Modeling of additive manufacturing processes for metals: Challenges and opportunities

By Marianne M. Francois, A. Sun, Wayne E. King, N. Henson, D. Tourret, C. Bronkhorst, N. Carlson, Christopher K. Newman, T. Haut, J. Bakosi and 17 more. 2017

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Jamming during particle spreading in additive manufacturing (2018, background): “Lack of sufficient understanding of the multi-physics process, such as cohesive and frictional powder flow in the spreading process [5,15] and heat transfer [16,17] in the sintering process, hinder further development of this technology and introduction of new materials [18,19].”
Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches (2020, methodology): “As Francois et al [5] point out in their article highlighting challenges and opportunities for modeling p-s-p-performance in AM, ‘To be useful, the predictions must be able to be run in a reasonable amount of time while retaining sufficient physics fidelity so as to yield trustworthy results’.”
Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo (2017, background): “may remain impractical for microstructural simulations of an entire AM build (especially for powder-bed methods where the cumulative path length of the beam over the entire build process can be many kilometers [4]).”