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Machine Learning-based Anomaly Detection in XMM-Newton Instrument Telemetry Data

Master thesis (2025) - T.L.E. Dijkstra, Stefano Speretta, P. Gómez, J. Guo, R. Sabzevari

Machine learning Anomaly Detection Spacecraft Telemetry

To ensure the safety of a spacecraft, operators collect thousands of telemetry signals and monitor them for anomalies, which is both expensive and time-consuming. Space agencies have been researching Machine Learning (ML)-based Time Series Anomaly Detection (TSAD) methods to impr ...

Neutrally stable tape spring actuation using shape memory alloys

Master thesis (2025) - N. Groeneweg, Ines Uriol Balbin, Bergsma Bergsma, Jurgen Vanhamel

Satellite Manufacturing Shape Memory Alloy Delfi-PQ Tape spring ESATAN TMS Thermal modeling

On the Delfi family of satellites, antenna deployment currently takes place using a burn wire system. This requires the antenna to be of the same length as the satellite body. To decouple this length, a new mechanism is needed. Neutrally stable tape springs actuated by shape memo ...

Impact of Alternative Transport Tariffs on Battery Performance

An Optimization and Distribution Network Model

Master thesis (2025) - P.A.C. Wetselaar, R.A. Hakvoort, Ozge Okur

The Dutch energy system is evolving rapidly, transitioning from centralized fossil-based generation to decentralized renewable sources. At the same time, electrification is increasing across heating, mobility, and industry, placing significant strain on the electricity grid. This ...

The Dutch energy system is evolving rapidly, transitioning from centralized fossil-based generation to decentralized renewable sources. At the same time, electrification is increasing across heating, mobility, and industry, placing significant strain on the electricity grid. This imbalance between supply and demand leads to severe congestion issues, costing the Netherlands approximately 20-40 billion EUR annually. While expanding grid infrastructure is an option, it is costly, time-consuming, and constrained by resource shortages. As an alternative, market-driven flexibility solutions such as battery storage, alongside regulatory interventions like alternative transport tariffs, are being explored for their potential to relieve congestion.
This research examines how alternative transport tariffs impact battery behavior and grid stability in the Dutch distribution network. Specifically, it evaluates the effects of two newly introduced tariff structures: Time-of-Use (TOU) tariffs, which warrant flexible participation on the grid, and Time-Block (TB) tariffs, which provide discounts for energy usage within predefined time windows. The study assesses battery behavior, congestion relief, and financial viability under these tariffs, comparing their effects to a baseline scenario without alternative transport tariffs and without a battery. A key objective is to determine whether non-market-based mechanisms such as alternative transport tariffs can enhance congestion management and whether the TOU tariff should be extended to the distribution grid.
To analyze these effects, a quantitative modeling approach is used, combining a Mixed Integer Linear Programming (MILP) model, which optimizes battery operation in the day-ahead and intraday electricity markets, with a PyPSA distribution network model, which simulates battery interactions within the grid. The study evaluates three scenarios: no tariff, TOU tariffs, and TB tariffs. A sensitivity analysis is conducted to examine the robustness of results under different price fluctuations and seasonal variations.
The results show that battery storage significantly improves congestion management by reducing line overloading, renewable energy curtailment, and peak loads. However, the extent of these benefits depends on the tariff design. The Time-of-Use tariff proves to be an effective mechanism, providing a structured yet flexible approach that allows batteries to optimize charging and discharging based on real-time grid conditions. This improves both their financial viability and their role in congestion relief. In contrast, the Time-Block tariff imposes rigid constraints that limit battery owners’ ability to adapt to market signals, significantly reducing both the financial attractiveness and technical effectiveness of batteries for congestion management. Seasonal variations also affect battery performance, with winter periods exhibiting higher volatility due to fluctuating energy demand and supply conditions. While some peak shaving occurs under all tariff scenarios, its effectiveness is reduced under the TB tariff because of its restrictive design...

Balancing Markets: Imbalance Pricing Designs

Analysis of Implicit Balancing by Flexible Assets within European Balancing Markets

Master thesis (2025) - E.S. Vermeulen, Kenneth Bruninx, A.F. Correlje, Rutger Bianchi

Imbalance pricing design Implicit balancing Flexible assets

The increasingly integrated renewable energy sources have a strong intermittency in electricity supply, resulting in increasing mismatches between electricity supply and demand. This has led to an increase in imbalances in the electricity grid, heightening the need for regulating ...

The increasingly integrated renewable energy sources have a strong intermittency in electricity supply, resulting in increasing mismatches between electricity supply and demand. This has led to an increase in imbalances in the electricity grid, heightening the need for regulating power, such as flexible assets. Currently, the balancing markets are experiencing a high volatility in system imbalance and imbalance prices, resulting in market and system instability.

Previous studies have largely focused on how renewable energy sources lead to an increase in system imbalance and have stressed the need for flexible assets. Furthermore, several studies show that flexible assets can make significant profits in today's balancing markets by optimising their implicit balancing strategy. However, little attention has been devoted to the price incentives provided by the different pricing designs in the EU and how their remuneration structure affects the implicit balancing behaviour of flexible assets. As flexible assets are increasingly deployed on the balancing market, any strategic or gaming behaviour might have a significant negative impact on grid stability and system costs. Therefore, this research aims to answer the following research question:

What implicit balancing behaviour do flexible assets show in different imbalance settlement designs and what balancing market design recommendations can be provided based on this?

This research question is explored using mainly a quantitative approach. First, a literature review on European balancing markets is provided, explaining how the EU Balancing Guideline forms a framework for the balancing markets in EU. Furthermore, the balancing markets in the Netherlands and Belgium, which serve as case studies in the modelling, are explored in detail. Then, two linear optimisation models are developed to simulate the balancing markets of both countries and to show how the price incentives provided by the markets influence the behaviour of a flexible asset that aims to optimise its profit. Additionally, the impact of the asset's implicit balancing, following three different strategies, on imbalance prices and the asset's own profit is examined. A comparison is made between the results under the two different pricing designs, showing how different design choices affect the opportunities for strategic behaviour and potential market exploitation. The main insights obtained can be summarised as follows:

- A flexible asset can, under certain circumstances, exploit the market with gaming behaviour, in which it intentionally amplifies the imbalance price and thereby enlarges its own profit.
- Marginal pricing, provides a larger opportunity window for strategic and gaming behaviour compared to the averaging of marginal prices. Establishing the imbalance price based on the average of all marginal prices during an ISP can mitigate the asset's effect on the imbalance price, but can eventually not prevent extreme imbalance prices either.
- There are advantages and disadvantages to both single and dual pricing. Single pricing provides a more stable pricing system, but is limited in discouraging overreactive implicit balancing. The dual pricing design discourages overreactive balancing stronger, but this can lead to great losses for BRPs, increasing their financial risks, and can decrease market stability.
- The volume of the system imbalance plays an important role; in ISP with lower system imbalances, flexible assets can only increase the imbalance price to a very limited extend, before a market saturation point is reached where all system imbalance is balanced implicitly. With higher system imbalances, flexible assets can push the imbalance price to much higher, or even extreme values.

As balancing markets evolve with increasing volatility in system imbalances and higher volumes of flexible assets, transaction costs are expected to rise due to higher levels of market participation, growing complexity in forecasting, and potential market saturation effects in quarter-hours with lower system imbalances. These expectations for future conditions emphasise the need for pricing designs that ensure grid stability and market efficiency. Therefore, this research provides several recommendations:

- TSOs should consider re-evaluating the overall pricing design for FRR and imbalance. These two pricing designs are highly interconnected, as imbalance prices should reflect the costs made for FRR. Marginal pricing has both advantages and disadvantages, as it can reduce strategic bidding for FRR, but can reward gaming behaviour in implicit balancing, leading to market instability. A different pricing design might provide a more stable market, where strategic implicit balancing is discouraged.
- The choice between single and dual pricing needs to be carefully considered. Based on this research's findings, single pricing leads to less risks for BRPs and contributes to market stability. However, additional research into the decision-making process of flexible assets under the risks present in both pricing designs is needed to be able to make a stronger recommendation.
- Adjusting other market design variables could help reduce volatility, such as loosening FRR qualification requirements to encourage flexible assets to provide FRR instead of implicit balancing and reducing the ISP to five minutes. Yet, further research is needed to assess the full implications of adjusting these design choices.

The findings presented by this research contribute to current efforts to improve balancing market designs, by showing that both pricing designs have vulnerabilities that allow flexible assets to exploit the market under certain circumstances, which is inconsistent with the objectives of the balancing market. The discussed design choices and future research recommendations contribute to improving balancing markets, to regain grid stability and market efficiency.

However, there are some limitations to consider. The model contains significant simplifications, such as the aggregation of multiple flexible assets into a single asset, which does not fully capture the decision-making process of multiple individual actors with a flexible asset in the real world. Additionally, the assumption that the flexible asset has perfect information and foresight does not correspond to reality. Furthermore, the heuristic optimisation method used may not always produce the optimal strategy for the flexible asset. Based on these limitations, several suggestions for future research are made. For example, using a bi-level optimisation method might provide more refined results of the asset's strategic behaviour. Future research could also consider the wider context of the market, such as how imbalance pricing influences the decision-making processes of numerous BRPs acting simultaneously, without perfect or with limited market information. An analysis from a game-theoretic point of view, showing the interactions among various actors, might lead to more refined or different outcomes when the different pricing designs are compared.

Differential Dynamic Programming for the aof Many-Revolution Solar-Sail Transfers

Master thesis (2025) - R. Minnozzi, Jeannette Heiligers, F. Gámez Losada, Stéphanie Cazaux, F. Oliviero

Optimal Control Solar Sailing Differential Dynamic Programming

Solar sailing is a propellant-free propulsion method, leveraging the momentum of Sun-emitted photons to generate thrust. In Earth orbit, the small and constrained magnitude of the solar-sail thrust with respect to the planetary gravity
implies the need for many revolutions t ...

Optimizing Multimodal Passenger Routing for Airline Alliances

Master thesis (2025) - S.B. Edmonds, A. Bombelli, M.J. Ribeiro, F. Oliviero

Optimization Sustainability Multimodal MILP Airline Rail Alliance Network expansion Intermodal Value of time Passenger Routing Air+Rail Profit Network replacement

This thesis investigates the use of optimization techniques to determine the value of multimodal (Air+Rail) networks. By using Mixed Integer Linear Programming (MILP), the mathematical model derived especially for this use case determines the optimal way for airlines to route the ...

Evaluation and improvement of tracklet correlation methods

Master thesis (2025) - B. Andriessen, S. Gehly, Dominic Dirkx, Sijme Jan Paardekooper

Robustness Space Situational Awareness Computational efficiency Initial Orbit Determination Tracklet correlation Passive optical sensors Cataloging Association accuracy

Nowadays, space-based systems for navigation, communication, Earth observation, meteorology and many other applications are indispensable for services critical for society. In order to preserve these vital applications among the increased risks in space, the Space Surveillance an ...

Nowadays, space-based systems for navigation, communication, Earth observation, meteorology and many other applications are indispensable for services critical for society. In order to preserve these vital applications among the increased risks in space, the Space Surveillance and Tracking segment of the Space Situational Awareness program has been set up in the last decade by the European Space Agency. This segment is occupied with one core activity: maintaining and building up a space object catalog. The object states within it can be used for conjunction assessment, collision avoidance and fragmentation event detection, allowing active satellites to be protected.

For objects in Low Earth Orbit, the Space Surveillance and Tracking segment primarily employs radar, which uses active signals, whose signal strength degrades with the fourth power of the distance. Beyond this orbit regime, passive optical sensors are primarily used, because they do not require an active signal and are therefore able to observe beyond Low Earth Orbit without large power requirements. As a consequence of the sparse optical sensors which have to track the large population of space objects, the optical observing arcs are typically very short: minutes at most. These short optical arcs are called tracklets.

Determining an orbit from a short arc is a challenging problem and is commonly referred to as the too short arc problem. Specifically, this problem entails that a single short arc tracklet is insufficient to construct an orbit with realistic state estimates. In order to obtain accurate state estimates, the object corresponding to the tracklet must be re-observed during a later pass to obtain six independent parameters of high quality. The initial problem to solve, however, is to identify which tracklets are correlated and thus associated with the same object. Thus, tracklet correlation is a critical step in the cataloging of objects. Evaluating and improving the performance of tracklet correlation methods is the key subject of this thesis. The performance is assessed on three key metrics: the association accuracy, the computational efficiency and the robustness.

In the first part of this thesis, tracklet correlation methods are evaluated. The most promising ones have been identified to be the Adapted Gooding method, the BVP optimization and IVP optimization. The performance of these methods is evaluated for different data distribution characteristics and orbit regimes, first without incorporating perturbations in the tracklet correlation methods.

In the second part, the tracklet correlation methods are modified to improve the performance. A major gap in the state of the art has been successfully addressed, namely to incorporate perturbations in the tracklet correlation methods. Results have shown a significant increase in association accuracy. Specifically, tracklet pairs with arbitrary time gap can be associated with the same true positive rate. Moreover, tracklet pairs from different orbit regimes can be associated with a similar true positive rate if the most important perturbations are incorporated.

Finally, the BVP and IVP optimization are found to be robust to noise, while the Adapted Gooding method severely suffers from the perfect measurement assumption. The performance of the latter has been improved by improving the accuracy of the angles through a Least Squares fit. Although the BVP and IVP optimization are robust to noise, the performance is limited by the accuracy of the angle rates, according to the Chi-squared distribution. A novel tracklet correlation method called the BVP-DC2-DC3 is developed to overcome this limitation, achieving an excellent TPR of 100% and a TNR of 99% for the analyzed objects in GEO for tracklets with a measurement noise of one arcsecond. This accuracy is superior to literature. Moreover, the computational efficiency is superior or comparable to literature. Additionally, the BVP-DC2-DC3 has a high robustness, because for the analyzed GEO tracklets with a measurement noise of five arcseconds, a TPR of 100% and a TNR of 95% can still be achieved.

Cabin interior Elysian Aircraft E9X

Master thesis (2025) - T.W. van Duivenboden, Erik Tempelman, Gerbera Vledder, Daniel Rosen Jacobson, Joaquin Exalto

Electric aircraft Concept Design Interior Design Luggage Spaciousness

This graduation report proposes a new cabin interior for the Elysian E9X. The project is driven by the main questions of Elysian Aircraft: How can we provide a seamless experience for economy-class passengers on a short-haul electric flight? And, how can an electric aircraft inte ...

This graduation report proposes a new cabin interior for the Elysian E9X. The project is driven by the main questions of Elysian Aircraft: How can we provide a seamless experience for economy-class passengers on a short-haul electric flight? And, how can an electric aircraft interior be different from today's airplanes?

The aircraft system involves three key stakeholders: the airline, the aircraft manufacturer and the aircraft interior manufacturer. Elysian, the aircraft manufacturer, is in the initial stage of the certification phase, which gives them significant design freedom to make meaningful innovations. The analysis phase of this research revealed the following main findings: passengers need a sense of visual and physical spaciousness. Additionally, there should be more legroom and improved luggage storage. These main findings were translated into a design goal: Design a lightweight 90-passenger cabin interior seat with enhanced legroom, easy luggage access and a spacious layout that gives passengers a sense of control and the ability to move more freely during the flight (keywords: legroom, spaciousness and luggage).

The final design features a cabin where luggage is stored in containers under the seats. An additional false floor has been installed above the structural floor. This layer creates space for luggage containers between the two floors. How does it work? You board the aircraft and walk to your seat. Once seated, you slide open the luggage container beneath you and place your luggage in the container. If you need to access your belongings during the flight, you can do so easily from your seat.

User testing was conducted to validate the container concept and its impact on user experience in terms of legroom, spaciousness and luggage (keywords design goal). Results from testing with a 1:1 mock-up model showed that luggage was easier to hold during boarding and disembarking, and people were positive about the privacy of their luggage. Testing results using VR technology indicated that the fuselage, without overhead bins, feels more spacious and allows for greater freedom of movement during the flight.

The design brings a lot more advantages. For future passengers, the new design creates a more spacious cabin, allowing them to enjoy an unobstructed view. Increased legroom and easy luggage access provide more convenience and a greater sense of control during the flight. For the airlines, faster boarding reduces turnaround times as passengers store luggage at their seats. More open space improves movement for both passengers and crew. Flexible seat configurations and customisable luggage compartments allow airlines to adapt the layout to their own needs. Therefore, the design eliminates the need for extra construction materials, making it a lightweight and sustainable choice. For the system, this concept integrates into existing aircraft fuselages without significant structural changes. It maintains the supply chain while offering aircraft manufacturers or airlines the option to lower the floor for an even more open and spacious cabin feel.

Thermal Simulation of In-Space Additive Manufacturing

Master thesis (2025) - U.T. Kemmsies, Angelo Cervone, Marcel Hermans, Wei Ya, A. Menicucci, Kunal Masania

Numerical Simulation Finite Element Analysis Microgravity In-Space Additive Manufacturing Metal Directed Energy Deposition Thermal Distribution and Modeling Wire Arc Additive Manufacturing Scandium

This thesis examines the thermal distribution and material behavior in in-space additive manufacturing (ISAM) using metal directed energy deposition (DED), addressing challenges of the orbital environment, including microgravity and vacuum. Experimental studies with a Scandium-mo ...

Data-Driven Optimization of Slow Sand Filters

Machine Learning for New Design Paradigms

Master thesis (2025) - O.H. Kobya, Doris Van Halem, L. C. Rietveld, Jan Peter van der van der Hoek, Thom Bogaard

Machine Learning Slow Sand Filter Exploratory Data Analysis XGBoost Modeling

This thesis presents a comprehensive investigation into the optimization of Slow Sand Filter (SSF) performance through data driven modeling, with a focus on bacterial (E. coli, Coliform) and viral (Enterovirus, Adenovirus, Bacteriophage MS2) removal efficiencies. Combining an ext ...

This thesis presents a comprehensive investigation into the optimization of Slow Sand Filter (SSF) performance through data driven modeling, with a focus on bacterial (E. coli, Coliform) and viral (Enterovirus, Adenovirus, Bacteriophage MS2) removal efficiencies. Combining an extensive literature review, exploratory data analysis (EDA), and machine learning modeling using XGBoost, this research provides new insights into the complex interactions between design parameters and SSF performance, ultimately contributing to the development of more efficient and sustainable SSF configurations. The study began with a systematic literature review of 135 experimental studies, identifying key design parameters and operational conditions of SSFs, including Filtration Rate (FR), Hydraulic Retention Time (HRT), Effective Grain Size (D10), Total Bed Height (T.B.H.), and Schmutzdecke characteristics. The literature review was supplemented with Exploratory Data Analysis (EDA) techniques such as scatterplots and correlation matrices to uncover trends and potential relationships between design parameters and removal efficiencies for bacteria and viruses. While the scatterplots and correlation matrices revealed limited linear relationships, they highlighted the complexity of the interactions, indicating the need for advanced modeling techniques capable of capturing nonlinear patterns. To address these complexities, XGBoost, a powerful machine learning model known for its ability to handle nonlinear relationships and parameter interactions, was developed and applied to the dataset. The model’s predictive capabilities were evaluated using performance metrics such as R², Mean Squared Error (MSE), and cross-validation results. Additionally, feature importance analysis was conducted using the XGBoost model, which provided insights into which design parameters and operational conditions had the most significant influence on removal efficiencies. A key contribution of this research was the development of interactive tools, such as feature contribution sliders and interactive heatmaps, which enabled dynamic exploration of how changes in design parameters affect removal efficiencies. These tools facilitated the simulation of design scenarios, offering an intuitive understanding of parameter impacts and guiding the formulation of new design paradigms. The model outputs were used to propose optimized parameter ranges that improve bacterial and viral removal while maintaining operational efficiency. The thesis further explored the robustness and reliability of the XGBoost models, discussing the results from controllable and uncontrollable design parameters and operational conditions and comparing the model’s predictive performance for bacterial and viral removal. In conclusion, this research highlights the effectiveness of XGBoost modeling for both predicting and explaining SSF performance. The insights gained provide a foundation for developing more efficient SSF design paradigms, enabling targeted adjustments to parameters based on model predictions. Additionally, the interactive tools created in this study offer practical resources for engineers to simulate different design configurations and optimize SSF performance. Overall, this thesis emphasizes the potential of machine learning to revolutionize the design and operation of SSFs, providing a foundation for future advancements in sustainable and effective water treatment technologies.

Embracing Uncertainty: Developing a Life Cycle Assessment Tool to Support Decision-Making Throughout the Design Process

Master thesis (2025) - R.A. Swinkels, B. Sprecher, Ruud Balkenende

With increasing policies and societal pressure, the environmental impact of product design has become a widespread concern. Life Cycle Assessment (LCA) is a key method used to quantify the environmental impacts associated with the manufacture, transport, use and disposal of a pro ...

With increasing policies and societal pressure, the environmental impact of product design has become a widespread concern. Life Cycle Assessment (LCA) is a key method used to quantify the environmental impacts associated with the manufacture, transport, use and disposal of a product. While LCA provides valuable insights, it is primarily used as a retrospective evaluation tool rather than to inform design decisions. This is largely due to the complexity, data-intensive nature and misalignment of existing LCA software with the design workflow. As a result, designers struggle to incorporate LCA insights into their decision-making process.

To bridge this gap and lower the threshold for LCA adoption, Polaris Sustainability, a start-up company aiming to specialise in LCA software, initiated this thesis project to explore the development of a designer-friendly LCA tool. The aim is to make LCA more accessible by integrating it seamlessly into the design process, allowing designers to apply LCA in an ex-ante manner, assessing environmental impacts before their products are finalised. This approach helps designers integrate sustainability considerations early in development when changes are still flexible. By addressing environmental impacts before decisions become too costly or difficult to reverse, it enables more sustainable design choices.

The research identified two key challenges: the complexity of LCA software and the lack of alignment with design workflows. Designers often struggle with critical LCA steps, such as defining Functional Units (FUs), handling incomplete datasets, and interpreting results. At the same time, different design stages require different levels of environmental insights. Recognizing LCA’s value at each stage (e.g., ideation or embodiment) can improve its integration into decision-making. Designers also need structured support in performing LCA, including guidance on working with incomplete data, using proxies, and simplifying LCA terminology to make it more intuitive and actionable.

To address these issues, a digital prototype was developed through UX design methods and usability testing, featuring a wizard-based approach that guides designers step by step through the LCA process. Key features include accessible databases for material and process data, uncertainty management for handling incomplete datasets, and clear data visualizations to help designers understand and compare environmental impacts.

A feasibility discussion with software developers confirmed that the tool’s core functionalities, such as guided workflows and real-time impact assessments, are technically feasible. However, some features will require excessive computing power, making them prone to error. Future development should focus on creating a functional prototype, gathering additional user feedback, and enhancing automation to reduce cognitive load. Developing databases tailored to designers' material and process knowledge will be essential to improving usability.

By refining the user experience, addressing data challenges, and modelling the back-end, Polaris will be able to develop a practical LCA tool that supports environmetnal design decisions. Collaboration with academia and industry, along with pilot studies, will further strengthen the tool, ensuring it is both methodologically sound and aligned with practical design needs before its full launch.

Measurement of low sediment concentrations in a pipe flow– A deep sea mining application

Master thesis (2025) - S.C.T. Laken, R.L.J. Helmons, A.M. Talmon, F.A. Doorn, Frans van Grunsven

Deep Sea Mining Polymetallic Nodules Sediment concentration measurement Coriolis Sensor

This thesis explores the measurement of low sediment concentrations in pipeline flows, a critical issue in deep-sea mining. The study aims to identify and validate a continuous measurement method capable of accurately detecting suspended sediment concentrations between 10-75 g/L. ...

This thesis explores the measurement of low sediment concentrations in pipeline flows, a critical issue in deep-sea mining. The study aims to identify and validate a continuous measurement method capable of accurately detecting suspended sediment concentrations between 10-75 g/L. These measurements are essential for minimizing the environmental impact of sediment plumes generated by mining operations.

The research begins with an analysis of material properties and flow dynamics, emphasizing the role of sediment particle size, and density in influencing suspension and settling behaviours. Highlighting the differences between concentration measurement and density measurement and the additional error involved. A review of flow regimes, turbulence, and their effects on sediment distribution within pipelines sets the foundation for understanding the complexities of representative sampling.

The thesis evaluates a range of measurement methodologies against criteria such as accuracy, range, spatial and temporal resolution, safety, cost, and impact on the flow. Optical, acoustic, conductivity, and radioactive source sensors were unsuitable due to limited range, low accuracy, or safety concerns. Promising alternatives include the U-loop, Coriolis, and vibrating fork sensors. The U-loop offers good accuracy and range, but causes significant pressure drops. Coriolis sensors provide excellent accuracy and broad range, but require careful sampling to ensure reliability. The vibrating fork sensor is simple and has a good range, but suffers from low accuracy and limited spatial resolution.

A key aspect of this research is the experimental setup, which integrates multiple sensor technologies in a controlled flow loop environment. Detailed methodologies for sensor calibration, installation, and data collection ensured the testing conditions. Tests are conducted under varying sediment concentrations, sediment types, grain sizes, and flow velocities to validate the accuracy and reliability of each measurement method.

The results reveal significant differences in sensor performance across test conditions. Test variables such as sediment type, concentration, and flow velocity are shown to influence sensor performance.

In conclusion, suspended sediment concentrations from 10 - 75g/L can be measured accurately using a Coriolis sensor. This sensor directly measures density which can be converted into concentration with minimal calibration or correction, demonstrating superior accuracy and precision across diverse flow conditions. Although it reliably detects finer deep-sea sediment, minor challenges remain when measuring coarser materials, such as nodule fines. Overall, the findings contribute to the development of environmentally responsible deep-sea mining practices, by facilitating real-time and accurate sediment monitoring.

Semi-Reactive Collision Avoidance in Unknown Environments

Master thesis (2025) - S. Van den Bergh, M. Popovic, Guido Cornelis Henricus Eugene de Croon, J Guo

UAV Collision avoidance Unknown Environment

Unmanned Aerial Vehicles (UAVs) play a crucial role in various applications, including disaster response, infrastructure inspection, and search-and-rescue missions. To maximise their effectiveness, UAVs must achieve a high level of autonomy, particularly when navigating cluttered ...

LeanSolver: Solving theorems through Large Language Models and Search

Improving Theorem Proving with Proof Assistants and Sequential Monte Carlo in Large Language Models

Master thesis (2025) - A.L. Halevy, Sebastijan Dumancic, G.F. Nane, Benedikt Ahrens

AI Theorem proving Sequential Monte Carlo LLMs Lean 4

We consider a subset of simple proving exercises that are part of the Lean 4 tutorials. The exercises consist of a statement, and the task will consist of creating a proof term of the desired type through the use of tactics.
Large Language Models on their own are known to be ...

Does working from home lead to longer commutes?

Exploring the impact of working from home conditions on commuting time valuation

Master thesis (2025) - J.T. van Eeken, Eric Molin, I.R. van de Poel, Marije Hamersma, Roel Faber

How to design spare parts for stereolithography to replace injection moulded parts

Development of a form factor optimisation guide

Master thesis (2025) - W.H. Bakkeren, A. R. Balkenende, Zjenja Doubrovski

Product design Repair Additive manufacturing Stereolithography Spare part Injection moulding Form factor Product architecture

The goal of this thesis was to provide designers guidance in designing their yet-to-be designed products that contain injection moulded parts in a way that allows for interchangeable, functionally equivalent spare parts produced with additive manufacturing in the future. The proj ...

The Effect of the STIL Orthosis on Action Tremor Severity in Parkinson’s Disease: A Pilot Study

Master thesis (2025) - M.C.L. Jongbloed, W. Mugge, S. Pirola, IJsbrand de Lange

Parkinson's Disease (PD) Orthotic device Medical Device Action Tremor Noninvasive Treatment

Objective Action tremors affect many Parkinson’s disease (PD) patients and can significantly impair daily functioning. These tremors often persist despite dopaminergic therapy, while stereotactic surgery, though effective, is invasive and not suitable for all. Alternative treatme ...

Investigating Cycling Stability in Acid-Base Flow Batteries

Mechanistic Understanding Through Crossover Analysis

Master thesis (2025) - L. Li, D.A. Vermaas, P.A. Loktionov, Peyman Taheri

Bipolar membranes Ion exchange membranes Cycling stability Acid-base flow batteries Co-ion crossover Ion transport phenomena

As the demand for sustainable energy grows, large-scale energy storage solutions are becoming in- creasingly essential to balance power supply and demand, ensuring grid stability and security. Acid- base flow batteries (ABFBs) have emerged as a promising energy storage solution d ...

Modelling changing travel behaviour in response to road capacity reductions

The impact of reallocating road space in urban areas on car use

Master thesis (2025) - S.A. van Heyningen, Maaike Snelder, Victor Knoop, R.T.J. van der Kleij

Car use reduction Disappearing traffic Road capacity reductions Road space reallocation Modelling changing travel behaviour Low-car city

As cities increasingly prioritize sustainable and low-car urban environments, road capacity reductions have become a widely applied policy measure. While traditional transport models predict severe congestion resulting from such interventions, empirical studies suggest that traff ...

Utilizing cross-modal correspondences to select fragrances

D'Accord

Master thesis (2025) - A. Strijker, Maarten W A Wijntjes, C.R.G. Smit

Multi-sensory design Experience Design Cross-modal perception Scent

The retail perfume industry often lacks the multi-sensory engagement needed to frame the perception of a fragrance and thus facilitate the fragrance selection process. Scent is very ambiguous and needs cues from other senses to better place a scent (Pierzchajlo et al., 2024). Thi ...