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In situ Visible Light and Thermal Imaging Data from a Laser Powder Bed Fusion Additive Manufacturing Process Co-Registered to X-ray Computed Tomography and Fatigue Data

  • Snow, Zackary | Oak Ridge National Laboratory
  • Scime, Luke | Oak Ridge National Laboratory
  • Joslin, Chase | Oak Ridge National Laboratory
  • Halsey, William | Oak Ridge National Laboratory
  • Marquez, Andres | Oak Ridge National Laboratory
  • Ziabari, Amir | Oak Ridge National Laboratory
  • Paquit, Vincent | Oak Ridge National Laboratory
  • Dehoff, Ryan | Oak Ridge National Laboratory
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Overview

Description

This dataset is comprised of in situ sensing data collected during a laser-based powder bed fusion additive manufacturing process, as well as rasterized scan path information, post-build X-ray computed tomography (XCT), and fatigue test results. A total of 64 cylinders, approximately 15 mm in diameter and 102 mm tall, were printed out of stainless steel 316H on a Colibrium Additive Concept Laser M2 Series 5 machine. Parameters known to produce dense material were used to construct 56 of these cylinders, while the remaining 8 cylinders were printed with relatively high energy density parameters prone to producing keyhole pores. In addition, two spatter generation blocks were constructed upstream of the 64 cylinders such that ejecta produced during the melting of the spatter generators were stochastically seeded onto the 64 cylinders. Based on previous experiments, these spatter particles were theorized to produce stochastic lack-of-fusion pores. During the construction of the build, high-resolution images of reflected light in the visible spectrum were captured both before and after recoating for each print layer. Additionally, temporally integrated thermal imaging in the near infrared spectrum produced integrated sum and max images on a layerwise basis. The multimodal in situ data has been co-registered to the build plate coordinate system, allowing for identification of process anomalies (e.g., spatter particles) apparent in the two sensors. Following construction of the build, the cylinders were subjected to XCT to identify internal flaws, and the resulting data have also been registered to the build plate coordinate system. Finally, 60 of the 64 cylinders were machined into fatigue coupons conforming to ASTM E466 and subsequently subjected to either high- or -low-cycle fatigue testing. The results of the fatigue tests have also been included in the dataset, and the XCT data corresponded to the approximate location of the gauge sections of the machine fatigue specimen geometry.

Funding resources

DOE contract number

DE-AC05-00OR22725

Originating research organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring organization

Office of Science (SC)

Details

DOI

10.13139/ORNLNCCS/2524534

Release date

April 21, 2025

Dataset

Dataset type

MM Multimedia

Software

Any software capable of reading HDF5 files (e.g., HDFView, h5py)

Acknowledgements

Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:

This work was carried out [in part] at Oak Ridge National Laboratory, managed by UT-Battelle, LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725.

Category

  • 42 ENGINEERING

Keywords

  • Powder Bed Additive Manufacturing,
  • Image Segmentation,
  • In-Situ Process Monitoring,
  • Machine Learning,
  • X-Ray Computed Tomography,
  • Additive manufacturing,
  • Machine vision,
  • Fatigue Life