In powder bed fusion (PBF) of metals, energy of a laser or electron beam is utilized to form near‐net‐shaped parts from a powder bed. A very promising application of PBF lies in the direct control of the resulting microstructure by adjusting process parameters. Especially the intentional tilting of grains in one certain direction offers a complete new field of activity for additively produced parts specially designed for a given load case. Nucleation is essential for utilization of this effect. Herein, an alternative approach for modeling nucleation in PBF of metals is introduced. The model is not intended to cover every physical effect of this extreme complex phenomenon. Based on observations reported from different researchers in the field of PBF, a heuristic approach is applied to consider new grains within a cellular automata (CA)‐based crystal growth model for PBF. Utilizing the implicit capability of the CA to model competitive growth of grains, this approach does not require any additional computational capacities. The numerical calculations are carried out using a message–passing interface (MPI) parallelization on a high‐performance computing (HPC) cluster located at the Regional Research Center Erlangen. The numerical results are validated by means of experiments and electron backscatter diffractometric measurements.

The latest advances in additive manufacturing have given rise to an increasing interest in additively built lattice structures due to their superior properties compared to foams and honeycombs. The foundation of these superior properties is a tailored microstructure, which is difficult to achieve in additive manufacturing because of the variety of process parameters influencing the quality of the final part. This work presents the numerical prediction of the resulting grain structure of a lattice structure additively built by electron beam powder bed fusion. A thermal finite-difference model is coupled to a sophisticated cellular automaton-based crystal growth model, including nucleation. Numerically predicted grain structures, considering different nucleation conditions, are compared with experimentally derived EBSD measurements. The comparison reveals that nucleation is important, especially in fine lattice structures. The developed software, utilizing the nucleation model, is finally able to predict the as-built grain structure in lattice structures.

Electron beam powder bed fusion (PBF‐EB) is a promising technology for fabricating complex parts with near‐net‐shape precision. Moreover, PBF‐EB offers a unique opportunity to tailor the microstructure, thereby tuning local mechanical properties. Numerical simulation has emerged as a powerful tool for predicting the evolution of texture and grain structure during PBF‐EB. Herein, the in‐house developed and experimentally validated simulation software, , is employed to investigate the impact of scanning strategy on the texture and grain structure of CMSX‐4 in PBF‐EB‐processed thin tilted lattice struts, commonly found in cellular structures. The core of consists of a finite difference solver for temperature field computation and a cellular automaton model for simulating grain structure evolution. Nine distinct scanning strategies are systematically explored. The resulting texture and grain structures are meticulously compared and comprehensively discussed. Notably, the contour scanning strategy yields distinctive texture and grain structures compared to other explored scanning strategies. This study highlights the capability of in assisting microstructure customization in the PBF‐EB process, and advances the understanding of the relationship between PBF‐EB scanning strategy and resulting microstructure in tilted lattice struts.