Predictive modeling of laser and electron beam powder bed fusion additive manufacturing of metals at the mesoscale

被引:51
作者
Zakirov, Andrey [1 ]
Belousov, Sergei [1 ]
Bogdanova, Maria [1 ]
Korneev, Boris [1 ]
Stepanov, Andrey [1 ]
Perepelkina, Anastasia [1 ]
Levchenko, Vadim [1 ]
Meshkov, Andrey [2 ]
Potapkin, Boris [1 ]
机构
[1] Kintech Lab Ltd, 3rd Khoroshevskaya St 12, Moscow 123298, Russia
[2] Gen Elect Global Res Ctr, 1 Res Circle, Niskayuna, NY 12309 USA
关键词
Powder bed fusion; 3D mesoscale modeling; Metal alloys; Lattice Boltzmann method; High-performance computing; LATTICE BOLTZMANN METHOD; MELT FLOW; MICROSTRUCTURE; ABSORPTIVITY; FLUID; CHALLENGES; DYNAMICS;
D O I
10.1016/j.addma.2020.101236
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
We present the results of 3D modeling of the laser and electron beam powder bed fusion process at the mesoscale with an in-house developed advanced multiphysical numerical tool. The hydrodynamics and thermal conductivity core of the tool is based on the lattice Boltzmann method. The numerical tool takes into account the random distributions of powder particles by size in a layer and the propagation of the laser (electron beam) with a full ray tracing (Monte Carlo) model that includes multiple reflections, phase transitions, thermal conductivity, and detailed liquid dynamics of the molten metal, influenced by evaporation of the metal and the recoil pressure. The model has been validated by a number of physical tests. We numerically demonstrate a strong dependence of the net energy absorption of the incoming heat source beam by the powder bed and melt pool on the beam power. We show the ability of our model to predict the measurable properties of a single track on a bare substrate as well as on a powder layer. We obtain good agreement with experimental data for the depth, width and shape of a track for a number of materials and a wide range of energy source parameters. We further apply our model to the simulation of the entire layer formation and demonstrate the strong dependence of the resulting layer morphology on the hatch spacing. The presented model could be very helpful for optimizing the additive process without carrying out a large number of experiments in a common trial-and-error method, developing process parameters for new materials, and assessing novel modalities of powder bed fusion additive manufacturing.
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页数:15
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