Simulation for additive manufacturing

Kollmannsberger, Stefan; Rank, Ernst; Auricchio, Ferdinando; Steinmann, Paul

doi:10.1016/j.camwa.2019.08.020

Cited by 1 publication

(1 citation statement)

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“…A large spectrum of scientific developments has led to a better understanding of the underlying physical processes and has contributed to the improvement of additive manufacturing (AM) (e.g. [29], [38], [49]). However, a complete description of the AM processes and products remains a challenge.…”

Section: Introductionmentioning

confidence: 99%

Image-based material characterization of complex microarchitectured additively manufactured structures

Korshunova

Jomo

Lékó

et al. 2020

Computers & Mathematics with Applications

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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. Computer 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.

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Section: Introductionmentioning

confidence: 99%