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Researcher
Matthias Faes
- Disciplines:Other engineering and technology
Affiliations
- Mecha(tro)nic System Dynamics (LMSD) (Division)
Member
From1 Aug 2020 → Today - Manufacturing Processes and Systems (MaPS) (Division)
Member
From1 Aug 2020 → 31 Jul 2020 - Mechanical Engineering Technology, De Nayer (Sint-Katelijne-Waver) Campus (Technology cluster)
Member
From1 Oct 2013 → 31 Jul 2020
Projects
1 - 8 of 8
- Digital Image Correlation enriched quantification of polymorphic random field uncertainty in finite-element modelsFrom28 Oct 2021 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- A grey-box approach for robust resistance pressure welding monitoringFrom1 Oct 2021 → TodayFunding: IOF - technology concept exploration
- Thermal modelling and online heat transfer estimation using active learning grey-box approachesFrom21 Sep 2021 → TodayFunding: Own budget, for example: patrimony, inscription fees, gifts
- Reliability-based topology optimization of continuous fibre compositesFrom15 Jan 2020 → TodayFunding: BOF - doctoral mandates, FWO Strategic Basic Research Grant
- From full-field data to spatial uncertaintyFrom1 Sep 2019 → TodayFunding: BOF - doctoral mandates, FWO Strategic Basic Research Grant
- GOODWIN: Grey-box approaches for digital twins of complex mechanical structures and systems under uncertainty.From15 Oct 2018 → 14 Oct 2020Funding: BOF - various
- Generalised inverse uncertainty quantification in numerical modelsFrom1 Oct 2018 → 1 Feb 2022Funding: FWO fellowships
- Interval methods for the identification and quantification of inhomogeneous uncertainty in Finite Element modelsFrom1 Dec 2013 → 27 Nov 2017Funding: Own budget, for example: patrimony, inscription fees, gifts
Publications
11 - 20 of 121
- No-Free-Lunch Theorems for Reliability Analysis(2023)
Authors: Matthias Faes
- Near-real-time online process control using grey-box models(2023)
Authors: Miriam Dodt, Augustin Persoons, Matthias Faes, David Moens
Number of pages: 8 - Special Section on Community Resilience to Disruptive Events: Models and Analyses, Lessons Learned, and Case Studies(2023)
Authors: Matthias Faes
- A machine learning approach for efficient and robust resistance spot welding monitoring(2023)
Authors: Lars Bogaerts, Arnout Dejans, Matthias Faes, David Moens
Pages: 1923 - 1935 - Combining data and physical models for probabilistic analysis: A Bayesian Augmented Space Learning perspective(2023)
Authors: Matthias Faes
- A self-learning Digital Twin for Process Control of fast processes under Uncertainty(2023)
Authors: Miriam Dodt, Augustin Persoons, Matthias Faes, David Moens
Pages: 486 - 499Number of pages: 14 - Robust design optimization of expensive stochastic simulators under lack-of-knowledge(2023)
Authors: Koen van Mierlo, Augustin Persoons, Matthias Faes, David Moens
- Multi-physical modelling of resistance spot welding including validation(2023)
Authors: Bouwe Verkens, Matthias Faes, David Moens
Number of pages: 14 - Design for crashworthiness under epistemic uncertainty(2023)
Authors: Koen van Mierlo, David Moens, Matthias Faes
- Estimation of an imprecise power spectral density function with optimised bounds from scarce data for epistemic uncertainty quantification(2023)
Authors: Matthias Faes
Linked dataset
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