SIM-AM 2023

Numerical model for the laser metal deposition additive manufacturing process: Multiphysics modeling and experimental validation

  • DALI, Ghassen (UTC - Roberval)

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Metallic Additive Manufacturing (AdM) technologies (3D printing) is rapidly advancing into various industrial applications. In more recent years, advances in AdM have progressively transformed the ways in which end-use parts are designed, manufactured, and distributed. It enables direct manufacturing of parts with complex shape geometries with high strength, less material waste and less production steps. Laser Metal Deposition (LMD) is one of the processes in this growing field. It is based on the injection of powders into a melt-pool created in the part being manufactured by a laser source. However, LMD process is complex, and several defects could happen during part printing. Numerical simulation is a helpful tool to predict the geometry of the molten, including defects, and to optimize process. In this work, a multi-physics numerical model of the LMD process at a mesoscopic scale (i.e. layer thickness scale) is developed to predict thermal conditions during manufacturing, as well as the complex relations between the material deposition and the operating parameters. The model is based on a finite element (FE) analysis workflow using the commercial software COMSOL Multiphysics. Fluid flow and heat transfer are taken into account in all domains (gas, substrate and melt pool). As a new feature, the developed model simulates the track growth using droplet generation when the powder stream is intercepted by the laser beam. The material addition, the interface tracking and the strong topological changes are handled with the help of the level set technique. The numerical results are compared to the experimental results for validation purposes. These comparisons include a cross-section of predicted melt pool dimensions and track geometry against experimental data from macrographs and high-speed videos. Then, the developed model is used to optimize operating parameters.