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

Efstratios Polyzos; Hendrik Pulju; Peter Mäckel; Michaël Hinderdael; Julien Ertveldt; Danny Van Hemelrijck; Lincy Pyl

doi:10.3390/ma16041444

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

Efstratios Polyzos, Hendrik Pulju, Peter Mäckel, Michaël Hinderdael, Julien Ertveldt, Danny Van Hemelrijck, Lincy Pyl

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

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Abstract

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.

Original language	English
Article number	1444
Pages (from-to)	1-15
Number of pages	15
Journal	Materials
Volume	16
Issue number	4
DOIs	https://doi.org/10.3390/ma16041444
Publication status	Published - 8 Feb 2023

Bibliographical note

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.

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materials-16-01444-v2Final published version, 4.81 MBLicence: CC BY

Cite this

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

abstract = "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-DEDsteel 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.",

author = "Efstratios Polyzos and Hendrik Pulju and Peter M{\"a}ckel and Micha{\"e}l Hinderdael and Julien Ertveldt and {Van Hemelrijck}, Danny and Lincy Pyl",

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doi = "10.3390/ma16041444",

language = "English",

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Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition. / Polyzos, Efstratios; Pulju, Hendrik; Mäckel, Peter; Hinderdael, Michaël; Ertveldt, Julien; Van Hemelrijck, Danny ; Pyl, Lincy.

In: Materials, Vol. 16, No. 4, 1444, 08.02.2023, p. 1-15.

Research output: Contribution to journal › Article › peer-review

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AU - Ertveldt, Julien

AU - Van Hemelrijck, Danny

AU - Pyl, Lincy

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

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