| Abstract Scope |
Within fusion-based additive manufacturing (AM) processes, understanding the temperature across the part during the build is useful for predicting cooling rates, material properties, and process defects. A significant portion of the thermal models developed specifically for AM are based on laser power bed fusion (LPBF) data and parameters. However, directed energy deposition (DED) processes have no less need for specialized thermal models, since heat buildup and the consequent part deformation are significant issues. Benchmarking models for DED requires evaluating both model accuracy and computational cost. In many cases, these two performance metrics have opposing effects; a classic example would be mesh density in finite element models. This work, still in progress, focuses on developing real-world data to evaluate models and comparisons of computational cost on identical computers. The models evaluated include classic finite element models, semi-analytical models, and models originally developed for LPBF being explored for use in DED processes. |