The resulting properties of parts fabricated by powder bed fusion additive manufacturing processes are determined by their porosity, local composition, and microstructure. The objective of this work is to examine the influence of the stochastic powder bed on the process window for dense parts by means of numerical simulation. The investigations demonstrate the unique capability of simulating macroscopic domains in the range of millimeters with a mesoscopic approach, which resolves the powder bed and the hydrodynamics of the melt pool. A simulated process window reveals the influence of the stochastic powder layer. The numerical results are verified with an experimental process window for selective electron beam-melted Ti-6Al-4V. Furthermore, the influence of the powder bulk density is investigated numerically. The simulations predict an increase in porosity and surface roughness for samples produced with lower powder bulk densities. Due to its higher probability for unfavorable powder arrangements, the process stability is also decreased. This shrinks the actual parameter range in a process window for producing dense parts.
Powder bed fusion comprises all layer‐by‐layer additive manufacturing technologies of parts built from a powder bed. To exploit the advantages of near‐net shape manufacturing of complex geometries, in contrast to conventional manufacturing techniques, it is essential to understand the underlying physical phenomena occurring during processing for a broad range of different process scenarios. Experimental approaches are costly in time and material and provide only limited access inside the process. However, to understand the process behavior and predict final properties of parts, numerical approaches are powerful tools. This work presents the software suite S𝔸𝕄PLE (Simulation of Additive Manufacturing on the Powder scale using a Laser or Electron beam) which simulates the consolidation and microstructure evolution during beam‐based powder bed fusion processes. It is based on a mesoscopic approach, in which statistical powder beds, melt pool dynamics, evaporation effects, and microstructure evolution are considered and can simulate the build‐up of more than 100 layers. The underlying models and algorithms of the software including a newly applied thermal model are described. Finally, the unique potential of the software is demonstrated by reviewing the influence of various powder bed properties, the effects of evaporation, and the grain structure evolution in the process.
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