The effects of bimodal grain size distributions on the mechanical properties of a newly developed TRansformation-TWinning induced plasticity (TRIP/TWIP) steel were investigated. The microstructures with different levels of bimodal grain size distributions were achieved through rolling at 1000, 1100 and 1200 °C where the restoration processes (in particular recrystallization) could be occurred at different rates. The results indicated that the bimodal distribution parameter was increased by raising the rolling temperature and lowering the thickness reduction. In addition, the room temperature strength and ductility were higher for the materials rolled at higher temperatures, where the level of bimodal grain size distributions (bimodality) was greater. This was justified considering the higher possibility of strain induced transformation and twinning in coarser grains than that of finer ones; this in fact would dictate the material work hardening potential during subsequent tensile deformation. For the material rolled at 1000 °C, where the grain size distributions were more homogeneous and the level of bimodal distributions was low, the austenite to martensite transformation during tensile deformation at room temperature was the prevailing mechanism to induce the plasticity. In contrast, in the materials rolled at 1100 and 1200 °C the mechanical twinning came into action thereby a rapid hardening region was recognized in their work hardening behavior. These effects were correlated to the length of work hardening region (dictated by twinning), and the magnitude of hardening rate (controlled by transformation of austenite to a' martensite).Peer ReviewedPostprint (author's final draft

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A model to predict the conditions for printability is presented. The model focuses on crack prevention, as well as on avoiding the formation of defects such as keyholes, balls and lack of fusion. Crack prevention is ensured by controlling the solidification temperature range and path, as well as via quantifying its ability to resist thermal stresses upon solidification. Defect formation prevention is ensured by controlling the melt pool geometry and by taking into consideration the melting properties. The model’s core relies on thermodynamics and physical analysis to ensure optimal printability, and in turn offers key information for alloy design and selective laser melting process control. The model is shown to describe accurately defect formation of 316L austenitic stainless steels reported in the literature.

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