A Co-Registered In-Situ and Ex-Situ Tensile Properties Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-11)
- Scime, Luke | Oak Ridge National Laboratory
- Joslin, Chase | Oak Ridge National Laboratory
- Collins, David | Oak Ridge National Laboratory
- Halsey, William | Oak Ridge National Laboratory
- Duncan, Ryan | Oak Ridge National Laboratory
- Paquit, Vincent | Oak Ridge National Laboratory
Overview
Description
This release contains a co-registered in-situ and ex-situ Peregrine dataset from five Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L builds containing 6,299 SS-J3 individually tracked tensile coupons. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, room-temperature static tensile test results, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided. To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. You may need to create an exception for Globus in your antivirus software so that it can create an Endpoint. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Be sure to confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (4) Sometimes users will need to manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab before the download will begin.
Funding resources
DOE contract number
DE-AC05-00OR22725Originating research organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Sponsoring organization
Office of Energy Efficiency and Renewable Energy (EERE);Office of Energy Efficiency and Renewable Energy (EERE), Advanced Manufacturing Office (EE-5A);Office of Nuclear Energy (NE)Related resources
- Cites (DOI): https://doi.org/10.1016/j.addma.2020.101453
- Continues (DOI): https://doi.org/10.13139/ORNLNCCS/1779073
- Continues (DOI): https://doi.org/10.13139/ORNLNCCS/1896716
- Cites (DOI): https://doi.org/10.3389/fmech.2021.767444
Details
DOI
10.13139/ORNLNCCS/2001425Release date
September 28, 2023Dataset
Dataset type
SM Specialized MixSoftware
any software or programming language capable of reading HDF5 files, such as Python's h5py packageAcknowledgements
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
- 36 MATERIALS SCIENCE,
- 97 MATHEMATICS AND COMPUTING
Keywords
- Powder Bed Additive Manufacturing,
- Image Segmentation,
- In-Situ Process Monitoring,
- Tensile Testing