Additive Manufacturing Benchmarks 2022 (AM-Bench 2022): Powders I
Program Organizers: Brandon Lane, National Institute of Standards and Technology; Lyle Levine, National Institute of Standards and Technology

Monday 1:30 PM
August 15, 2022
Room: Cabinet/Judiciary Suite
Location: Hyatt Regency Bethesda

Session Chair: Maxwell Praniewicz, National Institute of Standards and Technology


1:30 PM  
Spatially-resolved Mapping and Statistically-based Analysis of Powder Layer Density by Transmission X-ray Imaging: Ryan Penny1; Daniel Oropeza2; Reimar Weissbach3; Patrick Praegla4; Christoph Meier4; Wolfgang Wall4; John Hart3; 1Massachusetts Institue of Technology; 2NASA Jet Propulsion Laboratory; 3Massachusetts Institute of Technology; 4Technical University of Munich
    The uniformity and packing density of powder layers used in AM are intimately related to powder characteristics as well as mechanical boundary conditions imposed by the spreading mechanism and the build surface. Although optical techniques can provide critical information on layer quality, especially that related to surface topography and visible flaws, we recently demonstrated the use of transmission X-ray imaging to spatially map the density of thin powder layers for metal AM. We present this technique and the integration of a precision spreading mechanism with X-ray imaging, enabling high-fidelity comparison of layers produced with rigid and compliant spreading tools. Our results, combined with powder characterization (e.g., size distribution, angle of repose) and discrete element method (DEM) simulations, clarify how powder cohesion and spreading strategy influence the bulk and statistical nature of powder layers in AM, and further enable rapid assessment of spreading strategies and identification of practical guidelines.

1:50 PM  
Quantifying the Size, Shape, and Porosity of Metal Powder Particles using X-ray Computed Tomography: Newell Moser1; Orion Kafka1; Edward Garboczi1; Lyle Levine1; Nik Hrabe1; Jake Benzing1; Nicholas Derimow1; 1National Institute of Standards and Technology
    The particle size and shape distributions of metal powders used in additive manufacturing powder bed fusion processes are of technological importance for the final built product. Consequently, these measurements are a cornerstone towards the pivotal development of high-fidelity simulations of additive manufacturing processes. This presentation describes a set of techniques using X-ray computed tomography (X-ray CT), combined with various mathematical algorithms, to measure the 3D size, shape, and internal porosity of individual particles. Inconel powder particles that were used for AM Bench 2022 were characterized using these techniques, and the results and conclusions of these X-ray CT analyses are presented here. Moreover, a brief introduction to our new, open-source suite of Python scripts will be provided, which simplify the image analysis of particles and X-ray CT data in general.

2:10 PM  
Optimizing Roller-based Spreading of Fine, Cohesive Metal Powders via DEM Simulations: Reimar Weissbach1; Patrick Praegla2; Ryan Penny1; Christoph Meier2; Wolfgang Wall2; John Hart1; 1Massachusetts Institute of Technology; 2Technical University of Munich
    Use of fine powders in binder jetting (BJ) is desirable for improved sintering kinetics and high final part density. However, for smaller particles, cohesive forces dominate gravitational forces, leading to poor powder flowability and clumping, which results in non-uniformity and low packing fractions in the spread layer. This typically necessitates use of roller-based mechanisms that apply high shear to the powder. As such, a detailed understanding of the relationship between powder cohesion and the mechanics that enable controlled spreading using rollers is necessary to advance process capabilities. Via discrete element (DEM) simulations that consider cohesion and enable high-fidelity analysis of boundary conditions from the roller and build surface, we study how high layer packing density as well as low surface roughness can be achieved, using Ti64 powder as a model system. Our results suggest material and size-specific spreading conditions (e.g., roller rotation and translation speed) that optimize packing density.