MULTI-PHYSICS MODELING OF CONTINUOUS AND PULSED LASERS: IMPACT ON THERMAL HISTORY AND SURFACE PROPERTIES IN POWDER BED FUSION ADDITIVE MANUFACTURING

Metal additive manufacturing (MAM) processes have revolutionized manufacturing and design, offering unprecedented freedom to create intricate and complex parts.Research has demonstrated that in laser powder bed fusion (LPBF) of metal additive manufactured parts, the microstructure and surface can be influenced by various process parameters.However, the influence of laser pulse parameters in LPBF remains relatively unexplored.Laser pulse parameters significantly affect the microstructure and melt pool evolution in metal powder bed additive manufacturing processes.Control over these variations is crucial for achieving desired material properties and part quality.Adjustments in pulse parameters, such as power, width, and interval, can alter grain size, orientation, and subcellular structure, thus impacting mechanical properties.Moreover, optimizing laser energy density by controlling pulse parameters can mitigate defect formation, enhancing density and mechanical properties.Hence, exploring precise control over pulse width and interval during manufacturing contributes significantly to achieving high-quality components.In this study, a meso-scale numerical model was employed to investigate the influence of pulse parameters, such as pulse width and interval on the thermal history and melt pool evolution in LPBF.The physics-based model incorporates key phenomena such as heat transfer via radiation & convection, phase change, recoil pressure, and density-driven melt pool flow.These physical phenomena play a crucial role in the surface finish and microstructure of fabricated parts, affecting the formation of defects such as balling, keyhole, and spattering.A discrete element model (DEM) was employed to construct the powder bed, while the finite volume method (FVM) simulated the thermal-fluid behavior using an initial condition derived from an STL file.Validation of the numerical model against existing literature has confirmed its capacity to accurately predict melt pool behavior, including its influence on surface roughness, as well as temperature distribution and cooling rates across different laser source pulse width and interval settings.Additionally, it can also pave the way for future research directions, including the exploration of in situ hybrid processes involving multiple lasers for surface processing and enhancement.The evolution of computational models promises to facilitate more sophisticated control strategies, ultimately enhancing outcomes and efficiency in metal additive manufacturing processes, paving the way for tailored and optimized LPBF MAM parts.