Abstract
Single-track laser fusion were simulated using a heat-transfer-solidification-only (HTS) model and its extension with fluid dynamics (HTS_FD) model using a parallel open-source code, which included laminar fluid dynamics, flat-free surface of the molten alloy, heat transfer, phase-change, evaporation, and surface tension phenomena. The results illustrate that the fluid dynamics affects the solidification and ensuing microstructure. For the HTS_FD simulations, thermal gradient, G was found to exhibit a maximum at the extremity of the solidified pool (i.e., at the free surface), while for HTS simulations, G exhibited a maximum around the entire edge of the solidified pool. HTS_FD simulations predicted a wider range of cooling rates than the HTS simulations, exhibited an increased spread in the solidification speed, V variation within the melt-pool with respect to the HTS model results. Primary dendrite arm spacing (PDAS) were evaluated based on power law correlations and marginal stability theory models using the (G, V) from HTS and HTS_FD simulations to quantify the effect of the fluid dynamics on the microstructure. At low-laser powers and low-scan speeds, the PDAS obtained with the fluid dynamics model (HTS_FD) was larger by more than 30 pct with respect to the PDAS calculated with the simple HTS model. A new PDAS correlation, i.e., λ1[μm]=832G[K/m]-0.5V[m/s]-0.25, which uses the (G, V) results from the HTS_FD model was developed and validated against experimental results.
Original language | English |
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Pages (from-to) | 1263-1281 |
Number of pages | 19 |
Journal | Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science |
Volume | 51 |
Issue number | 3 |
DOIs | |
State | Published - Jun 1 2020 |
Funding
This research was conducted for the projects “Process Maps for Tailoring Microstructure in Laser Powder-Bed Fusion Additive Manufacturing,” which was supported by the High-Performance Computing for Manufacturing Project Program (HPC4Mfg), managed by the U.S. Department of Energy Advanced Manufacturing Office within the Energy Efficiency and Renewable Energy Office and “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 Office of Science and the National Nuclear Security Administration. The effort for the HPC4Mfg project was conducted in collaboration with GE Global Research (GEGR). For both projects, the research was performed under the auspices of the US Department of Energy by Oak Ridge National Laboratory under Contract No. DE-AC0500OR22725, UT-Battelle, LLC. The authors would like to thank Neil Carlson of Los Alamos National Laboratory, the Truchas developer project leader, for feedback during the projects. 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 ). This research was conducted for the projects ?Process Maps for Tailoring Microstructure in Laser Powder-Bed Fusion Additive Manufacturing,? which was supported by the High-Performance Computing for Manufacturing Project Program (HPC4Mfg), managed by the U.S. Department of Energy Advanced Manufacturing Office within the Energy Efficiency and Renewable Energy Office and ?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 Office of Science and the National Nuclear Security Administration. The effort for the HPC4Mfg project was conducted in collaboration with GE Global Research (GEGR). For both projects, the research was performed under the auspices of the US Department of Energy by Oak Ridge National Laboratory under Contract No. DE-AC0500OR22725, UT-Battelle, LLC. The authors would like to thank Neil Carlson of Los Alamos National Laboratory, the Truchas developer project leader, for feedback during the projects.