Laser Powder Bed Fusion (LPBF) technology represents the most promising metal additive manufacturing process to be scaled up to an industrial level for producing full batches of parts within the automotive aerospace and health sectors, among others. Despite this higher technological readiness, imperfections such as warping, porosities or undesired non-equilibrium microstructures can arise unexpectedly due to the complex thermal histories inherent to LPBF. Being able to anticipate to such imperfections is thus of high importance. With this purpose, numerical modeling strategies can be employed to significantly reduce experimental work on the melt pool scale. This allows to quantify the odds and magnitude of these process unwanted effects. More precisely, Computational Fluid Dynamics (CFD) enables high-fidelity models on the laser-matter interaction during LPBF processing. In this work, a modeling approach is presented in which the driving forces for melt formation are included in a CFD workspace, where multiple reflections of the laser on the melt pool Liquid-Gas Interface (LGI) are considered by means of an absorptivity function of the LGI depth. This simplification and the use of adaptive mesh strategies allows the model to be computed within a reasonable time. Results and applicability of the model on the determination of the melting mode (conduction or keyhole) are displayed and compared with experimental measurements of the melt pool width and depth for 316L and Ti64 single tracks produced on a LPBF machine. Likewise, further aspects such as total absorbed power are assessed.
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