People | Locations | Statistics |
---|---|---|
Naji, M. |
| |
Motta, Antonella |
| |
Aletan, Dirar |
| |
Mohamed, Tarek |
| |
Ertürk, Emre |
| |
Taccardi, Nicola |
| |
Kononenko, Denys |
| |
Petrov, R. H. | Madrid |
|
Alshaaer, Mazen | Brussels |
|
Bih, L. |
| |
Casati, R. |
| |
Muller, Hermance |
| |
Kočí, Jan | Prague |
|
Šuljagić, Marija |
| |
Kalteremidou, Kalliopi-Artemi | Brussels |
|
Azam, Siraj |
| |
Ospanova, Alyiya |
| |
Blanpain, Bart |
| |
Ali, M. A. |
| |
Popa, V. |
| |
Rančić, M. |
| |
Ollier, Nadège |
| |
Azevedo, Nuno Monteiro |
| |
Landes, Michael |
| |
Rignanese, Gian-Marco |
|
Furat, Orkun
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 20233D analysis of equally X-ray attenuating mineralogical phases utilizing a correlative tomographic workflow across multiple length scalescitations
- 2021Efficient fitting of 3D tessellations to curved polycrystalline grain boundaries
- 2021Efficient Fitting of 3D Tessellations to Curved Polycrystalline Grain Boundariescitations
- 2021Quantitative assessment of microstructural changes of hydrated cement blends due to leaching and carbonation, based on statistical analysis of image datacitations
- 2020Multiscale Tomographic Analysis for Micron-Sized Particulate Samples
- 2020Multiscale Tomographic Analysis for Micron-Sized Particulate Samplescitations
- 2019Mineralogical and microstructural response of hydrated cement blends to leachingcitations
- 2019Stochastic modeling of multidimensional particle properties using parametric copulascitations
- 2019Statistical 3D analysis and modeling of complex particle systems based on tomographic image datacitations
- 2018On microstructure-property relationships derived by virtual materials testing with an emphasis on effective conductivitycitations
Places of action
Organizations | Location | People |
---|
article
Statistical 3D analysis and modeling of complex particle systems based on tomographic image data
Abstract
<jats:title>Abstract</jats:title><jats:p>Geometrically complex particle systems containing individual particles characterized by disperse sizes and irregular non-spherical shapes exist in a wide range of application areas. One example are so-called active particle systems which form an important component of electrodes in lithium-ion batteries.</jats:p><jats:p>Apart from that, particle systems are also analyzed in the context of mining treatment processes in which the relevant particles are not only characterized by their disperse sizes and shapes but also by different material properties. These two examples serve to illustrate methods for the analysis and stochastic modeling of the 3D morphology of geometrically complex particle systems using tomographic image data. These methods are based on the phase- and/or particle-based segmentation of the voxel-based image data. Subsequently, parametric stochastic microstructure models are calibrated to real data by fitting geometrical image characteristics, whereby a significant reduction of complexity is achieved. Suplementary information about the material can also be integrated into the models, when additional imaging techniques, such as scanning electron microscopy, are included.</jats:p>