Abstract
Additive manufacturing (AM) of metals involves a wide range of processing conditions that result in significantly different thermal gradients and solidification behaviors across technologies such as directed energy deposition (DED), wire arc additive manufacturing (WAAM), and laser powder bed fusion (LPBF). These variations strongly influence microstructure evolution and crystallographic texture, which ultimately determine the mechanical performance of fabricated components. In this study, a two-dimensional cellular automaton (CA) framework is developed to model microstructure evolution during directional solidification under MAM-relevant thermal conditions. The model incorporates a prescribed thermal field, stochastic nucleation based on local undercooling, and anisotropic growth kinetics. Texture development is quantified using the probability-density distribution of crystal angle relative to the build direction. Simulations performed at a constant interface velocity and varying thermal gradients demonstrate a clear transition from equiaxed grain structures at low thermal gradient to strongly columnar morphologies at high thermal gradient. These regimes correspond to different MAM processes, ranging from DED/WAAM to LPBF. The corresponding orientation distributions show increasing crystallographic alignment with the build direction, indicating progressive texture strengthening. These results demonstrate that the proposed framework provides a unified and computationally efficient tool for investigating microstructure and texture evolution across a range of MAM processes.