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Local microstructure control in electron beam powder bed fusion (EB-PBF) is of great interest to the additive manufacturing community to realize complex part geometry with targeted performance. The local microstructure control relies on having a detailed understanding of local melt pool physics (e.g., 3-D melt pool shape as well as spatial and temporal variations of thermal gradient (G) and solidification rate (R)). In this research, a new scan strategy referred to as ghost beam is numerically evaluated as a candidate to achieve the targeted G and R of IN718 alloy. The boundary conditions for simulations, including the speed (490 mm/s) and spatial locations of the beam within a given layer, are obtained by using series of snapshot images, recorded at 12,000 frames per second, using a high-speed camera. The heat transfer simulations were performed using TRUCHAS an open-source software deployed within a high-performance computational infrastructure. The simulation results showed that reheating at short beam on-time and time delay decreases both G and R. Local variation of R at the center of the melt pool trailing edge showed periodic temporal fluctuations. Finally, the ghost beam scan strategy was compared to other existing raster and spot scan strategies.

We have investigated the relationship between structure and thermal conductivity in additively manufactured interpenetrating A356/316L composites. We used X-ray microcomputed tomography to characterize the pore structure in as-fabricated composites, finding microporosity in both constituents as well as a 50 μm thick layer of interfacial porosity separating the constituents. We measured the thermal conductivity of a 43 vol% 316L composite to be 53 Wm−1K−1, which is significantly less than that predicted by a simple rule-of-mixtures approximation, presumably because of the residual porosity. Motivated by these experimental results we used periodic homogenization theory to determine the combined effects of porosity and unit cell structure on the effective thermal conductivity. This analysis showed that in fully dense composites, the topology of the constituents has a weak effect on the thermal conductivity, whereas in composites with interfacial porosity, the size and structure of the unit cell strongly influence the thermal conductivity. We also found that an approximation formula of the strong contrast expansion method gives excellent estimates of the effective thermal conductivity of these composites, providing a powerful tool for designing functionally graded composites and for identifying mesostructures with optimal thermal conductivity values.