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Deep-Learned Generators of Porosity Distributions Produced During Metal Additive Manufacturing. (arXiv:2205.05794v1 [cs.LG])
May 13, 2022, 1:11 a.m. | Francis Ogoke, Kyle Johnson, Michael Glinsky, Chris Laursen, Sharlotte Kramer, Amir Barati Farimani
cs.LG updates on arXiv.org arxiv.org
Laser Powder Bed Fusion has become a widely adopted method for metal Additive
Manufacturing (AM) due to its ability to mass produce complex parts with
increased local control. However, AM produced parts can be subject to
undesirable porosity, negatively influencing the properties of printed
components. Thus, controlling porosity is integral for creating effective
parts. A precise understanding of the porosity distribution is crucial for
accurately simulating potential fatigue and failure zones. Previous research on
generating synthetic porous microstructures have succeeded …
More from arxiv.org / cs.LG updates on arXiv.org
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