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Researcher
David Moens
- Keywords:Mechanical engineering
- Disciplines:Control systems, robotics and automation, Design theories and methods, Manufacturing engineering, Mechatronics and robotics, Other mechanical and manufacturing engineering, Computer theory, Product development
Affiliations
- Mechanical Engineering Technology TC, De Nayer (Sint-Katelijne-Waver) Campus (Technology cluster)
Responsible
From1 Mar 2014 → Today - Mechanical Engineering Technology TC, De Nayer (Sint-Katelijne-Waver) Campus (Technology cluster)
Member
From1 Oct 2013 → Today - Production Engineering, Machine Design and Automation (PMA) Section (Division)
Member
From1 Oct 2010 → 30 Sep 2011
Projects
1 - 10 of 16 results
- RoMuPAM: Robotized Multi-axis Plastic Additive ManufacturingFrom1 Dec 2018 → TodayFunding: IWT / VLAIO - TETRA fund, Own budget, for example: patrimony, inscription fees, gifts
- GOODWIN: Grey-box approaches for digital twins of complex mechanical structures and systems under uncertainty.From15 Oct 2018 → TodayFunding: BOF - Bilateral scientific cooperation
- Generalised inverse uncertainty quantification in numerical modelsFrom1 Oct 2018 → TodayFunding: FWO fellowships
- High Dimensional Interval Fields: spatial uncertainty modeling for mechanical reliability (HiDIF)From1 Jan 2018 → TodayFunding: FWO research project
- Development and validation of high-definition numerical methods for mechanical design under manufacturing process variationFrom7 Nov 2017 → 6 May 2019Funding: BOF - Doctoral projects (previously NOI/LP)
- Spatial uncertainty quantification in high-fidelity finite element modelsFrom1 Oct 2017 → 30 Sep 2019Funding: IOF - Industrial Research Fund
- Additive Manufacturing of Plastic MouldsFrom1 Feb 2017 → 31 Jan 2019Funding: IWT / VLAIO - TETRA fund
- Experimental testing and heat transfer analysis of a novel iris-driven solar cavity receiverFrom1 Oct 2015 → 1 Oct 2019Funding: BOF - Doctoral projects (previously NOI/LP)
- Additive manufacturing of polymers.From1 Apr 2014 → 30 Jun 2016Funding: IWT / VLAIO - TETRA fund
- Characterisation and modelling of the variability of mechanical properties of natural fibre composites.From1 Jan 2014 → 31 Dec 2017Funding: FWO research project
Publications
1 - 10 of 130 results
- Robust uncertainty quantification in structural dynamics under scarse experimental modal data: A Bayesian-interval approach(2020)Journal: Journal of Sound and VibrationISSN: 0022-460XVolume: 467
Authors: Maurice Imholz, Matthias Faes, Dirk Vandepitte, David Moens
Number of pages: 17 - Imprecise random field analysis with parametrized kernel functions(2019)Journal: Mechanical Systems and Signal ProcessingISSN: 0888-3270Volume: 134
Authors: Matthias Faes, David Moens
Number of pages: 17 - Hybrid spatial uncertainty analysis for the estimation of imprecise failure probabilities in Laser Sintered PA-12 parts(2019)Journal: Computers & Mathematics with ApplicationsISSN: 0898-1221Issue: 7Volume: 78
Authors: Matthias Faes, Sabyasachi Ghosh Dastidar, David Moens
Pages: 2395 - 2406 - Cross-dependence between interval fields in Finite Element models: definition and analysis(2019)Book: Proceedings of ESREL 2019
Authors: Matthias Faes, David Moens
Pages: 2648 - 2655 - Monte Carlo Ray Tracing Coupled CFD Modeling and Experimental Testing of a 1 kW Solar Cavity Receiver Radiated via 7 kW HFSS(2019)Book: Proceedings of the ASME 2019 Summer Heat Transfer Conference
Authors: Cédric Ophoff, Nesrin Ozalp, David Moens
Pages: 1 - 11 - Experimental performance comparison and optical characteristics of aperture mechanisms for solar cavity receivers(2019)Journal: Solar EnergyISSN: 0038-092XVolume: 188
Authors: Cédric Ophoff, Nesrin Ozalp, David Moens
Pages: 66 - 82 - An experimental study on temperature control of a solar receiver under transient solar load(2019)Journal: Solar EnergyISSN: 0038-092XVolume: 186
Authors: Hamed Abedini Najafabadi, Nesrin Ozalp, Cédric Ophoff, David Moens
Pages: 52 - 59 - A machine learning approach for the inverse quantification of set-theoretical uncertainty(2019)Book: https://2019.uncecomp.org/proceedings/pdf/18848.pdf
Authors: Lars Bogaerts, Matthias Faes, David Moens
Pages: 1 - 13Number of pages: 13 - Robust efficient global optimisation via adaptive surrogate refinement(2019)Journal: Proceedings in Applied Mathematics and MechanicsISSN: 1617-7061Volume: 19
Authors: Noémie Le Carrer, David Moens, Matthias Faes
- Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?(2019)Book: Proceedings of the 13th International Conference on Applications of Statistics and Probability in Civil Engineering
Authors: Matthias Faes, Matteo Broggi, Edoardo Patelli, Yves Govers, John Mottershead, Michael Beer, David Moens