document

Uncertainty quantification of the wall thickness and stiffness in an idealized dissected aorta

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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A Bayesian defect-based physics-guided neural network model for probabilistic fatigue endurance limit evaluation

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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Uncertainty quantification for tensor network constrained kernel machines: A frequentist and Bayesian approach

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

document

Uncertainty quantification for solar sails in the near-Earth environment

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

document

Robust topology optimization considering part distortion and process variability in additive manufacturing

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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Sensitivity analysis for buckling characterisation using the vibration correlation technique

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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A View on Model Misspecification in Uncertainty Quantification

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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Uncertainty Quantification of the Neutronics Model of the U-Battery with Reduced Models

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

document

Uncertainty in aviation emissions inventories: Sources and improvements

Aldridge, Harry (author)

The approach to sustainable aviation requires effective policy and regulation, informed by accurate environmental research. Aviation emissions inventories form the basis of any environmental assessment, however they are based on simplifications and assumptions that introduce a degree of uncertainty. In terms of robust model development, it is...

master thesis 2022

document

Generation of design allowables on the open hole tensile strength of composite laminates using sensitivity analysis and uncertainty quantification framework

Sasikumar, Aravind (author), Ninyerola, Joan (author), Ruiz, Ivan (author), Bessa, M.A. (author), Turon Travesa, Albert (author)

Aeronautical industries are concerned about the cost effective generation of design allowables for composite laminates. Design allowables take into account the variabilities arising from different sources (material, manufacturing, defects etc.,) which are determined using expensive and time consuming experimental campaigns....

conference paper 2022

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Uncertainty quantification of the lifetime of self-healing thermal barrier coatings based on surrogate modelling of thermal cyclic fracture and healing

Kumthekar, A. (author), Ponnusami, Sathiskumar A. (author), van der Zwaag, S. (author), Turteltaub, S.R. (author)

Computationally-efficient surrogate models based on a Polynomial Chaos Expansion (PCE) are developed to quantify the uncertainties in the fracture behavior and lifetime of a self-healing thermal barrier coating system (SH-TBC) and a benchmark conventional TBC system. The surrogate models are built using deterministic information from...

journal article 2022

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Poro-Mechanical Coupling for Flow Diagnostics

Sosa, L. Gutierrez (author), Geiger, S. (author), Doster, Florian (author)

Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows using complex reservoir models is challenging, mainly because of the high computational cost. We hence introduce an alternative approach that couples hydrodynamics through existing flow diagnostics simulations with poro...

journal article 2022

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Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties

Joshi, A. (author), Thakolkaran, P. (author), Zheng, Y. (author), Escande, Maxime (author), Flaschel, Moritz (author), De Lorenzis, Laura (author), Kumar, Siddhant (author)

Within the scope of our recent approach for Efficient Unsupervised Constitutive Law Identification and Discovery (EUCLID), we propose an unsupervised Bayesian learning framework for discovery of parsimonious and interpretable constitutive laws with quantifiable uncertainties. As in deterministic EUCLID, we do not resort to stress data, but...

journal article 2022

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Verification, validation, and parameter study of a computational model for corrosion pit growth adopting the level-set method. Part II: Stress corrosion

Fayezioghani, A. (author), Dekker, R. (author), Sluys, Lambertus J. (author)

Structural components in corrosive environments such as pipelines, bridges, aircrafts, and turbines are imposed to stress corrosion. A stress corrosion model for pit growth should a) accurately consider the electrochemistry of the corrosion process, b) properly deal with the moving interface between solid and electrolyte, and c) effectively...

journal article 2022

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Verification, validation, and parameter study of a computational model for corrosion pit growth adopting the level-set method.: Part I: Corrosion

Fayezioghani, A. (author), Dekker, R. (author), Sluys, Lambertus J. (author)

Corrosion is a phenomenon observed in structural components in corrosive environments such as pipelines, bridges, aircrafts, turbines, etc. The computational model of corrosion should enjoy two features: a) accurately considering the electrochemistry of corrosion and b) properly dealing with the moving interface between solid and electrolyte....

journal article 2022

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Decision Making under Uncertainty for Construction Management of Offshore Wind Assets

Leontaris, G. (author)

Offshore wind is expected to be one of the important contributors to the energy transition towards a more renewable and sustainable energy future. This can be clearly seen from the amount of investments over the past years as well as from the substantial upcoming offshore wind projects in the years to come. Many technological implementation...

doctoral thesis 2021

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Robust needle channel planning for patient-tailored applicator design in cervical cancer brachytherapy

Straathof, Robin (author)

Brachytherapy (BT) is an essential component in the treatment of cervical cancer as it allows for locally delivering a high dose to the tumour with minimal trauma to surrounding tissues and organs at risk (OARs). However, in advanced cervical cancer patients commercially available BT applicators are particularly ill-adapted and therefore result...

master thesis 2021

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On the investigation of utility functions on optimal sensor locations

Igea, Felipe (author), Chatzis, Manolis N. (author), Cicirello, A. (author)

Structural Health Monitoring uses data collected from sensors placed on structures to determine their operating condition and whether maintenance is required. Often, optimal sensor placement strategies are used to find the optimal locations for the identification of their modal properties, structural parameters and/or abnormal behaviours under...

conference paper 2021

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Quantifying Accuracy and Uncertainty in Data-Driven Flight Trajectory Predictions with Gaussian Process Regression

Graas, R. (author), Sun, Junzi (author), Hoekstra, J.M. (author)

Several initiatives are developed to shift the current paradigm in Air Traffic Management from the tactical-based approach to more strategic-based coordination of flights. This transformation of the ATM system relies on the improvement of predictive models for the 4D flight trajectories. A variety of performance-based and data-driven approaches...

conference paper 2021

document

Climate change induced trends and uncertainties in phytoplankton spring bloom dynamics

Mészáros, L. (author), van der Meulen, F.H. (author), Jongbloed, G. (author), El Serafy, G.Y.H. (author)

Spring phytoplankton blooms in the southern North Sea substantially contribute to annual primary production and largely influence food web dynamics. Studying long-term changes in spring bloom dynamics is therefore crucial for understanding future climate responses and predicting implications on the marine ecosystem. This paper aims to study...

journal article 2021