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Part-Scale Simulation of Ti-6Al-4V Microstructure Evolution during Laser Powder Bed Fusion (LPBF) Process
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Microstructure evolution is closely related to the thermal history in the LPBF process, and the fraction and distribution of different solid-state phases is an important aspect of the microstructure dictating the mechanical properties (ductility and ultimate strength) of additively manufactured metal parts. For instance, additive-manufactured Ti-6Al-4V parts suffer from brittle α′ (martensite) phase, which can be eliminated with a post heat treatment. Nevertheless, it is of significance to possess metal parts manufactured through additive processes without necessitating any subsequent heat treatment. Besides, specific thermal histories can result in customized phase distributions, tailored to meet specific requirements or demands. Thus, it is crucial to perform part-scale thermal simulations and model the corresponding solid state phase transformations to assess the content and distribution of different phases. However, the part-scale simulations are computationally expensive due to the multiscale nature of the LPBF process, mismatch of the characteristic length and time scales of the process and part, and transient thermal history consisting of multiple heating and cooling cycles at a single point triggers a multitude of phase transformation processes. Therefore, it is vital to find out the critical process window that control the volume fraction of solid state phases. A framework consisting of a semi-analytical method for thermal analysis [1] one way coupled to a Ti-6Al-4V phase transformation model [2] is presented to predict the phase distributions for Ti-6Al-4Vcomponents. Effects of volumetric energy density and the number of simultaneously scanning lasers are studied. The semi-analytical method relies on the analytical solution for a line heat sources in a semi-infinite space to capture steep temperature gradients, while a complementary field is used to apply realistic boundary conditions. The latter can be resolved numerically with a coarse spatial resolution leading to high computational efficiency. The Ti-6Al-4V phase transformation model is based on four solid transformation processes including β to α and β to α′ transformations in cooling; α′ to β+α and α to β transformations in heating. During cooling, the β phase first nucleates from the liquid state, most of which will then transform through diffusion into α phase in slow cooling conditions, or α′ phase in a diffusionless manner in fast cooling conditions. When heated, α phase and α′ phase