Understanding and controlling the composition segregation during powder spreading is of key importance in the additive manufacturing (AM) of composite materials. Under this circumstance, the segregation behavior of WC/316 L composite powders during spreading in laser powder bed fusion (LPBF) AM was numerically investigated by the discrete element method. The effects of process conditions (i.e., spreader velocity and geometry) and powder properties (i.e., size and shape of the WC powder) on the powder bed composition segregation and related characteristics were systematically analyzed. Corresponding mechanisms were identified from microscopic scale in terms of particle velocity, motion trajectory, mechanical behavior, and energy information. Finally, proper solutions in designing and constructing WC/316 L composite materials with desired gradient structures were proposed. The results show that the small blade velocity (V) will enhance the negative segregation, increase the average packing density ρ¯, and decrease uniformity ρvc in the WC/316 L composite powder bed. Compared with the blade, the roller can increase the negative segregation (Seroller = −0.027 < Seblade = −0.019) and the average packing density (ρ¯roller = 0.31>ρ¯blade = 0.20). When the WC/316 L size ratio increases from 25 μm/45 μm to 45 μm/45 μm, the negative segregation becomes weaker, and its value increases from −0.084 to −0.007. When the size ratio increases to 65 μm/45 μm, the powder behaves positive segregation with Semax = 0.017; in this case, the packing density is the lowest (0.14), and the uniformity is the worst (0.17). In comparison with spherical shape, polyhedral WC powder can reduce the negative segregation of the powder bed (Sesphere = −0.019 < Sepolyhedron = −0.008), while the WC shape has less effect on the packing density and uniformity. The density difference of the WC and 316 L powders leads to the difference in energy and force, resulting in different motion and segregation behaviors in the composite powder bed. For WC/316 L composite powder with a fixed composition, the condition of V = 0.025 m/s, WC/316 L size ratio = 25 μm/45 μm, roller spreader, and spherical WC can realize the proper composition gradient along the spreading direction in the composite powder bed.@en

The performance of Persistent Scatterer Interferometry (PSI) depends heavily on Persistent Scatterer (PS) density. In order to increase PS density, we can apply Super-Resolution reprocessing algorithms in PSI. Involving the reprocessing algorithms and the peak-detection-based Persistent Scatterer Candidate points (PSCs) selection method, the full PSI chain is referred to as Super-Resolution PSI (SR-PSI). The implementation of the Super-Resolution reprocessing algorithm, however, is computationally intensive, which makes SR-PSI time-consuming. In this work, we propose to improve the efficiency by constraining the Capon-based reprocessing to the non-homogeneous areas (e.g., urban areas). We notice that the Capon algorithm performs similarly as the Fourier-based algorithm for homogeneous regions (e.g., grassland), thus we can use Single Look Complex (SLC) images for these areas. With the Coefficient of Variation (CV) as the index, we divide the full image into two classes: homogeneous areas, for which we select PSCs from the original stack, and non-homogeneous areas, for which we extract PSCs from the Capon-based reprocessed images. Then we combine the PSCs of both cases for further PSI processing. We applied the combination method to a stack of TerraSAR-X data. The results show that the proposed approach is more computationally efficient than the original SR-PSI with the effectiveness uncompromised, especially for applications aiming at the urban deformation.@en