In the Powder Bed Fusion-Laser Beam Melting (PBF-LB/M) process, the part-based manufacturing parameter adoption by a corrected laser scan strategy is a crucial step to successfully manufacturing metal components. These parameters are often determined by a trial and error approach or by simplified simulations like inherent strain. In this paper it is proposed to adapt the Lattice Boltzmann Method (LBM) for a hatch-based part-scale simulation of the thermal distribution during the manufacturing process, to optimize scan strategy and geometry, based on temperature gradients in the manufactured part. The high parallelisation degree of the LBM allows the efficient utilization of modern computing capabilities, creating a potential for faster design cycles. By determining the suitability of the LBM in comparison to traditional methods. The presented results prove, that the adapted LBM can model the PBF-LB/M process while outperforming the traditional methods and offering more potential improvements.

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Suitability Study of the Lattice Boltzmann Method for Part-Scale Thermal Simulation of the Additive Manufacturing Build Process

  • Maximilian Pohling,
  • Alexander Seidler,
  • Arthur Hilbig,
  • Stefan Holtzhausen,
  • Kristin Paetzold-Byhain

摘要

In the Powder Bed Fusion-Laser Beam Melting (PBF-LB/M) process, the part-based manufacturing parameter adoption by a corrected laser scan strategy is a crucial step to successfully manufacturing metal components. These parameters are often determined by a trial and error approach or by simplified simulations like inherent strain. In this paper it is proposed to adapt the Lattice Boltzmann Method (LBM) for a hatch-based part-scale simulation of the thermal distribution during the manufacturing process, to optimize scan strategy and geometry, based on temperature gradients in the manufactured part. The high parallelisation degree of the LBM allows the efficient utilization of modern computing capabilities, creating a potential for faster design cycles. By determining the suitability of the LBM in comparison to traditional methods. The presented results prove, that the adapted LBM can model the PBF-LB/M process while outperforming the traditional methods and offering more potential improvements.