Process-induced defects are the leading cause of discrepancies between as-designed and as-manufactured additive manufacturing (AM) product behavior. Especially for metal lattices, the variations in the printed geometry cannot be neglected. Therefore, the evaluation of the influence of microstructural variability on their mechanical behavior is crucial for the quality assessment of the produced structures. Commonly, the as-manufactured geometry can be obtained by computed tomography (CT). However, to incorporate all process-induced defects into the numerical analysis is often computationally demanding. Thus, commonly this task is limited to a predefined set of considered variations, such as strut size or strut diameter. In this work, a CT-based binary random field is proposed to generate statistically equivalent geometries of periodic metal lattices. The proposed random field model in combination with the Finite Cell Method (FCM), an immersed boundary method, allows to efficiently evaluate the influence of the underlying microstructure on the variability of the mechanical behavior of AM products. Numerical analysis of two lattices manufactured at different scales shows an excellent agreement with experimental data. Furthermore, it provides a unique insight into the effects of the process on the occurring geometrical variations and final mechanical behavior.
翻译:工艺诱发的缺陷是设计成的和制造成的添加剂(AM)产品行为之间差异的主要原因。特别是对于金属层,印刷几何的变异是不可忽视的。因此,对微结构变异对其机械行为的影响的评估对于质量评估所生产的结构结构至关重要。通常,制造成的几何可以通过计算透视法(CT)获得。然而,将所有过程变异的变异纳入数字分析往往具有计算上的要求。因此,这项任务通常限于一套预先界定的考虑的变异,例如结构大小或结构直径。在这项工作中,建议采用基于CT的二进制随机字段来生成定期金属层的等同统计的地理特征。拟议的随机场模型与精密细胞方法(FCM)相结合,可以有效地评估基微结构对AM产品的机械变异性的影响。对不同规模制造的两种变异性进行了定量分析,对不同比例的两次变异性进行了数值分析,从而得出了极佳的精确的实验性数据。