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Christopher Martin Laursen

Sandia National Laboratories

P.O. Box 969

Livermore, CA 94551

United States

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Scholarly Papers (1)

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Deep-Learned Generators of Porosity Distributions Produced During Metal Additive Manufacturing

Number of pages: 33 Posted: 15 May 2022
Odinakachukwu Francis Ogoke, Kyle Johnson, Michael Glinsky, Christopher Martin Laursen, Sharlotte Kramer and Amir Barati Farimani
Carnegie Mellon University, Sandia National Laboratories, Sandia National Laboratories, Sandia National Laboratories, Sandia National Laboratories and Carnegie Mellon University
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Abstract:

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Deep learning, Microstructural analysis, Generative Adversarial Networks, Porosity