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

Onderzoeksoutput: Articlepeer review

1 Citaat (Scopus)
25 Downloads (Pure)

Samenvatting

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 measurements and predictions. In particular, the thermal expansion coefficient of thin-wall L-DED
steel specimens is measured and then used to predict the displacement fields around the drilling hole in incremental hole-drilling tests. The incremental hole-drilling test is performed on cubic L-DED steel specimens and the displacement fields are visualized using a 3D micro-digital image correlation setup. A good agreement is achieved between predictions and experimental measurements.
Originele taal-2English
Artikelnummer1444
Pagina's (van-tot)1-15
Aantal pagina's15
TijdschriftMaterials
Volume16
Nummer van het tijdschrift4
DOI's
StatusPublished - 8 feb 2023

Bibliografische nota

Funding Information:
This research was funded by the FWO Research Foundation–Flanders grant number 1102822N. This research was additionally funded by the FWO under research project S009319 N (Hi-PAS-project).

Publisher Copyright:
© 2023 by the authors.

Copyright:
Copyright 2023 Elsevier B.V., All rights reserved.

Vingerafdruk

Duik in de onderzoeksthema's van 'Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition'. Samen vormen ze een unieke vingerafdruk.

Citeer dit