Laser-Induced Keyhole Defect Dynamics during Metal Additive Manufacturing
Abstract
Laser powder bed fusion (LPBF) metal additive manufacturing provides distinct advantages for aerospace and biomedical applications. However, widespread industrial adoption is limited by a lack of confidence in part properties driven by an incomplete understanding of how unique process parameters relate to defect formation and ultimately mechanical properties. To address that gap, high-speed X-ray imaging is used to probe subsurface melt pool dynamics and void-formation mechanisms inaccessible to other monitoring approaches. This technique directly observes the depth and dynamic behavior of the vapor depression, also known as the keyhole depression, which is formed by recoil pressure from laser-driven metal vaporization. Also, vapor bubble formation and motion due to melt pool currents is observed, including instances of bubbles splitting before solidification into clusters of smaller voids while the material rapidly cools. Other phenomena include bubbles being formed from and then recaptured by the vapor depression, leaving no voids in the final part. Such events complicate attempts to identify defect formation using surface-sensitive process-monitoring tools. Finally, once the void defects form, they cannot be repaired by simple laser scans, without introducing new defects, thus emphasizing the importance of understanding processing parameters to develop robust defect-mitigation strategies based on experimentally validated models.
- Authors:
-
[1];
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Ames Lab. and Iowa State Univ., Ames, IA (United States)
- Publication Date:
- Research Org.:
- SLAC National Accelerator Lab., Menlo Park, CA (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE National Nuclear Security Administration (NNSA); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Advanced Manufacturing Office
- OSTI Identifier:
- 1560679
- Alternate Identifier(s):
- OSTI ID: 1557328; OSTI ID: 1560982
- Report Number(s):
- LLNL-JRNL-748807
Journal ID: ISSN 1438-1656; TRN: US2000556
- Grant/Contract Number:
- AC02-07CH11358; AC02-76SF00515; SC0012704; AC52-07NA27344
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Advanced Engineering Materials
- Additional Journal Information:
- Journal Volume: 21; Journal Issue: 10; Journal ID: ISSN 1438-1656
- Publisher:
- Wiley
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 42 ENGINEERING; 36 MATERIALS SCIENCE; additive manufacturing; laser powder bed fusion; titanium; X-ray imaging
Citation Formats
Kiss, Andrew M., Fong, Anthony Y., Calta, Nicholas P., Thampy, Vivek, Martin, Aiden A., Depond, Philip J., Wang, Jenny, Matthews, Manyalibo J., Ott, Ryan T., Tassone, Christopher J., Stone, Kevin H., Kramer, Matthew J., van Buuren, Anthony, Toney, Michael F., and Nelson Weker, Johanna. Laser-Induced Keyhole Defect Dynamics during Metal Additive Manufacturing. United States: N. p., 2019.
Web. doi:10.1002/adem.201900455.
Kiss, Andrew M., Fong, Anthony Y., Calta, Nicholas P., Thampy, Vivek, Martin, Aiden A., Depond, Philip J., Wang, Jenny, Matthews, Manyalibo J., Ott, Ryan T., Tassone, Christopher J., Stone, Kevin H., Kramer, Matthew J., van Buuren, Anthony, Toney, Michael F., & Nelson Weker, Johanna. Laser-Induced Keyhole Defect Dynamics during Metal Additive Manufacturing. United States. doi:10.1002/adem.201900455.
Kiss, Andrew M., Fong, Anthony Y., Calta, Nicholas P., Thampy, Vivek, Martin, Aiden A., Depond, Philip J., Wang, Jenny, Matthews, Manyalibo J., Ott, Ryan T., Tassone, Christopher J., Stone, Kevin H., Kramer, Matthew J., van Buuren, Anthony, Toney, Michael F., and Nelson Weker, Johanna. Tue .
"Laser-Induced Keyhole Defect Dynamics during Metal Additive Manufacturing". United States. doi:10.1002/adem.201900455. https://www.osti.gov/servlets/purl/1560679.
@article{osti_1560679,
title = {Laser-Induced Keyhole Defect Dynamics during Metal Additive Manufacturing},
author = {Kiss, Andrew M. and Fong, Anthony Y. and Calta, Nicholas P. and Thampy, Vivek and Martin, Aiden A. and Depond, Philip J. and Wang, Jenny and Matthews, Manyalibo J. and Ott, Ryan T. and Tassone, Christopher J. and Stone, Kevin H. and Kramer, Matthew J. and van Buuren, Anthony and Toney, Michael F. and Nelson Weker, Johanna},
abstractNote = {Laser powder bed fusion (LPBF) metal additive manufacturing provides distinct advantages for aerospace and biomedical applications. However, widespread industrial adoption is limited by a lack of confidence in part properties driven by an incomplete understanding of how unique process parameters relate to defect formation and ultimately mechanical properties. To address that gap, high-speed X-ray imaging is used to probe subsurface melt pool dynamics and void-formation mechanisms inaccessible to other monitoring approaches. This technique directly observes the depth and dynamic behavior of the vapor depression, also known as the keyhole depression, which is formed by recoil pressure from laser-driven metal vaporization. Also, vapor bubble formation and motion due to melt pool currents is observed, including instances of bubbles splitting before solidification into clusters of smaller voids while the material rapidly cools. Other phenomena include bubbles being formed from and then recaptured by the vapor depression, leaving no voids in the final part. Such events complicate attempts to identify defect formation using surface-sensitive process-monitoring tools. Finally, once the void defects form, they cannot be repaired by simple laser scans, without introducing new defects, thus emphasizing the importance of understanding processing parameters to develop robust defect-mitigation strategies based on experimentally validated models.},
doi = {10.1002/adem.201900455},
journal = {Advanced Engineering Materials},
number = 10,
volume = 21,
place = {United States},
year = {2019},
month = {7}
}
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