Modeling analysis of grain morphologies in Directed energy deposition (DED) coating with different laser scanning patterns

Abstract Directed energy deposition (DED) is often utilized to coat metallic part with complex geometries in a variety of anti-corrosion materials or high-temperature materials. Computer-controlled scanning patterns always affect the grain morphology in coating, which can further influence coating’s mechanical properties. In this study, a Kinetic Monte Carlo (KMC) Potts model is applied to predict the grain morphology under two different frequently-used laser scanning patterns: unidirectional and bidirectional raster patterns. Then the predicted grain morphologies in coatings with these two scanning patters were quantified and analyzed respectively. The simulated results were verified with an electron backscatter diffraction (EBSD) image of SS304 DED part reported by a literature. It was found that the primary grain morphology in coating was columnar shape. Some fine equiaxed grains appeared near the center line of scanning path. However, the columnar grains had crescentic shapes under unidirectional pattern, which was different from the linear shape of columnar grains under bidirectional pattern.