Numerical analysis of the grain morphology and texture in 316L steel produced by selective laser melting

For tailoring the mechanical properties of additively manufactured parts, we first need to understand and predict additively manufactured microstructures. The present paper aims at in-depth analysis of a three-dimensional (3D) grain structure and texture of 316L austenitic stainless steel produced by powder bed based additive manufacturing (AM). For this purpose, we adopt a 3D framework combining the finite difference (FD) thermal model and modified cellular automata (CA) approach for grain structure prediction. The 3D CAFD model is first validated against the experimental findings on 316L steel produced by selective laser melting. The specimen manufactured by applying a bi-directional scanning strategy is shown to exhibit a strong {110}〈001〉 Goss texture. Multiple re-melting of the bulk material with scanning backward and forward at least once is supposed to result in a tendency of large columnar grains to align with the build direction. The texture strength is shown to increase with the increasing build height, following the exponential trend, as well as the grain size in the transverse and scanning directions.