Ferreira, Stephanie ; Klein, Benjamin ; Stork, André ; Fellner, Dieter W. (2022)
Physics-driven digital twin for laser powder bed fusion on GPUs.
8th European Congress on Computational Methods in Applied Sciences and Engineering. Oslo, Norway (05.-09.06.2022)
doi: 10.23967/eccomas.2022.221
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Metal Additive Manufacturing (AM) processes such as Laser Powder Bed Fusion (LPBF) suffer from part distortion due to the localized melting and resolidification of the metal powder, which introduces stresses and strains. Despite becoming more and more important as a manufacturing process, options for simulating the printing process to predict the distortions are limited, especially because existing solutions often require very long computation times. In this work, we present the results of an implementation of the inherent strain method on graphics processing units (GPUs) that exploits the massive parallelism of the many GPU cores to speed up the simulations considerably compared to CPU-based implementations.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Ferreira, Stephanie ; Klein, Benjamin ; Stork, André ; Fellner, Dieter W. |
| Art des Eintrags: | Bibliographie |
| Titel: | Physics-driven digital twin for laser powder bed fusion on GPUs |
| Sprache: | Englisch |
| Publikationsjahr: | 24 November 2022 |
| Verlag: | SCIPEDIA |
| Buchtitel: | ECCOMAS Congress 2022 - 8th European Congress on Computational Methods in Applied Sciences and Engineering |
| Veranstaltungstitel: | 8th European Congress on Computational Methods in Applied Sciences and Engineering |
| Veranstaltungsort: | Oslo, Norway |
| Veranstaltungsdatum: | 05.-09.06.2022 |
| DOI: | 10.23967/eccomas.2022.221 |
| Kurzbeschreibung (Abstract): | Metal Additive Manufacturing (AM) processes such as Laser Powder Bed Fusion (LPBF) suffer from part distortion due to the localized melting and resolidification of the metal powder, which introduces stresses and strains. Despite becoming more and more important as a manufacturing process, options for simulating the printing process to predict the distortions are limited, especially because existing solutions often require very long computation times. In this work, we present the results of an implementation of the inherent strain method on graphics processing units (GPUs) that exploits the massive parallelism of the many GPU cores to speed up the simulations considerably compared to CPU-based implementations. |
| Freie Schlagworte: | Physically based simulation, General Purpose Computation on Graphics Processing Unit (GPGPU), 3D Printing |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 06 Jan 2023 10:12 |
| Letzte Änderung: | 11 Jan 2023 09:01 |
| PPN: | 503547239 |
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