Ghent University Academic Bibliography

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Contribution of 3D automated mineralogy in unraveling the formation history of Nb-Ta-Sn mineralized LCT pegmatites in the Karagwe-Ankole belt (Central Africa)

Florian Buyse (UGent) , Stijn Dewaele (UGent) , Matthieu Boone (UGent) and Veerle Cnudde (UGent)

(2024) GEOLOGICA BELGICA. 27(1-2). p.1-14
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- Research Data
4D X-ray micro-velocimetry data of multiphase flow perturbations in porous media

Tom Bultreys (UGent) , Sharon Ellman (UGent) , Christian M. Schlepütz, Matthieu Boone (UGent) , Gülce Kalyoncu Pakkaner (UGent) , Shan Wang (UGent) , Mostafa Borji (UGent) , Stefanie Van Offenwert (UGent) , Niloofar Moazami Goudarzi (UGent) , Wannes Goethals (UGent) , et al.

(2023)
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Understanding the mechanical strength and dynamic structural changes of wood-based products using X-ray computed tomography

Wanzhao Li, Zheng Zhang, Changtong Mei, Pierre Kibleur (UGent) , Joris Van Acker (UGent) and Jan Van den Bulcke (UGent)

(2023) WOOD MATERIAL SCIENCE & ENGINEERING. 18(2). p.454-463
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Combining automated mineralogy with X-ray computed tomography for internal characterization of ore samples at the microscopic scale

Florian Buyse (UGent) , Stijn Dewaele (UGent) , Matthieu Boone (UGent) and Veerle Cnudde (UGent)

(2023) NATURAL RESOURCES RESEARCH. 32(2). p.461-478
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4D synchrotron X-ray imaging of grain scale deformation mechanisms in a seismogenic gas reservoir sandstone during axial compaction

Jeroen Van Stappen, J. A. McBeck, B. Cordonnier, R. P. J. Pijnenburg, F. Renard, C. J. Spiers and S. J. T. Hangx

(2022) ROCK MECHANICS AND ROCK ENGINEERING. 55(8). p.4697-4715
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Three-dimensional distribution of platinum group minerals in natural MSS-ISS ores from the Norilsk One deposit, Russia

Jonathan Sittner (UGent) , V. Brovchenko, Asim Siddique (UGent) , Florian Buyse (UGent) , M. Boone, A.D. Renno, Veerle Cnudde (UGent) , Margarita Merkulova (UGent) and S.F. Sluzhenikin

(2022) FRONTIERS IN EARTH SCIENCE. 10.
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- PhD Thesis
Spectral X-ray computed tomography : potential and applications in geoscience

Jonathan Sittner (UGent)

(2022)
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Detailed experimental validation and benchmarking of six models for longitudinal tensile failure of unidirectional composites

C. Breite, A. Melnikov, A. Turon, A. B. de Morais, C. Le Bourlot, E. Maire, E. Schöberl, F. Otero, F. Mesquita, I. Sinclair, et al.

(2022) COMPOSITE STRUCTURES. 279.
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X-ray CT based multi-layer unit cell modeling of carbon fiber-reinforced textile composites : segmentation, meshing and elastic property homogenization

Yuriy Sinchuk (UGent) , Oxana Shishkina, Mikael Gueguen, Loic Signor, Carole Nadot-Martin, Herve Trumel and Wim Van Paepegem (UGent)

(2022) COMPOSITE STRUCTURES. 298.
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- Journal Article
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Deep learning segmentation of wood fiber bundles in fiberboards

Pierre Kibleur (UGent) , Jan Aelterman (UGent) , Matthieu Boone (UGent) , Jan Van den Bulcke (UGent) and Joris Van Acker (UGent)

(2022) COMPOSITES SCIENCE AND TECHNOLOGY. 221.

Academic Bibliography

Contribution of 3D automated mineralogy in unraveling the formation history of Nb-Ta-Sn mineralized LCT pegmatites in the Karagwe-Ankole belt (Central Africa)

4D X-ray micro-velocimetry data of multiphase flow perturbations in porous media

Understanding the mechanical strength and dynamic structural changes of wood-based products using X-ray computed tomography

Combining automated mineralogy with X-ray computed tomography for internal characterization of ore samples at the microscopic scale

4D synchrotron X-ray imaging of grain scale deformation mechanisms in a seismogenic gas reservoir sandstone during axial compaction

Three-dimensional distribution of platinum group minerals in natural MSS-ISS ores from the Norilsk One deposit, Russia

Spectral X-ray computed tomography : potential and applications in geoscience

Detailed experimental validation and benchmarking of six models for longitudinal tensile failure of unidirectional composites

X-ray CT based multi-layer unit cell modeling of carbon fiber-reinforced textile composites : segmentation, meshing and elastic property homogenization

Deep learning segmentation of wood fiber bundles in fiberboards

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