Deep-learned generators of porosity distributions produced during metal Additive Manufacturing

• Published in: Additive manufacturing Vol. 60; no. PA; p. 103250
• Main Authors: Ogoke, Odinakachukwu Francis, Johnson, Kyle, Glinsky, Michael, Laursen, Chris, Kramer, Sharlotte, Barati Farimani, Amir
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2022; Elsevier
• Subjects: Additive Manufacturing; Deep learning; Generative Adversarial Networks; Microstructural analysis; Porosity; Deep learning; 0000; 1111; Microstructural analysis; Generative Adversarial Networks; Additive Manufacturing; Porosity

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 componen...