In the Air Force Research Laboratory Additive Manufacturing Challenge Series, melted track geometries for a laser powder bed fusion (L-PBF) process of Inconel 625 were used to challenge and validate computational models predicting melting and solidification behavior. The impact of process parameters upon single-track single-layer, multi-track single-layer, and single-track multi-layer L-PBF processes was studied. To accomplish this, a physics-based thermal-fluid model was developed and calibrated using a proper generalized decomposition surrogate model, then compared against the experimental measurements. The thermal-fluid model was enhanced through the usage of an adaptive mesh and residual heat factor (RHF) model, based on the scanning strategy, for improved efficiency and accuracy. It is found that this calibration approach is not only robust and efficient, but it also enables the thermal-fluid model to make predictions which quantitatively agree well with the experimental measurements. The adaptive mesh provides over a 10-times speedup as compared to a uniform mesh. The RHF model improves predictive accuracy by over 60%, particularly near starting and ending points of the melted tracks, which are greatly affected by the thermal behavior of adjacent tracks. Moreover, the thermal-fluid model is shown to potentially predict lack-of-fusion defects and provide insights into the defect generation process in L-PBF.

在空军研究实验室增材制造挑战系列中，Inconel 625的激光粉末床熔合（L-PBF）工艺的熔融轨道几何形状用于挑战和验证预测熔融和凝固行为的计算模型。研究了工艺参数对单道单层，多道单层和单道多层L-PBF工艺的影响。为此，开发了基于物理的热流体模型，并使用适当的广义分解替代模型进行了校准，然后将其与实验测量值进行了比较。通过基于扫描策略的自适应网格和残余热因子（RHF）模型的使用，增强了热流体模型，从而提高了效率和准确性。发现该校准方法不仅鲁棒且有效，而且还使热流体模型能够做出与实验测量在数量上非常吻合的预测。与均匀网格相比，自适应网格可提供10倍以上的加速。RHF模型将预测精度提高了60％以上，尤其是在熔化轨迹的起点和终点附近，这受相邻轨迹的热行为的影响很大。此外，热流体模型显示出可以潜在地预测融合不足的缺陷，并提供对L-PBF中缺陷生成过程的洞察力。与均匀网格相比，自适应网格可提供10倍以上的加速。RHF模型将预测精度提高了60％以上，尤其是在熔化轨迹的起点和终点附近，这受相邻轨迹的热行为的影响很大。此外，热流体模型显示出可以潜在地预测融合不足的缺陷，并提供对L-PBF中缺陷生成过程的洞察力。与均匀网格相比，自适应网格可提供10倍以上的加速。RHF模型将预测精度提高了60％以上，尤其是在熔化轨迹的起点和终点附近，这受相邻轨迹的热行为的影响很大。此外，热流体模型显示出可以潜在地预测融合不足的缺陷，并提供对L-PBF中缺陷生成过程的洞察力。