prof. dr. ir. Mathias Kersemans
- ORCID iD
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0000-0002-9325-0556
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Broadband nonlinear RAPID : a baseline-free probabilistic imaging approach for single-defect localization using a sparse sensor network
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- Journal Article
- A1
- open access
Broadband nonlinear delay and sum (NL-DAS) for baseline-free damage imaging using a sparse sensor network
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- Journal Article
- A1
- open access
Low-velocity impact resistance and compression after impact strength of thermoplastic nanofiber toughened carbon/epoxy composites with different layups
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A flexible deep learning framework for thermographic inspection of composites
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A novel physics-informed neural networks approach for efficient multimodal mapping and inversion of vibrations
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Phase inversion thermography for sensitive and depth-resolved inspection
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Thermographic inspection of woven fabric composites in pseudo-wavenumber domain
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Model-based deep learning for automated defect detection in composites
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Damage quantification in composites by dispersion analysis of local guided wave modes
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Two-stage characterization of the orthotropic visco-elastic stiffness tensor of composites using guided wavefield data