Novel Simulation-Inspired Roller Spreading Strategies for Fine and Highly Cohesive Metal Powders

When fine powders are to be used in powder bed metal additive manufacturing (AM), a roller is typically utilized for spreading. However, the cohesive nature of fine metal powder still presents challenges, resulting in low density and/or inconsistent layers under sub-standard spreading conditions. Here, through computational parameter studies with an integrated discrete element-finite element (DEM-FEM) framework, we explore roller-based strategies that are predicted to achieve highly cohesive powder layers. The exemplary feedstock is a Ti-6Al-4V 0-20 um powder, that is emulated using a self-similarity approach based on experimental calibration. The computational studies explore novel roller kinematics including counter-rotation as well as angular and transverse oscillation applied to standard rigid rollers as well as coated rollers with compliant or non-adhesive surfaces. The results indicate that most of these approaches allow to successfully spread highly cohesive powders with high packing fraction (between 50%-60% in a single layer) and layer uniformity provided that the angular/oscillatory, relative to the transverse velocity, as well as the surface friction of the roller are sufficiently high. Critically, these spreading approaches are shown to be very robust with respect to varying substrate conditions (simulated by means of a decrease in surface energy), which are likely to occur in LBPF or BJ, where substrate characteristics are the result of a complex multi-physics (i.e., powder melting or binder infiltration) process. In particular, the combination of the identified roller kinematics with compliant surface coatings, which are known to reduce the risk of tool damage and particle streaking in the layers, is recommended for future experimental investigation

Towards Additively Manufactured Metamaterials with Powder Inclusions for Controllable Dissipation: The Critical Influence of Packing Density

Particle dampers represent a simple yet effective means to reduce unwanted oscillations when attached to structural components. Powder bed fusion additive manufacturing of metals allows to integrate particle inclusions of arbitrary shape, size and spatial distribution directly into bulk material, giving rise to novel metamaterials with controllable dissipation without the need for additional external damping devices. At present, however, it is not well understood how the degree of dissipation is influenced by the properties of the enclosed powder packing. In the present work, a two-way coupled discrete element - finite element model is proposed allowing for the first time to consistently describe the interaction between oscillating deformable structures and enclosed powder packings. As fundamental test case, the free oscillations of a hollow cantilever beam filled with various powder packings differing in packing density, particle size, and surface properties are considered to systematically study these factors of influence. Critically, it is found that the damping characteristics strongly depend on the packing density of the enclosed powder and that an optimal packing density exists at which the dissipation is maximized. Moreover, it is found that the influence of (absolute) particle size on dissipation is rather small. First-order analytical models for different deformation modes of such powder cavities are derived to shed light on this observation

Spatial Mapping of Powder Layer Density for Metal Additive Manufacturing via X-ray Microscopy

Uniform powder spreading is a requisite for creating consistent, high-quality components via powder bed additive manufacturing (AM), wherein layer density and uniformity are complex functions of powder characteristics, spreading kinematics, and mechanical boundary conditions. High spatial variation in particle packing density, driven by the stochastic nature of the spreading process, impedes optical interrogation of these layer attributes. Thus, we present transmission X-ray imaging as a method for directly mapping the effective depth of powder layers at process-relevant scale and resolution. Specifically, we study layers of nominal 50-250 micrometer thickness, created by spreading a selection of commercially obtained Ti-6Al-4V, 316 SS, and Al-10Si-Mg powders into precision-depth templates. We find that powder layer packing fraction may be predicted from a combination of the relative thickness of the layer as compared to mean particle size, and flowability assessed by macroscale powder angle of repose. Power spectral density analysis is introduced as a tool for quantification of defect severity as a function of morphology, and enables separate consideration of layer uniformity and sparsity. Finally, spreading is studied using multi-layer templates, providing insight into how particles interact with both previously deposited material and abrupt changes in boundary condition. Experimental results are additionally compared to a purpose-built discrete element method (DEM) powder spreading simulation framework, clarifying the competing role of adhesive and gravitational forces in layer uniformity and density, as well as particle motion within the powder bed during spreading

Laser beam shape optimization: Exploring alternative profiles to Gaussian-shaped laser beams in powder bed fusion of metals

Laser-based powder bed fusion of metals (PBF-LB/M) commonly utilizes Gaussian-shaped laser beams characterized by a high intensity at the center. However, this type of profile leads to localized high temperatures and temperature gradients. When the laser power is increased beyond a certain threshold, the temperature inside the melt pool can reach the boiling point, causing excessive metal evaporation, hydrodynamic instabilities, and undesired effects such as keyholing. On the other hand, ring-shaped laser beams generate a more uniform temperature distribution but tend to produce shallower, wider, and shorter melt pools with reduced resolution compared to the Gaussian profiles. The deep, narrow, and elongated melt pools generated by the Gaussian shapes still have advantages for increased precision in the PBF-LB/M processes. This contribution uses numerical optimization to generate a new laser beam shape that also leads to a deep, narrow, and elongated melt pool, similar to a Gaussian-shaped beam, while maintaining a lower and more uniform temperature distribution inside the melt pool. The resulting optimized laser profile lowers the maximum laser intensity by 40 % without decreasing the total laser power compared to the Gaussian profile. The more uniform distribution of temperature with a peak value of just above 3 000 ◦C indicates a conduction dominated process with less hydrodynamic and minimal evaporative effects. This is expected to reduce the associated defects and improve the process stabilityMechanical Engineerin