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Erschienen in: Computational Mechanics 4/2023

28.01.2023 | Original Paper

Heat transfer finite element model for laser powder-bed fusion on consolidated simulation geometry

verfasst von: Ruixiong Hu, Stephen Rock, Antoinette M. Maniatty

Erschienen in: Computational Mechanics | Ausgabe 4/2023

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Abstract

Being able to efficiently predict the extreme temperature and temperature gradient fields in metal laser powder-bed fusion additive manufacturing for a given set of process parameters for multiple passes and layers is needed to improve process design and control. This work presents a simple, yet novel heat transfer finite element formulation defined on the consolidated geometry mapped to the actual powder on a substrate geometry to predict the temperature field and melting history along with experimental calibration and validation for tests on Inconel 718. Defining the model on the consolidated powder geometry eliminates the need to explicitly model the consolidation and allows for better mesh quality in the regions of greatest importance, where the material melts. The model includes phase change and the effect of powder consolidation on the laser-material interaction. The model is verified by comparing to simulations that explicitly model the powder consolidation. A calibration step is used to determine the laser-material interaction parameters required in the model based on the experimentally observed melt pool cross-section geometry for different processing parameters on a bare plate, which eliminates the variability due to a powder layer. Simulations for a single powder layer case are carried out with all parameters prescribed and validated by comparing predicted melt pool cross-section dimensions with those observed experimentally for different processing parameters.

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Metadaten
Titel
Heat transfer finite element model for laser powder-bed fusion on consolidated simulation geometry
verfasst von
Ruixiong Hu
Stephen Rock
Antoinette M. Maniatty
Publikationsdatum
28.01.2023
Verlag
Springer Berlin Heidelberg
Erschienen in
Computational Mechanics / Ausgabe 4/2023
Print ISSN: 0178-7675
Elektronische ISSN: 1432-0924
DOI
https://doi.org/10.1007/s00466-023-02267-1

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