Abstract
This paper presents a computational framework to model the mechanical response of selective laser melting processed 316L stainless steel by considering both the grain and melt pool in the material. In this model, inspired by the experimental observations, individual melt pools are approximated by overlapped cylinder segments that are connected to each other by cohesive surfaces. Each of the melt pools contains several grains, modeled by Voronoi tessellation method to represent the realistic grains in a polycrystalline material. The proposed computational model is used to predict the effects of various microstructural properties on the mechanical properties of the manufactured samples. These microstructural properties include melt pool size, the overlap between neighboring melt pools, texture, process-induced defects, and the orientation of layers with respect to the loading direction. Furthermore, several flat dog bone shaped 316L stainless steel samples are fabricated with selected values of laser power, scanning velocity, and scanning direction and their mechanical properties were determined to relate the macro-mechanical properties to the microstructural modeling and processing parameters.
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