Projects
Material characterization using spectral reflectance. University of Antwerp
Advanced hyperspectral image analysis for material characterization. University of Antwerp
Characterization of the thermal exposure and material properties of concrete during the fire decay phase for performance-based structural fire engineering. Ghent University
Fires are a frequent threat for society. Structures are commonly designed to avoid collapse in the heating phase of the fire, allowing for safe evacuation. Structural stability in the decay phase is not considered. This is a problem for fire fighter safety, and from the perspective of sustainability and resilience (buildings are not designed to survive a fire). The idea of designing buildings for decay phase safety and post-fire usability has ...
Inverse characterization of metals through information-rich material testing KU Leuven
Characterization of the thermal exposure and material properties of concrete during the fire decay phase for performance-based structural fire engineering Ghent University
Safety and sustainability require designing buildings for the decay phase. To enable this, (i) models for the fire decay phase will be developed; (ii) decay phase properties of concrete will be determined; (iii) structural models will be developed and validated for decay phase performance; and (iv) uncertainties will be quantified and a reliability-based design approach developed.
Inverse characterization of thermomechanical material behavior of metals using multi-physics FEMU KU Leuven
The PhD project aims at devising an inverse identification strategy to fully exploit multi-physics experimental data acquired from an information-rich experiment on a metallic test specimen. The focus in this project is on the identification of thermomechanical constitutive plasticity models used for simulating industrial metal forming and joining processes.
RESONAM: Resonant-based material characterization for metal Additive Manufacturing KU Leuven
The RESONAM project aims to study the variability in the quality of AM parts in relation to variations in the printing parameters and material conditions through the combined use of vibration techniques and material characterization techniques. In addition, new (non-linear) vibration techniques, coupled with learning algorithms, are being developed to predict AM material quality and understand the factors contributing to AM variability. A ...
RESONAM: Resonant-based material characterization for metal Additive Manufacturing Ghent University
RESONAM will study the mechanisms and origins of variability in AM part quality. The effect of modifying printing conditions on the AM material will be investigated with vibrational NDT techniques as well as with various traditional material characterization techniques (metallography, X-CT, …). Additionally, novel (nonlinear) vibrational techniques, coupled to learning algorithms, will be researched to predict the AM material quality, and to ...