussed. Insight in the wave heights and wave period should be obtained to aid in the decision for the dredging equipment to use and their workability. Key processes to include for a representative simulation for the dispersion of the plumes were identified to be the tidal and wind driven currents over the depth. Another local phenomenon to consider was the run-off from peak precipitation events, as this results in high background turbidity levels. Analysis of local sediment samples is required to obtain insight in the fines content, required for the estimation of the sediment flux, and the distribution of particle sizes and the particle density to determine the settling velocity.

Insight in the work method and duration of the dredging cycle provides information to determine the temporal distribution of the source terms to suitably simulate the loss of fines over time, making a distinction for the presence of the source between day and night cycles and during relocation. The primary source term contributing to the release of fines, identified to be the bucket drip, was spatially distributed to simulate the relocation of the backhoe. An additional method step was introduced by estimating the local fines content for each source term over the dredging volume, resulting in a more representative approach for dredging volumes exhibiting a heterogeneous distribution of the fines content compared to using a single value for the fines content. The source terms were estimated using an existing method by Becker et al. (2015) and distributed over multiple sediment fractions, to include the representation of the smaller particles, affecting the
far-field SSC in the model.

The effects of tidal and wind-forcing were incorporated using a 3D model, while running different hydrodynamic scenarios to test the effects for a variety of flow conditions. The grid resolution was chosen to ensure an accurate representation of the spatial distribution of the sediment concentration resulting from the bucket drip. The source terms were equally distributed over the depth to simulate the gradual loss of the fines over the depth by the bucket drip. The selection of an appropriate formulation for the settling velocity, to account for the local hydrodynamic conditions and sediment characteristics, increases the representation of the distribution of fines over time.

The model results indicated that for both a stationary and relocating source term, an accurate
depiction of the average SSC values over longer time periods as days and weeks is simulated, while the relocating source tends to estimate peak concentrations more accurately, as the source location and quantity is represented more precisely. Turbidity thresholds, set for the Black Rocks project, were only exceeded on one occasion during the occurrence of a current reversal for the relocating source, but not for a stationary source. This indicates the added value of applying a more detailed approach to simulate the turbidity stresses. Following the suggested additions to the methods an updated approach to simulate the turbidity stresses by a backhoe dredger was proposed. Further research into refinement of the method, focusing on the spatial distribution of the source and appropriate spatial and vertical grid resolution, can increase the suitability of the suggested method for simulating turbidity stresses induced by a backhoe dredger.

The lock of Hansweert, located in the province of Zeeland in the Netherlands, serves as a crucial inland shipping node between the Western Scheldt estuary and the Rhine Delta. The outer harbour of the lock complex provides the connection to the Western Scheldt and accommodates waiting facilities for inland ships. The Western Scheldt is a vital gateway for maritime traffic, linking the Port of Antwerp to the North Sea. As the navigation channel of the Western Scheldt is located close to the outer harbour of Hansweert, multiple ship incidents at this location are attributed to the water motions generated by passing seagoing vessels on the Western Scheldt. This research investigates how the water motions induced by passing vessels in the Western Scheldt contribute to unsafe situations in the outer harbour and locks of Hansweert, and what preventative measures can be identified to effectively minimize incidents and mitigate risks.

Investigating the incident records reveals that the key contributors are the primary water motions generated by the passing vessels in the Western Scheldt. The phenomenon, experienced as a sudden lowering of the water level and suction forces, can lead to the breakage of mooring lines and uncontrolled movements of inland ships, resulting in a range of safety hazards and operational disruptions. Several documented incidents, field studies and interviews highlight the urgency for effective measures to mitigate the potentially harmful effects of passing vessels on the ships in the Hansweert outer harbour and locks.

A seven-week measurement campaign, involving 1281 passages of so-called oversized vessels, reveals distinct patterns of water level fluctuations during a vessel’s passage. A vessel is considered oversized if its length exceeds 210 metres or if its draught is larger than 10 metres. These patterns are described as a translatory drawdown wave travelling into the harbour, reflecting against the lock complex and oscillating back and forth in the outer harbour until dampened. The key parameter characterizing this wave is the lowering of the water level, referred to as the drawdown height. The average measured drawdown height approximates 6 centimetres, with maximum observations up to 40 centimetres. The main factors influencing the drawdown height are the vessel’s passing distance to the outer harbour, its speed relative to the currents and its dimensions, shown by a correlation analysis between the parameters describing the passing vessel and the generated drawdown height. Extreme drawdown events were exclusively observed during a combination of a relatively high speed through the water of the seagoing vessel and small passing distances relative to the harbour’s entrance.

The impact of the drawdown effects on the inland ships is determined by the forces generated by the pressure difference along the ships, caused by the inclination of the water level. A critical drawdown height of 12 centimetres is set, based on existing force criteria and the linear relation between the drawdown height and water level slope. To improve on the existing drawdown height prediction methods, a site-specific drawdown height prediction equation has been derived. Validation of this equation using the observations made during the measurement campaign yields a Pearson correlation coefficient of 0.81 and an Mean Absolute Error score of 2.2 centimetres.

Preventative measures are identified, aiming to minimize incidents and mitigate the risks related to the water motions induced by passing vessels. The predicted drawdown, generated by the passing vessel, is kept below the critical level by recommending a maximum speed related to the passing distance and dimensions of the vessel. Practically, this measure could be applied as a calculation tool or as an overlay on the pilot’s electronic sea chart. Coupling this information with awareness campaigns for pilots will contribute to minimizing the adverse effects on the ships in the outer harbour. The resilience against drawdown-induced risks could be strengthened by restricting the maximum combined width of ships moored alongside. Furthermore, by limiting the excessive slack in the lines of the moored ships, through signage and floating bollards, the movements of the ships will be restricted, reducing the risk of line breakage. Notifications of anticipated critical drawdowns would allow traffic controllers or lock operators to caution the inland ships and delay the lock chamber door openings, whilst alerting the passing vessel. Incorporating the mitigation measures recommended in this research could positively impact the safety of navigation in the Hansweert outer harbour and locks.

The Dutch government has set an ambitious target of reducing CO2 emissions by 55% by 2030, primarily through the development of offshore wind farms in the North Sea. While this transition supports sustainability, it also reduces available space for maritime traffic, increasing the risk of incidents. In response, this research aims to improve the detection of anomalous behaviour in the North Sea using machine learning, assisting Dutch Coast Guard operators in their monitoring tasks.
The primary focus of this study is to detect anomalous cargo vessel behaviour, specifically drifting, which has safety implications, as evidenced by the Julietta D. incident in January 2022. The research uses Automatic Identification System (AIS) data to monitor vessel trajectories and apply a machine learning-based anomaly detection model. This model uses features extracted from ship motion (e.g., speed, rate of turn), spatial properties (e.g. presence in anchorage area) and metocean condition (e.g., wave height) to detect anomalous behavior. The Local Outlier Factor (LOF) algorithm is employed to identify local outliers in a two-dimensional embedding of vessel trips, which is created using a density-preserving dimension reduction technique called densMAP.
The model successfully detects anomalous vessel behaviour within 30 minutes of occurrence, demonstrating its potential for real-time monitoring. In a case study of the cargo vessel Julietta D. incident, the model identified the drifting behaviour of this vessel, validating its effectiveness. The model also shows promise in detecting other types of anomalous behaviour, such as sudden changes in speed, and presence in defined areas.
While the model performs well in detecting a drifting incident and certain anomalies, it does not account for global outliers or identify other types of anomalous behaviour. Additionally, due to the limitations of AIS data, heading information was not incorporated. The research contributes to the safety monitoring of maritime traffic by providing a scalable, interpretable, and operationally feasible machine learning approach for the detection of anomalous cargo vessel behaviour.
Future work should focus on integrating time components, and supervised learning with labeled incident data to further refine the model. Ultimately, this research offers significant potential for enhancing operational safety and supporting the Coast Guard in the monitoring of maritime traffic in the North Sea.

Rapid changes in the marine environment are taking place worldwide, for which infrastructural development is one of the most extreme anthropogenic drivers. It comes in many forms and covers functionalities for multiple usages, such as coastal defence, transportation, and energy production. Marine infrastructure modifies seascapes by replacing natural habitats and changing environmental conditions critical to habitat persistence, potentially leading to its degradation and biodiversity loss. Although primarily built to meet functional criteria, their designs can incorporate nature-inclusive elements that benefit ecosystem components, i.e. species, habitats or ecosystem processes.

The implementation of nature-inclusive marine infrastructure is increasingly encouraged, but currently fails to achieve impact at scale due to the fragmented nature of individual measures. Without shared objectives, parallel efforts to enhance targeted ecosystem components might not lead to the desired effect, and could even interfere with each other. A jointly established strategy is required to design and implement nature-inclusive marine infrastructure that meets the wanted impact. Such as strategy is based upon overarching objectives for promoting selected ecosystem components at system-scale, i.e. the seascape dimension required to achieve the desired effect. It is furthermore essential to determine and develop design measures that would induce impact and to define the scale needed for these interventions. It is recognized that marine construction works first serve human needs, not nature goals, but nature-inclusive marine infrastructure does provide an opportunity to benefit ecological values at system-scale. Marine construction works can be synergized with the functioning of the ecosystem in which they are build much better than is currently practiced, and one should always strive for nature-inclusive features in their designs.

This dissertation provides insight into the process to identify, select and implement measures for nature-inclusive marine infrastructure to make a desired impact at system-scale, i.e. the seascape dimension required to achieve that impact. First, a stepwise approach is presented to define clear objectives for improving targeted ecosystem components, in which ruling polices, environmental conditions and the potential of using marine infrastructure are aligned. Stakeholders jointly select the most effective design measures for nature-inclusive marine infrastructure to reach shared targets for ecological impact. Next, it is key to define the scale of these interventions needed to achieve significant impact. A method is developed to select appropriate measures to benefit ecosystem components at a range of scales, from micro-scale (materials used) to mega-scale (connectivity between systems), and to assess their potential effects quantitatively. And finally, it is emphasized that nature-inclusive marine infrastructure can only make impact at system-scale if scientific knowledge about ecosystem functioning is paired with industry-based approaches used for infrastructural development. Five basic principles are provided for establishing this alignment, in order to effectively implement nature-inclusive design measures.

The approaches for engineering nature-inclusive marine infrastructure are demonstrated by defining a strategy to develop European flat oyster (Ostrea edulis) reefs in offshore wind farms in the Southern North Sea. The huge roll out of offshore wind farms aimed at renewable energy production in the North Sea is currently one of the most prominent marine infrastructural developments globally. Its potential for promoting targeted ecosystem components is recognized, as offshore wind farms provide an undisturbed seabed as well as hard substrate infrastructure, which both provide suitable habitat for a wide range of marine organisms. The results of a dedicated monitoring survey in existing offshore wind farms show that their presence indeed contributes to an increase in marine epibenthic biodiversity. Using the offshore wind farm areas specifically for the development of flat oyster reefs has gained particular interest. This species went near to extinct in the 20th century due to overfishing and diseases, and restoring flat oyster reefs in the North Sea meets international policy agreements. Offshore wind farms can be designed to include elements that benefit the restoration of this flat oyster population, such as using a type of hard substrate as scour protection that is favourable for oyster larvae settlement.

In conclusion, this dissertation provides guidance for defining management strategies for implementing nature-inclusive marine infrastructure to achieve impact at system-scale, with an emphasis on flat oyster reef development in offshore wind farms in the Southern North Sea. Application of the presented methods and outcomes of the studies could lead to the realisation of truly effective nature-inclusive marine infrastructure, seizing the opportunity offered by infrastructural developments to have a positive impact on the marine environment.

In the early project phase, decisions are made when considering a port basin berth layout that affects the outcome and the success of the project. In order to make a decision regarding the berth layout, port planners create a set of variants for comparison and assessment in order to pick the basin berth layout that suits the project goals the best. The selected basin berth layout is the preferred variant that will be used to eventually be realised. However, since the decision in the early project phase has a great influence on the entire project, port planners want to improve the decision-making for selecting the best berth layout. This research aims to improve the decision-making process for selecting the berth layout of preference by developing a design generation method for berth layouts and its respective pathway. This method might give insights into optimal berth layout configurations and its pathway in order for decision-makers to assess their preferred variant resulting from the set of variants developed by experts and the generated layout. After the method is developed, the method is tested on conceptual benchmark cases and a real case in order to assess whether such method can add value, or improve, design solutions of port basin layouts during the early project phase. Although limited studies and methods exist that have resemblance or commonalities with berth layout optimisation, the idea is in its infancy. Methods for berth layout optimization have been developed to generate berth layouts and its re spective pathway through the basin in this report. The optimization is separated into two steps: firstly, berth location optimization using a pre-defined central basin pathway, and secondly, optimization of the pathway belonging to the respective berth layout. The separation of the berth location and pathway optimisation reduces computational time. The heuristic berth location optimization optimizes the locations of the berths to minimize the central pathway dredging, while satisfying constraints prescribing a minimal distance between the berths. After the berth locations are optimized, the pathways can either be optimized by means of a heuristic pathway approach, or by means of an exact mathematical pro gramming approach, both of which are developed in this research. The heuristic pathway optimization approach models required dredging by translating the dredging for a berth into a graph with weighted edges and then sequentially defining the route that requires the least dredging per berth, eventually forming the complete basin pathway. The exact pathway approach uses a mathematical programming setup. The methods are applied to conceptual benchmark cases a real-life case. The benchmarks differ in basin dimensions, basin bottom profile, and fleet characteristics. The real-life case concerned the Scheurhaven, which is a small port basin for mainly tugboats. The layout of the Scheurhaven had to be adapted to fit more tugboats in the basin. The Scheurhaven case was optimised with the heuristic approach, due to the potentially large computational time of the exact approach. As the berth locations were limited and the method lacked features to make the design comparable, such as structures and berth geometry, only heuristic pathway optimisation was done.

Inland shipping is widely acknowledged as a sustainable mode of transportation due to its low energy consumption and emissions in comparison to road and rail transport. However, with growing concerns around reducing emissions in the transportation sector, there is pressure to address environmental issues associated with inland shipping. In the Netherlands, a Green Deal has been formulated to outline the goals for reducing CO2 emissions by 2030 and other environmental pollutants by 2035 in inland navigation, to enable us to take the next step towards a climate-neutral society by 2050. This increasing pressure raises the question of how to get insight of the energy consumption and the associated emissions from inland shipping. To date, an accurate method is lacking that is able to estimate the total resistance, the propulsive power and in turn the energy consumption in shallow water and thus to quantify the CO2 emissions. Over the years, several power estimation methods have been developed for inland vessels, with the Rijkswaterstaat power estimation method being one of the most widely recognized. Recently, Backer van Ommeren (2019) investigated the Rijkswaterstaat power estimation method and found that certain assumptions and parameters used in the method were not well-founded, and that some approximations were unnecessary.
The main objective of this study to conduct a comprehensive literature analysis on Backer van Ommeren (2019) comments and recommendations regarding the Rijkswaterstaat (RWS) or Bolt (2003) method in order to clarify to what extent these recommendations will indeed improve the Bolt (2003) method or if an alternative power method should be proposed instead. This will be accomplished through a comparison process of the power results as a function of sailing speed, water depth, and channel dimensions for various types of inland vessels, utilizing the selected methods that will be derived from the literature study along with Backer van Ommeren (2019) recommendations applied to the original method. After coding these methods in Python and analyzing their results, the best practice(s) that will be derived from the test cases, will be implemented on two classes of motor vessels an M6 and an M8 to estimate the resistance and the power and then they will suggest to Rijkswaterstaat for potential future use.
To achieve the main research objectives, the following research was conducted. Initially, a literature analysis on the available resistance methods, how they consider and divide the several resistance components, and which are the shallow water effects that affect them, was done in order to evaluate their performance in terms of power estimations. Secondly, the comments made by Backer van Ommeren were presented and analyzed. Specifically, he investigated various formulations for calculating the return flow, water level depression, and characterizing the waterway as normal, narrow, wide, or very wide. This study was accomplished through the use of specific power efficiency and resistance coefficients. Based on his study, he derived a method, the Backer method (Backer van Ommeren, 2019) and suggested a number of formulas to be further tested. After completing the literature review, the findings lead to the selection of the power methods that will be treated in this thesis and the kind of improvements that will be applied to the original Bolt (2003) method.
Subsequently, from the literature study and Backer van Ommeren (2019) review, four methods were derived to be simulated and tested in this thesis. These methods include the TU Delft method, Bolt method with speed correction, Bolt method modified by Backer, and Backer method. The simulation was achieved with two rounds of tests that are conducted, firstly the “Academic test case” and secondly the “Real-world test case”. In the “Academic test case” five methods were simulated and the most promising that met specific criteria are selected. Then, in the “Real-world test case” the selected methods as they were derived from the “Academic test case”, were further evaluated for the selection of the best practice(s). The first round of tests is applied to two classes of motor vessels in narrow and wide waterways with shallow, intermediate and deep water depth conditions and the results include the total resistance and the brake power while the second round simulates only one motor vessel of class six in wide waterways for the same depth conditions as previously and the outcome includes the delivered power. The “Real-world test case” is divided in two parts. The first part includes the comparison between the estimated and the measured delivered power in order to assess the performance of the methods with the real data. The second part evaluates the performance of the methods in the presence of a current flow, by comparing the fuel consumption in upstream, downstream and round trips.
The evaluation of the methods in a real-world test case led to a number of conclusions, and the best practices were recommended accordingly. It should be noted that the comparison process was based solely on a single real-world case, utilizing a singular set of real data. It is important to be conducted additional comparisons across multiple real cases in order to increase the understanding of the accuracy of the various methods being compared. In the context of power estimation in shallow water, both the Bolt (2003) method and TU Delft method(Jiang, Baart & van Koningsveld, 2022) have demonstrated remarkable accuracy in their predictions while Backer method and Bolt method modified by Backer are not recommended for power predictions. Notably, Bolt (2003) method has proven to be effective in estimating power within a speed range of 2.5m/s to 3.5m/s while TU Delft method (Jiang, Baart & van Koningsveld, 2022) showed accurate predictions within a speed range of 2.5m/s-4m/s (accurate as defined within 20% of the observed value). Regarding the intermediate and deep water conditions, only TU Delft method (Jiang, Baart & van Koningsveld, 2022) showed acceptable performance in power estimation again for sailing speeds varying 2.5 m/s – 5 m/s. The power demand at very low speeds for all the three methods display a considerable deviation between the estimated power output and the actual values, surpassing the acceptable rate of 20%. This can be attributed to two reasons. At low speeds, the interaction between a sailing vessel and the boundary layer becomes more pronounced, causing the ship to experience turbulent effects that dominate the boundary layer more intensively. As a result, the vessel experiences increased resistance, requiring more power. Secondly, in actual operating conditions, a ship has a minimum power engine setting that is dependent on the engine characteristics. So, when the ship is moored and the "hotel mode" is on, as the ship not having a separate auxiliary power unit, a propeller brake is used to allow the turbine to continue running and generate power without the propeller spinning. This effect does not consider by the power estimation methods that rely on parameters such as sailing speed and water depth. The Backer (2019) method demonstrated satisfactory performance in predicting resistance and power for both types of motor cargo vessels within narrow waterways. This method effectively accounted for the variations in depth by accurately estimating lower resistance and power demand as the depth increased. However, Its accuracy in wide waterways diminished due to the equations' unsuitability for such conditions, by generating nearly identical resistance and power estimations for the three different water depths. Based on the aforementioned restriction, it is not recommended to employ this particular approach for subsequent power estimations. As regards the Bolt method modified by Backer performs poorly in estimating resistance and power across narrow and wide waterways with varying depths. It consistently yields similar results for shallow, intermediate, and deep depths at a specific sailing speed. Therefore, it is not recommended as an improvement to the Bolt method. In the presence of current flow, three methods have shown promising results. Specifically, the TU Delft method (Jiang, Baart & van Koningsveld, 2022) is recommended for motor vessel, as it produces deviations from real measurements of 0.93% for upstream, 1.36% for downstream, and 0.45% for round trips. Also, TU Delft method (Jiang, Baart & van Koningsveld, 2022) is recommended in case of pushed and coupled convoys as it has been found to produce the smallest deviations in upstream sailing, with a maximum of 3.9% while the deviations observed for downstream sailing and round trips are around 1.9%. Bolt (2003 )method and Bolt method with speed correction, were found to produce acceptable deviation rates of around 7% for upstream trips, with the benefit that these methods require less detailed input data. Nevertheless, for downstream and round trips, the deviations were much higher, reaching up to 80% and 30%, respectively and event that requires additional investigation and validation.

This study integrates strategic decisions and operational control systems in autonomous shipping. By providing ships with situational information and adding a virtual operator, we show that vessels can make informed choices regarding their route and engine settings. To demonstrate this integration, we developed new components that were tested in three lab experiments.
The 'green routing' experiment showed the bridge between the control system of the autonomous vessel, operated via Robot Operating System (ROS), to the simulation environment of OpenCLSim. We developed a real-time variant of OpenCLSim and a communication component that could expose the state of the OpenCLSim simulation with the ROS system. This experiment showed that the path provided by the simulation was followed by an autonomous vessel.
The 'green steaming' experiment showed that the ship could also adapt its speed based on information from the simulations. We developed an additional communication component capable of advising the vessel about its velocity. Together with the green routing capability, this forms the basis for more complex experiments.
The 'port call' experiment showed a potential use case of the green routing and green steaming capabilities. We created a waypoint layout similar to the port. While a ship is sailing, every five seconds, twelve simulations are computed. The scenarios vary in engine order, route choices, resulting in varying emissions, fuel, and cost. We evaluated the impact of different tactics such as green routing, green steaming, and full-speed sailing on operational behavior like steering and engine order. Our approach, using a real-time version of a Vessel in the OpenCLSim simulation software, enabled predictive simulations to facilitate the chosen tactic based on a given strategy. Integrating simulations to evaluate the options with the control systems can develop into a valuable tool for optimizing vessel performance and reducing environmental impact in autonomous shipping operations.

The increasing severity of river drought poses a potential threat to the operations of ports using rivers as hinterland connections. River droughts have impacted navigation in various rivers worldwide, including the Rhine river where instances of low water levels in 2018 and 2022 caused disruptions in navigation. As a consequence, inland vessels were forced to reduce their cargo loads. Seaport terminals that serve as crucial links between sea vessels and inland vessels may be impacted by changes in fleet composition, thereby affecting a terminal's cargo handling operations and storage. However, there is a lack of research quantifying the effects of low river levels on seaport processes and determining suitable methods to assess this impact using vessel movement data.

To address this research gap, this study aims to quantify the impact of low river levels on seaport processes by focusing on the EMO dry bulk terminal within the Port of Rotterdam as a case study. Given the connection between this port and the Rhine, which is known for its vulnerability to drought and serves as a vital route for inland navigation, the analysis begins by examining the impact of reduced river discharge on the dry bulk fleet sailing from Rotterdam to Germany utilising Information and Tracking System for Shipping (IVS) data. Additionally, Automatic Identification System (AIS) data is employed to assess the service time, the number of vessels and the berth occupancy within the terminal to quantify the impact of low river discharge on the cargo handling process within the terminal. Specifically investigating the effects on vessels being loaded and bound to the hinterland and those being unloaded after arriving from the sea. Finally, the study analyses the impact on the storage capacity of the EMO terminal using monthly cargo data provided by the terminal, by studying the balance between the amount of cargo being unloaded and loaded.

The findings show that vessels sailing along the Rhine are required to reduce their load as discharge decreases, leading to an increased number of vessels. However, this compensation by more vessels does not fully offset the load losses, resulting in a decrease in the total load carried per day when discharge decreases. Consequently, more vessels arrive at the EMO loading berths during low discharge periods to compensate for the reduced load and therefore loading time for vessels at these berths is shortened. Due to the increased vessel arrivals, the berth occupancy at the loading berths increases to a maximum of 65%. On the contrary, the berth occupancy at the unloading berths remains unaffected. Cargo flow analysis shows that the lowest cargo loading into inland vessels occurs during months without low discharge, rather than during the months with the lowest discharge. Additionally, the share of rail transport increases during low discharge months but remains below maximum capacity, indicating sufficient slack to handle all cargo. The stockpile analysis reveals a small surplus during low discharge months, although not as significant as in months with normal discharge levels.

Overall, the findings indicate that the large size of the EMO terminal allows it to withstand the impacts of past periods of low river discharge. As the loading berth's occupancy is not at its maximum capacity and the unloading berths remain unaffected, there is sufficient slack to accommodate additional vessels. Accordingly, adequate vessels are loaded to transport cargo to the hinterland, ensuring no impact on the stockpile and thus maintaining the storage operations at the EMO terminal without disruption.

While this research provides valuable insights, it is important to acknowledge that terminals of varying sizes or handling different cargo types may experience different impacts and should be subject to further investigation. Additionally, the limited availability of AIS and cargo data, with only one year of extreme drought (2022) for analysis, prevents drawing definitive trends and making long-term assumptions for future scenarios. Nevertheless, this study's methodology can be adopted in related studies to analyse more terminals and gain further insights.

To facilitate the energy transition, effective collaboration among all stakeholders is necessary. However, there is currently a lack of understanding regarding the impact of different components in the value chain on the energy system's overall structure and the final energy price. This knowledge gap poses a significant obstacle to cooperation and progress in the energy transition. It creates the risk that effort goes into developing certain partial solutions when they may not be feasible from a larger system perspective. By focusing on their own component, stakeholders do not fully take into account the needs and interests of others involved. As the development of green hydrogen projects is in its early stages, it is important to think in terms of systems. Stakeholders should establish an ecosystem where players operating in different parts of the value chain are collaborating together. This helps to de-risk projects, share lessons and promote the development of innovative, first-mover initiatives.

This study aims to develop a standardised method to evaluate offshore wind to hydrogen concepts through a techno-economic analysis. This analysis method combines technical analysis with economic evaluation of projects and concepts to determine the potential economic outcomes and impacts of implementing a particular technology or project.

Through stakeholder interviews, the study found that stakeholders in the offshore wind and hydrogen market have distinct objectives and concerns. Key factors influencing their willingness to contribute include confidentiality, competition, and reputation.

To increase the transparency of the model, it was developed in Python. A standard notation system was developed, which was presented alongside the model's results. This should aid in the understanding of the underlying assumptions.

The dredging industry is a contributor to the greenhouse gas (GHG) emissions due to the energy-intensive process of dredging and transporting sediment. This industry has to reduce the GHG emissions due to future possible restricting regulations on GHG emissions. The dredging industry is shifting towards more environmentally friendly fuels, but designing new vessels which can run on these fuels will be a time consuming transformation. Though, the demand of dredging activities is growing, think of construction of offshore wind farms and creating flood defences against sea level rise. To minimize the costs due to the high GHG footprint in the short term, Van Oord should be able to estimate the energy consumption (GHG emissions) based on different dredging strategies.

Van Oord uses a model to estimate energy consumption that accurately describes the majority of dredging projects, based on the power installed, dredging time, and a power coefficient term. This power coefficient term is based on empirical data and may result in a less accurate estimation of more complex (new) projects such as offshore wind farms and cable dredging, which are the new opportunities arising for dredging companies. To better estimate energy consumption during these complex dredging operations, a physics-based and semi-empirical method is developed that can more accurately estimate energy consumption based on certain dredging strategies. Previous research already looked at the sailing phases of the dredging cycle, therefore the main objective of this thesis is:

To quantify the energy consumption of different TSHD dredging strategies based on physics for the loading phase.

To achieve this research objective, first a literature study is conducted to list the different physics-based methods available to estimate the energy consumption. The energy consumption of a TSHD is divided into five main energy consumers (propulsion system, dredge pumps, jet pumps, bow thrusters and board net) in which the energy of the individual components is described by a power and a time term. The time component is represented by the duration of the loading cycle, which in this study is limited to the filling process of the hopper until overflow. The power term of the jet- and dredge pumps have been estimated by the (adjusted) in-house physics-based methods of Van Oord. The board net and the bow thrusters have been estimated by data analysis of a case study. The goal of this research is to develop a method to estimate the required propulsion power and a tool to bring all methods together to simulate the total energy consumption during the loading phase based on different dredging strategies.

A model is developed to estimate the required propulsion power during loading. The model development is divided into three phases; The first phase describes the development of a semi-empirical physics based model. In this, the various resistance forces acting on the vessel, suction pipe, and draghead are calculated based on stationary parameters such as vessel dimensions, and project parameters. The project parameters, including water depth, trailing speed, and visor angle, are extracted by filtering the actual data from the case study. In this way the estimation model is set equal to a reference case. Finally, the output of the estimation model is calibrated by comparison with the actual data of the case study. This calibration phase is an iterative process in which the accuracy of the model is described and increased.

The model shows that it is possible to calculate the required propulsion power based on operational parameters, such as trailing speed. Furthermore, the model provides insight into the amount of resistance on the three components (draghead, suction pipe and vessel). The power curve follows a quadratic pattern for increasing trailing speed, which appears to be a reasonable estimate. When comparing the model to the actual data it can be seen that the model underestimates at lower trailing speed and over estimates at higher trailing speed. By finding correlations between visor angle and trailing speed the model is calibrated and seems to better fit the dataset, however the slope of the curve still has a large deviation compared to the regression line based on the actual dataset. Therefore, the model needs to be further developed before it can be included as an addition to the existing models within Van Oord. The static friction term is not included, which could compensate the underestimation of the model and the high cutting forces are the potential reason for the overestimation at high Van Oord Marine Ingenuity iii Delft University of Technology trailing speed. For now, the current developed model falls within the reference dataset for the trailing speed between 1.6 [kn] and 1.9 [kn], thus making it a reasonable first estimate of the required propulsion power.

The OpenCLSim python package, which can be used to simulate discrete events, is used to simulate the dredging processes of the loading phase. A plugin for this python package is developed to calculate the total energy consumption during these processes. The propulsion model is integrated (with the set limitations) in this plugin together with the four other power estimation methods (dredge pumps, jet pumps, bow thrusters and board net). The simulation tool runs based on four input characteristics: vessel parameters (TSHD), site characteristics, dredging strategy, and data describing the bow thrusters and board net. The output of the simulation includes required power, duration, and consumed energy. Additionally, the simulation estimates the fuel usage,
emissions, and project costs associated with energy consumption.

The main ability of the simulation tool is that it can visualize the energy consumption (and emissions) based on dredging strategies and location. This enables the prediction and potential reduction of emissions in sensitive areas, such as fine dust emissions near cities. By using this simulation tool, a dredging plan can be created based on dredging strategies (trailing speed) to reduce emissions in these sensitive areas. To better demonstrate the other capabilities of the developed plugin within the OpenCLSim Python package, the simulation tool is applied to an imaginary project called Barachi. This project has strict regulations that prohibit overflow and apply emission taxes. Two dredging strategies are compared based on the limitations of the developed propulsion model: trailing speeds of 1.6 [kn] and 1.9 [kn]. The results show that, first of all, the project duration will decrease with an increasing trail speed. Secondly, the increase in power has a greater effect on energy consumption than the decrease in project duration, meaning that energy consumption will increase. Since fuel use and corresponding emissions are linked to energy consumption, they will also increase. However, the cost analysis provides a different view. In this case, because the ship’s operating costs are governing, faster trailing is the most cost-efficient, even if an emission tax of 200 euros/ton CO2e is applied.

To conclude, by creating a model to estimate the propulsion power and by integrating this model in a simulation tool, it is possible to quantify the energy consumption of different TSHD dredging strategies based on physics for the loading phase. Subsequently, the simulation also provides insight into the fuel usage, carbon emissions, and costs of the project. Further development and validation of the propulsion model is needed to give a more accurate estimation of the required power. Firstly, the static friction component should be included in the estimation model which could potentially solve the underestimation at lower trailing speed. Secondly, a maximum trail speed limit should be set based on the available propulsion power with respect to the total power distribution of the vessel. This limit should be included in the simulation tool, since it is linked to the other power consumers and the operational parameters. Thirdly, the propulsion model can only be used in saturated sand projects. Other cutting models based on cutting of silt, clay and rock should be added in the propulsion model to be able to apply the model in these soil conditions. Finally, the use of the tool is limited to dredging projects where overflow is not allowed. The suction production and the settling process within the hopper should be added to expand the capabilities of the tool to projects where overflow is possible.

Currently, inland waterway safety assessments rely heavily on historic accident data and expert opinions, often lacking comprehensive qualitative and quantitative information. Addressing this gap, this thesis introduces a method based on Automatic Identification System (AIS) data to identify anomalous vessel behaviour for enhancing safety assessments.

The proposed methodology establishes definitions of normal vessel behaviour and identifies deviations from these norms as anomalies. Analysing vessel trips recorded in AIS data logs, various features—including speed, acceleration, direction, manoeuvrability, and positional attributes—are extracted to define vessel behaviour.

The Uniform Manifold Approximation and Projection (UMAP) algorithm reduces the multidimensional features into a two-dimensional embedding to condense the vessel behaviour into a manageable form. This reduction technique preserves the inherent behaviour while representing similarities within a 2-dimensional space. Subsequently, the K-means clustering algorithm is applied to group vessels displaying similar behavioural patterns. The hyperparameters for clustering are determined using the elbow method and multiple scoring metrics.

Application of this methodology to the Moerdijkbrug at the Hollands Diep and Schellingwouderbrug at the IJ reveals clusters with similarities in vessel direction and paths. Several atypical patterns were observed and further investigated, analysing less than 1% of the data set in both cases, revealing two distinct patterns classified as probable accidents in the IJ case. These findings demonstrate the potential of the proposed method in identifying specific vessel behavioural anomalies with implications for safety assessment on inland waterways.