Akademik Veri Yönetim Sistemi
Computational Materials Science, cilt.161, ss.64-75, 2019 (SCI-Expanded)
Grain structure is one of the most important factors that affect the mechanical properties of metallic alloys. Accurate prediction of as-cast grain structure is critical in the design and manufacturing of metal castings using an integrated computational materials engineering (ICME) approach. In this paper, a three-dimensional (3-D) model based on cellular automaton (CA) and process simulation was developed for predicting grain size of components produced by high pressure die casting (HPDC) of aluminum alloys. The concurrent nucleation and growth of grains were considered in the model. A test specimen casting, consisting of different wall thicknesses, was simulated using a finite element based casting process simulation software ProCAST®. The thermal history of the simulated casting was extracted and used in subsequent mesoscale CA modeling. Different thermal conditions were used to simulate grain nucleation and growth during HPDC. The grain morphology, grain density and grain size were obtained by CA modeling. Electron backscatter diffraction (EBSD) analysis was performed on aluminum castings of different wall thicknesses under various cooling rates to validate the simulation results. The 3-D grain structure model is in excellent agreement with the experimental results, and can be used in ICME design and development of aluminum castings.