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<p>Selective laser melting is widely used to manufacture near-net-shape and good surface quality parts, which is prominent in fabricating metal matrix composites for better performance. However, precise observation of the molten pool morphology and particle distribution remains unachievable, resulting in difficulty in the control of the surface roughness of the parts. In this paper, NbC/316L stainless steel was prepared to improve mechanical properties as well as resistance. A mesoscopic-scale numerical model based on CFD-DEM is established to predict molten pool dynamics and surface evolution of the particle-reinforced metal matrix composite, considering Marangoni convection, surface tension, and recoil pressure. The simulated results indicated that the fluid backflow phenomena within the molten pool under high laser power (300 W) and low hatch space (70&#xa0;μm) were more pronounced, which persisted for a longer duration, as shown in the speed differences between the fluid flow and scanning laser at the front end of the molten pool. An additive model was proposed to establish the relationship between the ratio of effective volume to additive volume (E/A) and roughness (Sa), and it showed a reasonable fit with the experimental results. It is found that when the E/A rate of the molten pool approaches 1, the remelting rate in the Z direction approaches 0.13 while the filling efficiency of the molten pool is high, which yields low surface roughness (Sa) of the material. Especially when <i>P</i> = 250 W, V = 440&#xa0;mm/s, and H = 110&#xa0;μm, the Sa is as low as 18&#xa0;μm.</p>

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Influence Factors and Prediction Model of Surface Evolution Based on Computational Fluid Dynamics-Discrete Element Method for Selective Laser Melting NbC/316L Stainless Steel Composite

  • 期刊论文

  • 发表日期：

    2026年2月24日

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  • L. Liu,
  • K. Yang,
  • F. Y. Lin,
  • S. W. Yang,
  • Yanni Ma

摘要

Selective laser melting is widely used to manufacture near-net-shape and good surface quality parts, which is prominent in fabricating metal matrix composites for better performance. However, precise observation of the molten pool morphology and particle distribution remains unachievable, resulting in difficulty in the control of the surface roughness of the parts. In this paper, NbC/316L stainless steel was prepared to improve mechanical properties as well as resistance. A mesoscopic-scale numerical model based on CFD-DEM is established to predict molten pool dynamics and surface evolution of the particle-reinforced metal matrix composite, considering Marangoni convection, surface tension, and recoil pressure. The simulated results indicated that the fluid backflow phenomena within the molten pool under high laser power (300 W) and low hatch space (70 μm) were more pronounced, which persisted for a longer duration, as shown in the speed differences between the fluid flow and scanning laser at the front end of the molten pool. An additive model was proposed to establish the relationship between the ratio of effective volume to additive volume (E/A) and roughness (Sa), and it showed a reasonable fit with the experimental results. It is found that when the E/A rate of the molten pool approaches 1, the remelting rate in the Z direction approaches 0.13 while the filling efficiency of the molten pool is high, which yields low surface roughness (Sa) of the material. Especially when P = 250 W, V = 440 mm/s, and H = 110 μm, the Sa is as low as 18 μm.