Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing
Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing
复制标题
用于金属增材制造的时间连续热流-热机械建模框架
DOI：
10.1016/j.ijmecsci.2023.108424
复制
发表时间：
2023
影响因子：
7.3
通讯作者：
Malik, Arif
中科院分区：
文献类型：
--
作者：
Mathews, Ritin;Nagaraja, Kishore Mysore;Zhang, Runyu;Sunny, Sumair;Yu, Haoliang;Marais, Deon;Venter, Andrew;Li, Wei;Lu, Hongbing;Malik, Arif
已知增材制造（AM）由于陡峭和局部的热梯度而在构造内产生大幅度的残余应力（RS）。在目前的商业AM技术状态下，制造商通常进行热处理，以努力减少所产生的RS及其对零件变形和使用中故障的不利影响。有效模拟沉积过程的计算模型可以为改善RS分布提供有价值的见解。因此，通常采用计算流体动力学（CFD）模型或有限元（FE）模型。虽然CFD可以预测几何和热流体行为，但它不能预测结构响应（例如，应力-应变）行为。另一方面，有限元模型可以预测力学行为，但它缺乏预测几何和流体行为的能力。因此，一个有效集成的热流体热机械建模框架，利用这两种技术的好处，同时避免各自的局限性，可以提供有价值的预测能力AM过程。与以前发表的努力相比，本文的工作描述了一种单向耦合CFD-FEA框架，该框架放弃了主要的简化假设，例如几何稳态条件，材料塑性的缺乏，以及沉积过程中缺乏详细的RS演变/积累，以及结果的验证不足。所提出的框架被证明为定向能量沉积（DED）过程，并进行实验来验证预测的几何形状和RS轮廓。单层和双层不锈钢316L构建均被考虑。通过3D光学表面扫描和X射线显微计算机断层扫描获得几何数据，并使用中子衍射（ND）测量残余应力。模拟和测量之间的比较表明，所描述的CFD有限元分析框架是有效的捕捉耦合的热机械和热流体行为的DED过程。所提出的方法可扩展到其他金属AM工艺，包括动力床融合和基于送丝的AM。
Additive manufacturing (AM) is known to generate large magnitudes of residual stresses (RS) within builds due to steep and localized thermal gradients. In the current state of commercial AM technology, manufacturers generally perform heat treatments in effort to reduce the generated RS and its detrimental effects on part distortion and in-service failure. Computational models that effectively simulate the deposition process can provide valuable insights to improve RS distributions. Accordingly, it is common to employ Computational fluid dynamics (CFD) models or finite element (FE) models. While CFD can predict geometric and thermal-fluid behavior, it cannot predict the structural response (e.g., stress–strain) behavior. On the other hand, an FE model can predict mechanical behavior, but it lacks the ability to predict geometric and fluid behavior. Thus, an effectively integrated thermofluidic–thermomechanical modeling framework that exploits the benefits of both techniques while avoiding their respective limitations can offer valuable predictive capability for AM processes. In contrast to previously published efforts, the work herein describes a one-way coupled CFD-FEA framework that abandons major simplifying assumptions, such as geometric steady-state conditions, the absence of material plasticity, and the lack of detailed RS evolution/accumulation during deposition, as well as insufficient validation of results. The presented framework is demonstrated for a directed energy deposition (DED) process, and experiments are performed to validate the predicted geometry and RS profile. Both single- and double-layer stainless steel 316L builds are considered. Geometric data is acquired via 3D optical surface scans and X-ray micro-computed tomography, and residual stress is measured using neutron diffraction (ND). Comparisons between the simulations and measurements reveal that the described CFD-FEA framework is effective in capturing the coupled thermomechanical and thermofluidic behaviors of the DED process. The methodology presented is extensible to other metal AM processes, including power bed fusion and wire-feed-based AM.