Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition

This article presents a novel approach for assessing the effects of residual stresses in laser-directed energy deposition (L-DED). The approach focuses on exploiting the potential of rapidly growing tools such as machine learning and polynomial chaos expansion for handling full-field data for measur...

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Detalles Bibliográficos
Autores principales: Polyzos, Efstratios, Pulju, Hendrik, Mäckel, Peter, Hinderdael, Michael, Ertveldt, Julien, Van Hemelrijck, Danny, Pyl, Lincy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9965518/
https://www.ncbi.nlm.nih.gov/pubmed/36837074
http://dx.doi.org/10.3390/ma16041444

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9965518/
https://www.ncbi.nlm.nih.gov/pubmed/36837074
http://dx.doi.org/10.3390/ma16041444

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