Prediction of microstructure formation in laser powder bed fusion process.
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Lang Yuan | University of South Carolina
Jean-Luc Fattebert | Oak Ridge National Laboratory
Adrian Sabau | Oak Ridge National Laboratory
Description
The 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
Funding Information
DOE Contract Number
DE-AC0500OR22725Originating Research Organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Sponsoring Organization
Office of Science (SC)Details
Release Date
February 23, 2024Subject
36 MATERIALS SCIENCEKeywords
Additive manufacturing, Laser powder bed fusion, Solidification microstructure, Microsegregation, Subgrain cellular structureDataset
Dataset Type
ND Numeric DataSoftware
Visualization software: ParaviewCite This Dataset:
Yuan, L., Fattebert, J., Sabau, A. (2024). Prediction of microstructure formation in laser powder bed fusion process.. Oak Ridge National Laboratory. https://doi.org/10.13139/OLCF/2283409.
Acknowledgements
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Advanced Scientific Computing Research programs in the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.