Grain growth prediction in selective electron beam melting of Ti-6Al-4V with a cellular automaton method

Abstract

An integrated modeling framework coupling the discrete element method for powder spreading, finite volume method for powder bed melting, and an extended cellular automaton method for grain structure evolution during solidification is proposed. In this framework, the initial grain structure of both the substrate and metal powders can be taken into account and used to capture epitaxial and competitive grain growth. The framework is used to provide an in-depth understanding of microstructure development in Ti-6Al-4V during the selective electron beam melting process. The complex process of grain growth during deposition of multiple tracks and multiple layers is modeled through an analysis restarting scheme. The epitaxial growth of grains from pre-existing grains, in particular the grains of partially melted powders, is reproduced. The mechanism of microstructure development within the overlap region of consecutive tracks and layers for various scan strategies is revealed. The simulation results are in qualitative agreement with experimental observation in the literature. The proposed modeling framework is a powerful tool to guide optimal process parameters that lead to designed, site-specific microstructure control and therefore to tailored mechanical properties of parts fabricated by the powder bed fusion additive manufacturing process.