Prediction of microstructure formation in laser powder bed fusion process.
10.13139/OLCF/2283409The datasets are results analyzing the predicted microstructures in a single track during the laser powder bed fusion additive manufacturing process. They are the outputs by running the opensource code, muMatScale (The code can be cited at: Yuan, Lang, Fattebert, Jean-Luc, and Sabau, Adrian. (2023, August 03). muMatScale. [Computer software]. https://github.com/lang-yuan/muMatScale. https://doi.org/10.11578/dc.20240112.2.) For each set of data, it contains the time-dependent information of Temperature, Fraction Solid, Grain ID, Grain Angle ( crystallographic orientations by Euler angles), and solute Composition. The dataset can be visualized by Paraview (https://www.paraview.org/ ). The 6 datasets are: 1. Baseline_base1_n4e14_dt20: baseline case with bulk nucleation density of 4E+14/m^3, undercooling of 20K, substrate nucleation density of 1.5E+15/m^3 2. Nuc_n4e15_dt20: case with bulk nucleation density of 4E+15/m^3, undercooling of 20K, substrate nucleation density of 1.5E+15/m^3 3. Nuc_n4e15_dt50: case with bulk nucleation density of 4E+15/m^3, undercooling of 50K, substrate nucleation density of 1.5E+15/m^3 4. Nuc_n6e15_dt20: case with bulk nucleation density of 4E+16/m^3, undercooling of 20K, substrate nucleation density of 1.5E+15/m^3 5. Base4_n4e14_dt20: case with bulk nucleation density of 4E+14/m^3, undercooling of 20K, substrate nucleation density of 6.0E+15/m^3 6. Base16_n4e14_dt20: case with bulk nucleation density of 4E+14/m^3, undercooling of 20K, substrate nucleation density of 2.4E+16/m^3
Published: 2024-02-23 10:20:23 Download DatasetDataset Properties
Field | Value |
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Authors |
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Project Identifier | 17-SC-20-SC |
Dataset Type | ND Numeric Data |
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Software Needed | Visualization software: Paraview |
Originating Organizations | Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) |
Sponsoring Organizations | Office of Science (SC) |
DOE Contract | DE-AC0500OR22725 |
Acknowledgements
Papers using this dataset are requested to include the following text in their acknowledgements:
*Support for 10.13139/OLCF/2283409 is provided by the U.S. Department of Energy, project 17-SC-20-SC under Contract DE-AC0500OR22725. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.