Searched for: subject%3A%22Uncertainty%255C+quantification%22
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Li, G. (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Traffic condition forecasting is fundamental for Intelligent Transportation Systems. Besides accuracy, many services require an estimate of uncertainty for each prediction. Uncertainty quantification must consider the inherent randomness in traffic dynamics, the so-called aleatoric uncertainty, and the additional distrust caused by data shortage...
journal article 2024
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Gheysen, Lise (author), Maes, Lauranne (author), Caenen, Annette (author), Segers, Patrick (author), Peirlinck, M. (author), Famaey, Nele (author)
Personalized treatment informed by computational models has the potential to markedly improve the outcome for patients with a type B aortic dissection. However, existing computational models of dissected walls significantly simplify the characteristic false lumen, tears and/or material behavior. Moreover, the patient-specific wall thickness...
journal article 2024
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Li, G. (author), Li, Zirui (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Predicting the trajectories of road agents is fundamental for self-driving cars. Trajectory prediction contains many sources of uncertainty in data and modelling. A thorough understanding of this uncertainty is crucial in a safety-critical task like auto-piloting a vehicle. In practice, it is necessary to distinguish between the uncertainty...
journal article 2024
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Tognan, A. (author), Patanè, Andrea (author), Laurenti, L. (author), Salvati, Enrico (author)
Accurate fatigue assessment of material plagued by defects is of utmost importance to guarantee safety and service continuity in engineering components. This study shows how state-of-the-art semi-empirical models can be endowed with additional defect descriptors to probabilistically predict the occurrence of fatigue failures by exploiting...
journal article 2024
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Rocchetta, Roberto (author), Zhan, Zhouzhao (author), van Driel, W.D. (author), Di Bucchianico, Alessandro (author)
Lifetime analyses are crucial for ensuring the durability of new Light-emitting Diodes (LEDs) and uncertainty quantification (UQ) is necessary to quantify a lack of usable failure and degradation data. This work presents a new framework for predicting the lifetime of LEDs in terms of lumen maintenance, effectively quantifying the natural...
journal article 2024
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Li, G. (author), Li, Zirui (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Resolving predicted conflicts is vital for safe and efficient autonomous vehicles (AV). In practice, vehicular motion prediction faces inherent uncertainty due to heterogeneous driving behaviours and environments. This spatial uncertainty increases non-linearly with prediction time horizons, leading AVs to perceive more road space occupied by...
journal article 2024
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Diab Montero, H.A. (author), Størksen Stordal, Andreas (author), van Leeuwen, Peter Jan (author), Vossepoel, F.C. (author)
Probabilistic forecasts are regarded as the highest achievable goal when predicting earthquakes, but limited information on stress, strength, and governing parameters of the seismogenic sources affects their accuracy. Ensemble data-assimilation methods, such as the Ensemble Kalman Filter (EnKF), estimate these variables by combining physics...
working paper 2024
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van Tunen, Rick (author)
Congenital heart disease (CHD) affects almost 1% of newborns. Right ventricular outflow tract (RVOT) CHD affects 20% of newborns and includes anomalies such as tetralogy of Fallot (TOF) with or without pulmonary atresia, transposition of the great vessels, and truncus arteriosus. All these anomalies require RVOT reconstruction. Prosthetic heart...
master thesis 2023
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Smeenk, Rutger (author)
This research aims at quantifying the uncertainty in the predictions of tensor network constrained kernel machines, focusing on the Canonical Polyadic Decomposition (CPD) constrained kernel machine. Constraining the parameters in the kernel machine optimization problem to be a CPD results in a linear computational complexity in the number of...
master thesis 2023
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Sennema, Erik (author)
Intrusion detection systems (IDSs) are essential for protecting computer systems and networks from malicious attacks. However, IDSs face challenges in dealing with dynamic and imbalanced data, as well as limited label availability. In this thesis, we propose a novel elastic gradient boosting decision tree algorithm, namely Elastic CatBoost...
master thesis 2023
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Garcia Bonilla, Juan (author)
Solar sailing is a promising propellantless propulsion method that employs large reflective surfaces to harness solar radiation pressure for spacecraft propulsion. Despite the fact that several solar-sail near-Earth missions will launch in the coming years, there is notable lack of published studies on the uncertainties associated with missions...
master thesis 2023
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Mészáros, L. (author)
This thesis presents a doctoral research where statistical concepts and techniques are applied to problems at the interface of marine and atmospheric processes. The research was conducted at the Statistics group of the Delft Institute of Applied Mathematics (TU Delft) and the Marine and Coastal unit of Deltares. The main objective of the work is...
doctoral thesis 2023
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Baciu, Theodor D. (author), Degenhardt, Richard (author), Franzoni, Felipe (author), Gliszczynski, Adrian (author), Arbelo, Mariano A. (author), Castro, Saullo G.P. (author), Kalnins, Kaspars (author)
The Vibration Correlation Technique (VCT) is a non-destructive method to predict buckling loads for imperfection-sensitive structures. While successfully used to validate numerical models and predict experimental buckling loads, recommendations for defining the VCT experiment are scarce. Here, its sensitivity towards the number of load steps...
journal article 2023
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Kato, Y. (author), Tax, D.M.J. (author), Loog, M. (author)
Estimating uncertainty of machine learning models is essential to assess the quality of the predictions that these models provide. However, there are several factors that influence the quality of uncertainty estimates, one of which is the amount of model misspecification. Model misspecification always exists as models are mere simplifications...
conference paper 2023
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Komini, Ludian (author), Langelaar, Matthijs (author), Kriegesmann, Benedikt (author)
This paper presents a method to consider uncertainties in the distortion prediction of additive manufacturing processes within robust topology optimization. The random variable of the stochastic additive manufacturing process is the inherent thermomechanical strain, typically determined by process characterization experiments. The value of...
journal article 2023
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Wang, Y. (author), Voskov, D.V. (author), Daniilidis, Alexandros (author), Khait, M. (author), Saeid, S. (author), Bruhn, D.F. (author)
The efficient operation and management of a geothermal project can be largely affected by geological, physical, operational and economic uncertainties. Systematic uncertainty quantification (UQ) involving these parameters helps to determine the probability of the focused outputs, e.g., energy production, Net Present Value (NPV), etc. However,...
journal article 2023
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de Hoop, S. (author)
Society relies on large amounts of energy to progress and allow for a high standard of living. The recent severe climate changes require advanced technologies related to cleaner energy resources. One such technology beneficial for accelerating this current energy transition is geothermal energy. This type of energy is often found in fractured...
doctoral thesis 2022
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van den Broek, Erik (author)
High-fidelity models are computationally intensive to work with in many-query applications, such as the design process of small modular reactors. A reduced order model of the high-fidelity model can still accurately determine the quantities of interest with only a fraction of the computational cost, and thus can potentially solve the...
master thesis 2022
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Lyons, Jeff (author)
In light of worsening climate change and an increased interest in adapting infrastructure to cope with its effects, model-based decision support has become an essential tool for policy makers. In conditions of deep uncertainty, models may be used to explore a large space of possible system behaviours and so encourage a wider consideration of the...
master thesis 2022
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Hageman, R.B. (author)
Floating offshore structures are continuously subjected to wave loads and loading originating from operational activities. These loads lead to cracks growing in the structure, a process known as fatigue accumulation. The analysis of fatigue accumulation is subject to large uncertainties. This is related to the high sensitivity of fatigue...
doctoral thesis 2022
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