Abstract
Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. The highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.
Original language | English |
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Article number | 104401 |
Journal | Additive Manufacturing |
Volume | 92 |
DOIs | |
State | Published - Jul 25 2024 |
Funding
This research was partially conducted for the project \u201CExaAM: Transforming Additive Manufacturing through Exascale Simulation,\u201D which was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the US Department of Energy (DOE) Office of Science and the National Nuclear Security Administration. This research used resources from the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. The research was performed under the auspices of the US DOE by Oak Ridge National Laboratory under contract No. DE-AC0500OR22725, UT-Battelle, LLC. This research was partially conducted for the project \u201CExaAM: Transforming Additive Manufacturing through Exascale Simulation,\u201D which was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the US Department of Energy (DOE) Office of Science and the National Nuclear Security Administration. This research used resources from the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05\u201300OR22725. The research was performed under the auspices of the US DOE by Oak Ridge National Laboratory under contract No. DE-AC0500OR22725, UT-Battelle, LLC. This manuscript has been co-authored by UT-Battelle, LLC, under contract DE-AC05\u201300OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/doe-public-access-plan).).
Funders | Funder number |
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National Nuclear Security Administration | |
DOE Public Access Plan | |
U.S. Department of Energy | |
Office of Science | |
UT-Battelle | |
Oak Ridge National Laboratory | DE-AC0500OR22725 |
Keywords
- Additive manufacturing
- Laser powder bed fusion
- Microsegregation
- Solidification microstructure
- Subgrain cellular structure