Grain structure control is challenging for metal additive manufacturing (AM). Grain structure optimization requires the control of grain morphology with grain size refinement, which can improve the mechanical properties of additive manufactured components. This work summarizes methods to promote fine equiaxed grains in both the additive manufacturing process and subsequent heat treatment. Influences of temperature gradient, solidification velocity and alloy composition on grain morphology are discussed. Equiaxed solidification is greatly promoted by introducing a high density of heterogeneous nucleation sites via powder rate control in the direct energy deposition (DED) technique or powder surface treatment for powder-bed techniques. Grain growth/coarsening during post-processing heat treatment can be restricted by presence of nano-scale oxide particles formed in-situ during AM. Grain refinement of martensitic steels can also be achieved by cyclic austenitizing in post-processing heat treatment. Evidently, new alloy powder design is another sustainable method enhancing the capability of AM for high-performance components with desirable microstructures.
Additive manufacturing (AM) of titanium alloys is a rapidly growing field due to an increase in design flexibility of parts. However, AM parts are highly anisotropic in material microstructure and mechanical behavior due to the change of the local processing conditions in the build-up process. This study follows a link chain model to investigate the relationships between process parameters, cooling rate, porosity and mechanical behavior. The aim of this work is to present a framework that is inspired by the three-link chain model. The framework combines theoretical, computational and experimental approaches. We demonstrate this by using an in-house thermal simulator to link predicted cooling rates with micrographs describing experimental shape descriptors to develop a relationship between solidification cooling rate and porosity geometry. Finally, representative volume elements from predicted porosity maps allow for a prediction of mechanical properties at localized areas. The capability of being able to predict mechanical behavior of titanium alloys is demonstrated for the directed energy deposition process.
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