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Koronaios, Panagiotis (author)This study investigates the development and application of meta-models for crashworthiness assessment of helicopter structures and components. It aims to address the challenges associated with scarcity of data from computationally expensive simulations and experimental drop-tests, and enable the use of surrogates in a crashworthiness...master thesis 2024
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Buriani, Gioele (author)This work introduces a novel methodology for the development of interpretable reduced-order dynamic models specifically tailored for jumping quadruped robots. Leveraging Symbolic Regression combined with autoencoder neural networks, the framework autonomously derives symbolic equations from data and fundamental physics principles capturing the...master thesis 2024
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Yap, Li-Toong (author)Site analysis to determine the loads experienced by wind turbines based on site-specific environmental conditions is typically done using either coupled aero-servo-elastic simulations for onshore wind turbines or coupled aero-servo-hydroelastic simulations in the case of offshore wind turbines. These simulations become computationally expensive...master thesis 2023
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O'Hanrahan, Mike (author)Predicting streamflow in a changing climate poses significant challenges for traditional hydrological models. Static parameter sets result from model calibrations over historical data that increasingly encounter the non-stationary impacts on the hydrological system. Endeavouring toward non-stationary model parameters by incorporating time...master thesis 2023
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Wang, Yunhan (author)Temporal Action Localization (TAL) aims to localize the start and end times of actions in untrimmed videos and classify the corresponding action types. TAL plays an important role in understanding video. Existing TAL approaches heavily rely on deep learning and require large-scale data and expensive training processes. Recent advances in...bachelor thesis 2023
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Vilhjálmsson, Thor (author)This thesis aims to investigate the feasibility of developing a successful unsupervised Structural Health Monitoring (SHM) methodology to detect damage in structures, specifically bridges. Detecting damage, especially in its earliest stages, is challenging, thus prompting the need for robust and effective methods. The success of such a...master thesis 2023
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Hopman, Luuk (author)Asphalt concrete is one of the most widely used materials in modern road construction. Predicting its functional properties is crucial in the design of new asphalt concrete mixtures. However, current prediction models are limited in accuracy and applicability due to the complex nature of asphalt concrete properties. This thesis researches the...master thesis 2023
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Middelweerd, Marloes (author)In the Netherlands, online groceries are becoming increasingly popular, as are the challenges grocery companies face in meeting customers' rising demand for smaller and cheaper time slots while maintaining thin profit margins due to a highly competitive market. Customer choice modelling will be used to identify customers' behaviour and control...master thesis 2023
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Kaniewski, Tadeusz (author)The computational cost of high-fidelity engineering simulations, for example CFD, is prohibitive if the application requires frequent design iterations or even fully fledged optimization. A popular way to reduce the computational cost and enable fast iteration cycles is to use surrogate models that are trained to predict simulation results from...master thesis 2023
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Schouten, Janno (author)Patients who are admitted to the Intensive Care Unit (ICU) are extremely ill and at high risk of organ failure and death. Being admitted to the ICU is known to cause long lasting physical, cognitive, and physiological symptoms, which is called Post-Intensive Care syndrome (PICS). To provide better management of PICS, early recognition and...master thesis 2023
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Aleebrahimdehkordi, M. (author), Lechner, J.M. (author), Ghorbani, Amineh (author), Nikolic, I. (author), Chappin, E.J.L. (author), Herder, P.M. (author)Agent-based modelling and simulation (ABMS), whether simple toy models or complex data-driven ones, is regularly applied in various domains to study the system-level patterns arising from individual behaviour and interactions. However, ABMS still faces diverse challenges such as modelling more representative agents or improving computational...journal article 2023
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Restrepo Botero, Miguel (author)Understanding the fatigue load history of wind turbines is critical for taking decisions regarding the lifetime of a project. However, direct measurement of fatigue loads at each turbine in a wind farm is unfeasible. For this reason, surrogate models offer a useful alternative. In this thesis, a methodology for creating surrogate models for...master thesis 2022
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Andrade Castanheira, Francisco (author)The optimization of interplanetary, low-thrust trajectories is a computationally expensive aspect of preliminary mission design. To reduce the computational burden associated with it, surrogate models can be used as cheap approximations of the original fitness function. Training the surrogate models in a fully online manner can be done to...master thesis 2022
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Khan, Arghem (author)Artificial Intelligence (AI) and Machine learning (ML) applications are being widely used to solve different problems in different sectors. These applications have enabled the human-effort and involvement to be very low. The AI/ML systems<br/>make their own predictions and do not require a great deal of human help. However, over the last few...bachelor thesis 2022
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de Mooy, Dion (author)In this thesis, a new photovoltaic fault detection and classification method is proposed. It combines the generation of a synthetic photovoltaic training database and the use of a machine learning model to detect and classify faults in small-scale residential PV systems. The database was generated in Matlab, and the machine learning modeling was...master thesis 2022
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Meister, S. (author)In modern aircraft, structural lightweight composite components are increasingly<br/>used. To manufacture these components in a costeffective way, robust production systems for the manufacturing of complex fibre composite components are necessary. A rather novel but already established process for fibre material deposition is the Automated Fibre...doctoral thesis 2022
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Forouzandeh Shahraki, N. (author), Zomorodian, Zahra Sadat (author), Tahsildoost, Mohammad (author), Shaghaghian, Zohreh (author)Recent studies have focused on data-driven methods for building energy efficiency, by using simulated or empirical data, for energy-based design assessment rather than the common physics-based techniques, which are mostly time-consuming. In this paper, the feasibility of using seven different Machine Learning models, including three single...journal article 2022
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Valchev, I. (author), Coraddu, A. (author), Oneto, L. (author), Kalikatzarakis, M. (author), Tiddens, W. (author), Geertsma, R.D. (author)Deterministic models based on the laws of physics, as well as data-driven models, are often used to assess the current state of vessels and their systems, as well as predict their future behaviour. Predictive maintenance methodologies (i.e., Condition Based Maintenance), and advanced control strategies (i.e., Model Predictive Control), are built...journal article 2022
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Kordes, Arthur (author)Atrial Fibrillation affects millions of people worldwide. It is associated with an impaired quality of life and an increased risk of stroke, cardiac failure and mortality. Treatments exist, but early detection and treatment is crucial, due to the progressive nature of the disease. Algorithms can help with early detection. Machine learning...master thesis 2021
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Emanuel Febrianto Prakoso, Emanuel (author)This study addresses the truck rescheduling problem as the consequence of uncertain arrival time. It proposes an integrated system of predictive model powered by machine learning algorithm and exact optimization model such that it is distinct from most existing literatures in this domain. The uncertainty of truck arrival time is captured as...master thesis 2021