The laser powder bed fusion (LPBF) process involves using a laser beam to selectively melt metal powder with a desired shape on a substrate to create a part layer-by-layer. As an Additive Manufacturing (AM) process, laser powder bed fusion (commonly referred to as selective laser melting—SLM) offers superior design freedom over conventional manufacturing methods and enables the production of complex, lightweight geometries with applications in the aerospace, automotive, and biomedical industries. In addition to enhanced design freedom, AM technologies provide improved material utilization and allow for reduced assembly needs. However, the reliability and repeatability of additively manufactured parts is a challenge to the wide-scale adoption of the technology for safety critical parts. A critical limitation of process optimization is the prediction and control of residual stresses, distortion, and microstructure evolution. This work focuses on the development and implementation of a numerical modeling technique for the prediction of residual strains within an Inconel 625 LPBF part. The model, using the SIMULIA Additive Manufacturing Scenario App, based on the Abaqus 2018 finite element solver, was developed and analyzed as part of a submission for the NIST AM Benchmark 2018. A sequentially coupled thermo-mechanical analysis was adopted to replicate the building conditions of a single cantilever beam built at the NIST laboratories. The results of the blind study were compared to X-ray diffraction (XRD) measurements of the physical build. The predicted three-dimensional residual strain field showed a high level of accuracy and the submission described in this paper received joint first prize in the residual elastic strain category of the NIST AM Benchmark 2018. The results presented in this paper reflect only findings before the benchmark measurements were posted on the NIST website.

中文翻译：

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粉末床熔融Inconel 625单悬臂零件的残余应变预测

激光粉末床熔化（LPBF）工艺涉及使用激光束在基板上选择性地熔化具有所需形状的金属粉末，以逐层生成零件。作为增材制造（AM）工艺，激光粉末床熔合（通常称为选择性激光熔化-SLM）提供了优于传统制造方法的卓越设计自由度，并能够生产复杂，轻巧的几何形状，并应用于航空航天，汽车和汽车制造业。生物医学产业。除了提高设计自由度之外，增材制造技术还提高了材料利用率，并减少了组装需求。但是，增材制造零件的可靠性和可重复性对安全关键零件技术的广泛采用提出了挑战。工艺优化的一个关键限制是残余应力，变形和微结构演变的预测和控制。这项工作专注于数值建模技术的开发和实现，以预测Inconel 625 LPBF零件内的残余应变。该模型使用基于Abaqus 2018有限元求解器的SIMULIA Additive Manufacturing Scenario App开发并进行了分析，作为NIST AM Benchmark 2018提交的一部分。采用了顺序耦合的热机械分析来复制建筑条件NIST实验室制造的单个悬臂梁。将盲法研究的结果与物理结构的X射线衍射（XRD）测量结果进行了比较。