Powder bed fusion (PBF) has become a widely used additive manufacturing (AM) technology to produce metallic parts. Since the PBF process is driven by a moving heat source, consistency in part production, particularly when varying geometries, has proven difficult. Thermal field evolution during the manufacturing process determines both geometric and mechanical properties of the fabricated components. Simulations of the thermal field evolution can provide insight into desired process parameter selection for a given material and geometry. Thermal simulation of the PBF process is computationally challenging due to the geometric complexity of the manufacturing process and the inherent computational complexity that requires a numerical solution at every time increment of the process.

We propose a new thermal simulation of the PBF process based on the laser scan path. Our approach is unique in that it does not restrict itself to simulations on the part design geometry, but instead simulates the formation of the geometry based on the process plan of a part. The implication of this distinction is that the simulations are in tune with the as-manufactured geometry, meaning that calculations are more aligned with the process than the design, and thus could be argued is a more realistic abstraction of real-world behavior. The discretization is based on the laser scan path, and the thermal model is formulated directly in terms of the manufacturing primitives. An element growth mechanism is introduced to simulate the evolution of a melt pool during the manufacturing process. A spatial data structure, called contact graph, is used to represent the discretized domain and capture all thermal interactions during the simulation. The simulation is localized through exploiting spatial and temporal locality, which is based on known empirical data. This limits the need to update to at most a constant number of elements at each time step. This implies that the proposed simulation not only scales to handle three-dimensional (3D) printed components of arbitrary complexity but also can achieve real-time performance. The simulation is fully implemented and validated against experimental data and other simulation results.

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