Abstract
In laser powder bed fusion additive manufacturing (LPBFAM), different solidification conditions, e.g., thermal gradient and cooling rate, can be achieved by controlling the process parameters, such as laser power and laser speed. Tailoring the behaviour of the columnar to equiaxed transition (CET) of the printed alloy during fabrication can facilitate the production of highly customized microstructures. In this study, effective analytical solutions for both thermal conduction and solidification are employed to model solidifying melt pools. Microstructure textures and solidification conditions are evaluated for numerous combinations of laser power and laser speed under bead-on-plate conditions. This analytical-based high-throughput tool was demonstrated to select specific process parameters that lead to desired microstructures. Two selected process conditions were examined in detail by a highly parallelized microstructural solidification model to reveal both nucleation and grain growth. Both numerical solutions agree well with experiments that are performed based on bead-on-plate conditions, indicating that these numerical models aid evaluation of the nucleation parameters, providing insights for controlling CET during the LPBFAM processing.
| Original language | English |
|---|---|
| Article number | 012007 |
| Journal | IOP Conference Series: Materials Science and Engineering |
| Volume | 861 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jun 12 2020 |
| Event | 15th International Conference on Modelling of Casting, Welding and Advanced Solidification Processes, MCWASP 2020 - Jonkoping, Sweden Duration: Jun 22 2020 → Jun 23 2020 |
Funding
This research was partially conducted for the project “ExaAM: Transforming Additive Manufacturing through Exascale Simulation”, which was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of the U.S. Department of Energy (DOE) Office of Science and the National Nuclear Security Administration. This research used resources of 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. PDL acknowledges support by the UK-EPSRC (EP/P006566/1). Notice: This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).
| Funders | Funder number |
|---|---|
| DOE Office of Science | DE-AC05-00OR22725 |
| UK-EPSRC | EP/P006566/1 |
| US Department of Energy | |
| U.S. Department of Energy | |
| Office of Science | |
| National Nuclear Security Administration | |
| Oak Ridge National Laboratory |
