A D V A N C E D M A T E R I A L S & P R O C E S S E S | J U L Y / A U G U S T 2 0 2 1 2 1 function was used for R, to assure every coordinate (or point) was melted only once and all coordinates were melted every layer. The Dehoff (D) strategy requires melting in an ordered manner by organizing the coordinates into arrays and subarrays and following a specific order. More information about all three of these scan strategies can be found in M. Quintana[14], M. Kirka[15], and P. Nandwanda[16]. The layer thicknesswas 50 µm for all strategies, and all samples were printed at the same time on a stainless steel build plate. Samples were imaged using an FEI Teneo LoVac field-emission scanning electron microscope (SEM). Images were then analyzed using MIPAR image analysis software. Analysis of internal planes of the samples resulted in the spherical (gas) pore data presented in Table 1 and Figs. 1 and 2. The raster scan strategy (L) had three times as many pores as either of the two point-melting strategies. All spherical pores over 25 µm were only ob- served in the L sample, meaning the selected strategy has a large influence in both the number of pores formed and their sizes. The distribution of pores relative to build height in each sample was also assessed (Fig. 2) by classifying pores as belonging to oneof three equal sized bins (each ~8.3 mm in height, labeled top, middle, and bottom). Samples R and L have a uniform distribution throughout the sample, while D has slightly fewer pores in the middle and more in the bottom. Porosity is, by nature, very common in AM builds, and because pores are typi- cally considered de- fects, research has been done to optimize AM parameters to minimize both the volume fraction and the size of pores in final parts[17,18]. As expected, the measurements of small amounts of porosity in the samples show both large standard deviations (Table 1) and a broad range of pore diameters. A comparison between the samples (strategies) can provide insights into the influence of melt pool morphologies and process parameters on the sizes of gas pores. FLUID DYNAMICS IN AM MELT POOLS Melt pool fluid dynamics can be divided into two general stages: first, the powder initially interacts with the heat source and melts, creating a region ruled by thermocapillary forces; and second, the heat source moves away and the melt pool begins to cool, switching the dominating force from thermocapillary to drag. Thermocapillary forces move pores in the direction of the thermal gradient, which, in the case of both raster and point-melting strategies, will bring pores to the surface of the melt pools[4]. As the melt pool cools, the thermal gradient is reduced, which in turn reduces the magnitude and influence of the thermocapillary force and makes drag the driving and dominant force (particularly in the tail end of the elongated raster melt pool). Fluid flow no longer drives pores to the surface and instead they are trapped inside the liquid material[4]. In other words, pores are more easily eliminated from the leading edge of a raster melt pool, as opposed to the tail end, as a result of thermocapillary forces dominating over drag forces. Notably, because the heat source does not move during the residence time in point-melting strategies, the melt pool does not develop a trailing region (i.e., a “tail”), and instead is by TABLE 1 — STATISTICS OF SPHERICAL PORES: ANALYSIS OF ONE INTERNAL PLANE FOR EACH STRATEGY Scanning strategy Pore count Area fraction* Equivalent diameter (µm) Average Standard deviation Range L 47 0.0000433 14.20 13.55 1.6-51.7 R 15 0.0000028 7.17 5.20 2.8-20.1 D 11 0.0000018 6.97 4.74 2.2-14.8 *Area fraction is based on a sectioned surface of 15 x 25 mm. Fig. 1 — Equivalent diameter distribution of the spherical pores across the three strategies (L, D, and R) observed in one internal plane (15 x 25 mm). Fig. 2 — Distribution of spherical porosity across raster, Dehoff, and random strategies sub-separated into top, middle, and bottom regions within each sample.
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