Image-based material characterization of complex microarchitectured additively manufactured structures
| Autor: | Gábor Lékó, Stefan Kollmannsberger, Péter Balázs, Nina Korshunova, J. Jomo, D. Reznik |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Fabrication Discretization Field (physics) Process (computing) 010103 numerical & computational mathematics 01 natural sciences Characterization (materials science) Computational Engineering Finance and Science (cs.CE) 010101 applied mathematics Computational Mathematics Computational Theory and Mathematics Mesh generation Modeling and Simulation Surface roughness 0101 mathematics 01.02. Számítás- és információtudomány Biological system Porosity Computer Science - Computational Engineering Finance and Science Mathematics |
| Popis: | Significant developments in the field of additive manufacturing (AM) allowed the fabrication of complex microarchitectured components with varying porosity across different scales. However, due to the high complexity of this process, the final parts can exhibit significant variations in the nominal geometry. Computed tomographic images of 3D printed components provide extensive information about these microstructural variations, such as process-induced porosity, surface roughness, and other undesired morphological discrepancies. Yet, techniques to incorporate these imperfect AM geometries into the numerical material characterization analysis are computationally demanding. In this contribution, an efficient image-to-material-characterization framework using the high-order parallel Finite Cell Method is proposed. In this way, a flexible non-geometry-conforming discretization facilitates mesh generation for very complex microstructures at hand and allows a direct analysis of the images stemming from CT-scans. Numerical examples including a comparison to the experiments illustrate the potential of the proposed framework in the field of additive manufacturing product simulation. |
| Databáze: | OpenAIRE |
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