Wire arc additive manufacturing achieves high efficiency and low costs by using a melting wire for directional depositions. Thermal analyses and the finite element method have been applied to predict residual stress and the deformation of fabricated parts. For Ni-based alloy production, a method for predicting solidification microstructure evolution with segregation is needed in order to design precise heat treatment procedures. In this study, a multi-phase field method coupled with a CALPHAD database is developed to simulate the solidification microstructure evolution of a practical Ni-based alloy. Thermal analyses of a wire arc additive manufacturing model were performed by the process modeling of multi-pass depositions with a running cyclic arc. Solidification microstructure evolution was obtained using the temperature profile in each deposited layer by the multi-phase field method. These predicted microstructures are compared with experimental measurements. It is confirmed that the multi-phase field method coupled with the CALPHAD database is effective for predicting solidification microstructure and segregation in the engineering of Ni-based alloys.

A solidification microstructure is formed under high cooling rates and temperature gradients in powder-based additive manufacturing. In this study, a non-equilibrium multi-phase field method (MPFM), based on a finite interface dissipation model, coupled with the Calculation of Phase Diagram (CALPHAD) database, was developed for a multicomponent Ni alloy. A quasi-equilibrium MPFM was also developed for comparison. Two-dimensional equiaxed microstructural evolution for the Ni (Bal.)-Al-Co-Cr-Mo-Ta-Ti-W-C alloy was performed at various cooling rates. The temperature-γ fraction profiles obtained under 10⁵ K/s using non- and quasi-equilibrium MPFMs were in good agreement with each other. Over 10⁶ K/s, the differences between the non- and quasi-equilibrium methods grew as the cooling rate increased. The non-equilibrium solidification was strengthened over a cooling rate of 10⁶ K/s. Columnar-solidification microstructural evolution was performed at cooling rates of 5 × 10⁵ K/s to 1 × 10⁷ K/s at various temperature gradient values under a constant interface velocity (0.1 m/s). The results show that, as the cooling rate increased, the cell space decreased in both methods, and the non-equilibrium MPFM was verified by comparing with the quasi-equilibrium MPFM. Our results show that the non-equilibrium MPFM showed the ability to simulate the solidification microstructure in powder bed fusion additive manufacturing.

A multi-phase field method (MPFM) using the finite interface dissipation model is applied to simulate the solidification microstructure evolution of a stainless-steel composition, including the delta-ferrite to gamma austenite peritectic transformation. The calculation is performed for a quinary system of engineering steel in a two-dimensional field. Thermodynamics calculations using the CALPHAD database in this MPFM are replaced by machine learning prediction to reduce the numerical time. Neural network methodology is introduced for machine learning in this study. The Gibbs free energy and chemical potential values estimated from the CALPHAD database coupling results are inputted into the neural network learning procedure, together with the composition and temperature values. The microstructure evaluated using the obtained neural network parameter is in good agreement with that directly coupled with the CALPHAD database. This calculation is approximately five times faster than direct CALPHAD calculation.

Various defects are produced during the laser powder bed fusion (L-PBF) process, which can affect the quality of the fabricated part. Previous studies have revealed that the defects formed are correlated with molten pool dimensions. Powder particles are thinly spread on a substrate during the L-PBF process; hence, powder packing properties should influence the molten pool dimensions. This study evaluated the influence of particle size on powder packing properties and molten pool dimensions obtained through numerical simulations. Using particles with different average diameters ($D_{av}$) of 24, 28, 32, 36, and 40 $\mathsf{\mu }$m, a series of discrete-element method (DEM) simulations were performed. The packing fraction obtained from DEM simulations became high as $D_{av}$ became small. Several particles piled up for small $D_{av}$, whereas particles spread with almost one-particle diameter thickness for large $D_{av}$. Moreover, the packing structure was inhomogeneous and sparse for large $D_{av}$. As a result of multiphysics computational fluid dynamics (CFD) simulations incorporating particles’ positions as initial solid metal volume, the molten pool width obtained was hardly dependent on the $D_{av}$ and was roughly equivalent to the laser spot size used in the simulations. In contrast, the molten pool depth decreased as $D_{av}$ decreased. Even if the powder bed thickness is the same, small particles can form a complex packing structure by piling up, resulting in a large specific surface area. This can lead to a complex laser reflection compared to the large particles coated with almost one-particle thickness. The complex reflection absorbs the heat generated by laser irradiation inside the powder bed formed on the substrate. As a result, the depth of the molten pool formed below the substrate is reduced for small particles.

The laser powder bed fusion (L-PBF) process provides the cellular microstructure (primary α phase surrounded by a eutectic Si network) inside hypo-eutectic Al–Si alloys. The microstructure changes to the particle-dispersed microstructure with heat treatments at around 500 °C. The microstructural change leads to a significant reduction in the tensile strength. However, the microstructural descriptors representing the cellular and particle-dispersed microstructures have not been established, resulting in difficulty in terms of discussion regarding the structure–property relationship. In this study, an attempt was made to analyze the microstructure in L-PBF-built and subsequently heat-treated Al–12Si (mass%) alloys using the persistent homology, which can analyze the spatial distributions and connections of secondary phases. The zero-dimensional persistent homology revealed that the spacing between adjacent Si particles was independent of Si particle size in the as-built alloy, whereas fewer Si particles existed near large Si particles in the heat-treated alloy. Furthermore, the first principal component of a one-dimensional persistent homology diagram would represent the microstructural characteristics from cellular to particle-dispersed morphology. These microstructural descriptors were strongly correlated with the tensile and yield strengths. This study provides a new insight into the microstructural indices describing unique microstructures in L-PBF-built alloys.