A critical issue in laser powder bed fusion (LPBF) additive manufacturing is the selective vaporization of alloying elements resulting in poor mechanical properties and corrosion resistance of parts. The process also alters the part’s chemical composition compared to the feedstock. Here we present a novel multi-physics modeling framework, integrating heat and fluid flow simulations, thermodynamic calculations, and evaporation modeling to estimate and control the composition change during LPBF of nickel-based superalloys. Experimental validation confirms the accuracy of our model. Moreover, we quantify the relative vulnerabilities of different nickel-based superalloys to composition change quantitatively and we examine the effect of remelting due to the layer-by-layer deposition during the LPBF process. Spatial variations in evaporative flux and compositions for each element were determined, providing valuable insights into the LPBF process and product attributes. The results of this study can be used to optimize the LPBF process parameters such as laser power, scanning speed, and powder layer thickness to ensure the production of high-quality components with desired chemical compositions.

激光粉末床熔合 (LPBF) 增材制造的一个关键问题是合金元素的选择性汽化，导致零件的机械性能和耐腐蚀性较差。与原料相比，该过程还改变了零件的化学成分。在这里，我们提出了一种新颖的多物理场建模框架，集成了热量和流体流动模拟、热力学计算和蒸发建模，以估计和控制镍基高温合金LPBF期间的成分变化。实验验证证实了我们模型的准确性。此外，我们定量量化了不同镍基高温合金对成分变化的相对脆弱性，并研究了 LPBF 过程中逐层沉积造成的重熔影响。确定了每种元素的蒸发通量和成分的空间变化，为 LPBF 工艺和产品属性提供了宝贵的见解。这项研究的结果可用于优化 LPBF 工艺参数，例如激光功率、扫描速度和粉末层厚度，以确保生产具有所需化学成分的高质量部件。