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Generating virtual process maps of SLM using powder-scale SPH simulations

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Abstract

In selective laser melting (SLM), three-dimensional parts are build up from a metal powder bed by layer-wise melting with a laser. While SLM offers a high flexibility in geometrical design and material texture, the interplay of dozens of parameters is difficult to analyze experimentally. The current research focuses on numerical simulation to increase confidence in manufactured parts and to reduce the time to market. Using a smoothed particle hydrodynamics (SPH) implementation on GPU, the 3D melt pool dynamics in a single laser track can be simulated within less than 2 h with a reasonable spatial resolution of 3 \(\upmu \)m. This is an extreme speedup compared to concurrent CFD methods that have recently been applied to the same problem. Using a SPH implementation on GPU, the 3D melt pool dynamics in a single laser track can be simulated within less than an hour with a reasonable spatial resolution of 3 \(\upmu \)m. This is an extreme speedup compared to concurrent CFD methods that have recently been applied to the same problem. The computational efficiency allows to conduct parameter studies, which before were prohibitively expensive, to generate a virtual process. To make the simulations possible a curvature calculation technique was applied, which is novel in the field of SPH. Additionally the advantage of a direct description of the internal energy is outlined by comparing the approach with the commonly applied apparent heat approach. Designers may profit from the fast simulations in two different scenarios: firstly, through a direct numerical simulation of certain parameter combinations and scenarios and, secondly, by informing advanced surrogate models or part-scale models to predict the behavior of the entire part being produced. When adapting the heat source model, the SPH framework may also be used to describe the related electron beam melting process.

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Acknowledgements

The authors wish to thank Tobias Bode for providing the DEM-based particle packing algorithm.

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  1. Institute of Continuum Mechanics, Leibniz University Hannover, Appelstraße 11, 30167, Hannover, Germany

    Jan-Philipp Fürstenau, Henning Wessels, Christian Weißenfels & Peter Wriggers

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  1. Jan-Philipp Fürstenau
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Appendices

Appendix A: Variable material parameters

In this section the used temperature variable process parameters, describing SS 316L according to [28, 57], are given in a tabular and graphical way (Table 6, Figs. 20, 21, 22, 23, 24).

Table 6 Tabular overview of temperature-dependent variables
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Fig. 20
figure 20

Temperature plotted over internal energy

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Fig. 21
figure 21

Thermal conductivity plotted over the temperature

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Fig. 22
figure 22

Heat capacity plotted over the temperature

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Fig. 23
figure 23

Surface tension coefficient plotted over the temperature

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Fig. 24
figure 24

Heat capacity for the apparent heat approach according to [14] with the values according to [57] and the melting point as a vertical line

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Appendix B: Surface tension results

See Fig. 25.

Fig. 25
figure 25

Final contours of the melting path. Top: constant surface tension coefficient; middle: constant surface tension coefficient; bottom: full Marangoni convection

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Appendix C: Yadroitsev results

See Figs. 26 and 27.

Fig. 26
figure 26

Plot of the full powder bed around 80% of the simulation time for the laser speeds 0.06 m/s, 0.08 m/s, 0.12 m/s, 0.16 m/s and 0.2 m/s. Light gray represents powder material, medium gray represents resolidified material, and dark gray represents molten material

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Fig. 27
figure 27

Plot of the melt pool contours around 80% of the simulation time for the laser speeds 0.06 m/s, 0.08 m/s, 0.12 m/s, 0.16 m/s and 0.2 m/s (top to bottom)

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Fürstenau, JP., Wessels, H., Weißenfels, C. et al. Generating virtual process maps of SLM using powder-scale SPH simulations. Comp. Part. Mech. 7, 655–677 (2020). https://doi.org/10.1007/s40571-019-00296-3

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