Modeling and Characterization of Cohesion in Fine Metal Powders with a Focus on Additive Manufacturing Process Simulations
arXiv:1804.06816 · doi:10.1016/j.powtec.2018.11.072
Abstract
The cohesive interactions between fine metal powder particles crucially influence their flow behavior, which is in turn important to many powder-based manufacturing processes including emerging methods for powder-based metal additive manufacturing (AM). The present work proposes a novel modeling and characterization approach for micron-scale metal powders, with a special focus on characteristics of importance to powder-bed AM. The model is based on the discrete element method (DEM), and the considered particle-to-particle and particle-to-wall interactions involve frictional contact, rolling resistance and cohesive forces. Special emphasis lies on the modeling of cohesion. The proposed adhesion force law is defined by the pull-off force resulting from the surface energy of powder particles in combination with a van-der-Waals force curve regularization. The model is applied to predict the angle of repose (AOR) of exemplary spherical Ti-6Al-4V powders, and the surface energy value underlying the adhesion force law is calibrated by fitting the corresponding angle of repose values from numerical and experimental funnel tests. To the best of the authors' knowledge, this is the first work providing an experimental estimate for the effective surface energy of the considered class of metal powders. By this approach, an effective surface energy of is found for the investigated Ti-6Al-4V powder. This value is considerably lower than typical experimental values for flat metal contact surfaces in the range of , indicating the crucial influence of factors such as surface roughness and chemical surface contamination on fine metal powders. More importantly, the present study demonstrates that a neglect of the related cohesive forces leads to a drastical underestimation of the AOR and, consequently, to an insufficient representation of the bulk powder behavior.
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