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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MDPI AG
2023-02-01
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| Series: | Materials |
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| Online Access: | https://www.mdpi.com/1996-1944/16/4/1444 |
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| author | Efstratios Polyzos Hendrik Pulju Peter Mäckel Michael Hinderdael Julien Ertveldt Danny Van Hemelrijck Lincy Pyl |
| author_facet | Efstratios Polyzos Hendrik Pulju Peter Mäckel Michael Hinderdael Julien Ertveldt Danny Van Hemelrijck Lincy Pyl |
| author_sort | Efstratios Polyzos |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T08:30:11Z |
| format | Article |
| id | doaj.art-39029647341c4116b24647fdb45f7a0c |
| institution | Directory Open Access Journal |
| issn | 1996-1944 |
| language | English |
| last_indexed | 2024-03-11T08:30:11Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Materials |
| spelling | doaj.art-39029647341c4116b24647fdb45f7a0c2023-11-16T21:49:52ZengMDPI AGMaterials1996-19442023-02-01164144410.3390/ma16041444Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy DepositionEfstratios Polyzos0Hendrik Pulju1Peter Mäckel2Michael Hinderdael3Julien Ertveldt4Danny Van Hemelrijck5Lincy Pyl6Department of Mechanics of Materials and Constructions, Vrije Universiteit Brussel (VUB), Pleinlaan 2, BE-1050 Brussels, Belgiumisi-sys GmbH, Wasserweg 8, D-34131 Kassel, Germanyisi-sys GmbH, Wasserweg 8, D-34131 Kassel, GermanyDepartment of Mechanical Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, BE-1050 Brussels, BelgiumDepartment of Mechanical Engineering, Vrije Universiteit Brussel (VUB), Pleinlaan 2, BE-1050 Brussels, BelgiumDepartment of Mechanics of Materials and Constructions, Vrije Universiteit Brussel (VUB), Pleinlaan 2, BE-1050 Brussels, BelgiumDepartment of Mechanics of Materials and Constructions, Vrije Universiteit Brussel (VUB), Pleinlaan 2, BE-1050 Brussels, BelgiumThis 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.https://www.mdpi.com/1996-1944/16/4/14443D micro-DICincremental hole drillingL-DED AISI 316L stainless steelthermal expansion coefficientresidual thermal stressesstochastic finite element modeling |
| spellingShingle | Efstratios Polyzos Hendrik Pulju Peter Mäckel Michael Hinderdael Julien Ertveldt Danny Van Hemelrijck Lincy Pyl Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition Materials 3D micro-DIC incremental hole drilling L-DED AISI 316L stainless steel thermal expansion coefficient residual thermal stresses stochastic finite element modeling |
| title | Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition |
| title_full | Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition |
| title_fullStr | Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition |
| title_full_unstemmed | Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition |
| title_short | Measuring and Predicting the Effects of Residual Stresses from Full-Field Data in Laser-Directed Energy Deposition |
| title_sort | measuring and predicting the effects of residual stresses from full field data in laser directed energy deposition |
| topic | 3D micro-DIC incremental hole drilling L-DED AISI 316L stainless steel thermal expansion coefficient residual thermal stresses stochastic finite element modeling |
| url | https://www.mdpi.com/1996-1944/16/4/1444 |
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