Spatiotemporally Registered In-Situ and Ex-Situ Datasets for Laser-based Blown Powder Directed Energy Deposition
Abstract
This dataset is comprised of in situ sensing data collected during laser-based, blown powder directed energy deposition (DED) of Inconel 718 representing eight different printing conditions: (1) nominal, (2) +15% scan speed, (3) +12% laser power, (4) +42% powder feed rate, (5) +100% jerk limit, (6) +10% layer height, (7) +20% hatch spacing, (8) +20% carrier gas flow. All eight DED builds constructed an identical test coupon geometry consisting of geometric features representative of industrial print requirements (e.g., bulk deposition, thin walls, overhangs). In situ data consists of xyz-coordinates (100 Hz) and on-axis melt pool camera video (60 Hz), both of which have been temporally synchronized to spatially map the melt pool camera data. In addition, post-build X-ray computed tomography (XCT) data for each of the eight test geometries have been spatially registered to the recorded xyz-coordinates, allowing for comparisons between melt pool camera data and flaws identified in the XCT data.
- Authors:
-
- ORNL-OLCF
- Publication Date:
- DOE Contract Number:
- AC05-00OR22725
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office (EE-5A)
- Subject:
- additive manufacturing, directed energy deposition, in situ sensing, process monitoring, X-ray computed tomography
- OSTI Identifier:
- 2446626
- DOI:
- https://doi.org/10.13139/OLCF/2446626
Citation Formats
Snow, Zackary, Haley, James, Leach, S. Clay, Halsey, William, Jordan, Brian, Rossy, Andres Marquez, and Paquit, Vincent. Spatiotemporally Registered In-Situ and Ex-Situ Datasets for Laser-based Blown Powder Directed Energy Deposition. United States: N. p., 2024.
Web. doi:10.13139/OLCF/2446626.
Snow, Zackary, Haley, James, Leach, S. Clay, Halsey, William, Jordan, Brian, Rossy, Andres Marquez, & Paquit, Vincent. Spatiotemporally Registered In-Situ and Ex-Situ Datasets for Laser-based Blown Powder Directed Energy Deposition. United States. doi:https://doi.org/10.13139/OLCF/2446626
Snow, Zackary, Haley, James, Leach, S. Clay, Halsey, William, Jordan, Brian, Rossy, Andres Marquez, and Paquit, Vincent. 2024.
"Spatiotemporally Registered In-Situ and Ex-Situ Datasets for Laser-based Blown Powder Directed Energy Deposition". United States. doi:https://doi.org/10.13139/OLCF/2446626. https://www.osti.gov/servlets/purl/2446626. Pub date:Mon Nov 04 04:00:00 UTC 2024
@article{osti_2446626,
title = {Spatiotemporally Registered In-Situ and Ex-Situ Datasets for Laser-based Blown Powder Directed Energy Deposition},
author = {Snow, Zackary and Haley, James and Leach, S. Clay and Halsey, William and Jordan, Brian and Rossy, Andres Marquez and Paquit, Vincent},
abstractNote = {This dataset is comprised of in situ sensing data collected during laser-based, blown powder directed energy deposition (DED) of Inconel 718 representing eight different printing conditions: (1) nominal, (2) +15% scan speed, (3) +12% laser power, (4) +42% powder feed rate, (5) +100% jerk limit, (6) +10% layer height, (7) +20% hatch spacing, (8) +20% carrier gas flow. All eight DED builds constructed an identical test coupon geometry consisting of geometric features representative of industrial print requirements (e.g., bulk deposition, thin walls, overhangs). In situ data consists of xyz-coordinates (100 Hz) and on-axis melt pool camera video (60 Hz), both of which have been temporally synchronized to spatially map the melt pool camera data. In addition, post-build X-ray computed tomography (XCT) data for each of the eight test geometries have been spatially registered to the recorded xyz-coordinates, allowing for comparisons between melt pool camera data and flaws identified in the XCT data.},
doi = {10.13139/OLCF/2446626},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Nov 04 04:00:00 UTC 2024},
month = {Mon Nov 04 04:00:00 UTC 2024}
}
