Abstract
While experimental work has shown promising results regarding control of additive manufacturing metal grain structure, the effects of processing parameters on the grain structure is difficult to understand and predict from experiment alone. To this end, a modeling framework is developed which sequentially couples a macro-scale, semi-analytic thermal model, and a meso-scale, cellular automata-based microstructure model. This framework is applied to electron beam additive manufacturing of Inconel 718 using a complex spot scan pattern. The model shows that, with the same scan pattern, variations in the spot time and electron-beam current produce thermal histories with significant spatial and temporal differences, which then produce complex solidification conditions from the interplay between molten pools in the same layer and subsequent layers, resulting in vastly different grain structures. It is noted that the framework can significantly reduce the computational expenses for coupled thermal-metallurgical problems, and has the potential to be used for component level problems.
| Original language | English |
|---|---|
| Article number | 015002 |
| Journal | Modelling and Simulation in Materials Science and Engineering |
| Volume | 31 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 2023 |
Funding
Research was sponsored by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office. S K and W T acknowledge the financial support from the National Science Foundation under Grant No. CMMI-1752218 and the technical support from the Center for High-Performance Computing at the University of Utah. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. 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). Research was sponsored by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Manufacturing Office. S K and W T acknowledge the financial support from the National Science Foundation under Grant No. CMMI-1752218 and the technical support from the Center for High-Performance Computing at the University of Utah. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. 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 ).
Keywords
- EBSD
- crystallographic texture
- electron-beam additive manufacturing
- grain structure
- melt pool
- multi-physics modeling solidification
- scan pattern
