Metal additive manufacturing (AM) while offering advantages such as generating parts with intricate geometries, introduces challenges such as intrinsic defects. Since fatigue cracks often start at defects, developing analytical methods to predict fatigue failure is necessary for critical AM applications involving cyclic loadings. In this work a computational framework is presented where a generalized Paris equation and the Hartman-Schijve variant of NASGRO equation are used to predict the fatigue life of L-PBF Ti-6Al-4V and 17-4 PH stainless steel specimens. A variety of conditions resulting in different failure modes and defect sized were considered, including annealed and HIPed treatments as well as as-built and machined surface conditions. In contrast to the commonly assumed mode I crack growth in the literature, in this work the appropriate crack growth mode based on the observed failure mechanism is used for fatigue life predictions. By using Extreme Value Statistics (EVS) and equivalent defect size based on Murakami’s method for approximation of the initial defect size, and appropriate crack growth equation and properties, good correlations between experimental results and prediction curves are demonstrated.

金属增材制造（AM）在提供诸如生成具有复杂几何形状的零件等优点的同时，也带来了诸如固有缺陷之类的挑战。由于疲劳裂纹通常始于缺陷，因此对于涉及循环载荷的关键AM应用，必须开发预测疲劳失效的分析方法。在这项工作中，提出了一个计算框架，其中使用广义的巴黎方程和NASGRO方程的Hartman-Schijve变体来预测L-PBF Ti-6Al-4V和17-4 PH不锈钢试样的疲劳寿命。考虑了导致不同失效模式和缺陷尺寸的各种条件，包括退火和HIP处理以及实际和机械加工的表面条件。与通常认为的模式I打破了文献中的增长方式相反，在这项工作中，基于观察到的破坏机理的适当裂纹扩展模式被用于疲劳寿命预测。通过使用基于村上方法的极值统计（EVS）和等效缺陷尺寸来近似初始缺陷尺寸，适当的裂纹扩展方程和性能，证明了实验结果与预测曲线之间的良好相关性。