| Autor: |
Marouane Kabbej, Valérie Guillard, Hélène Angellier-Coussy, Valentin Thoury-Monbrun, Nathalie Gontard, Laurent Orgéas, Sabine Rolland du Roscoat, Sébastien Gaucel |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
MethodsX, Vol 10, Iss , Pp 102177- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2215-0161 |
| DOI: |
10.1016/j.mex.2023.102177 |
| Popis: |
Reconstruction of three-dimensional (3D) structure from experimental image acquisition (e.g., from micro computed tomography data) is very useful in composite material science. Composite considered are characterized by a dispersion of particles in a continuous phase. Many properties of the composite (e.g., mass transfer properties) depend on its structural assembly. A reliable prediction of these properties requires to well represent this structure and especially, the region at the vicinity of the dispersed phase. (3D) structure generation must thus permit to (1) simplify the real composite structure observed to make it compatible with further modelling tasks (e.g., meshing constraints in finite elements methods, computation time) and (2) keep enough representativeness of the structure of the specimen to produce reliable numerical predictions. This article describes an innovative, cascading (3D) reconstruction procedure of composite material from microtomography data. • First step of this pipeline is the extraction of relevant structural markers from microtomography images using image analysis. • Second step is the modelling of the distribution of the structural markers selected (statistical laws). • Third and final step is the reconstruction of the (3D) structures based on the pre-determined distribution laws in a RVE (representative volume element) of the composite. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
