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...
Main Authors: | , , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-02-01
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Series: | Materials |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1944/16/4/1444 |