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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Bibliographic Details
Main Authors: Efstratios Polyzos, Hendrik Pulju, Peter Mäckel, Michael Hinderdael, Julien Ertveldt, Danny Van Hemelrijck, Lincy Pyl
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Materials
Subjects:
Online Access:https://www.mdpi.com/1996-1944/16/4/1444