Collaborative Research: Pore Formation Mechanisms in Laser Powder-Bed Fusion Additive Manufacturing: Particle-Resolved Modeling and Fundamental Experimentation

加法制造(AM)创造了一种集成材料、设计和制造创新的新范式，可在广泛的行业中有效地进行产品开发和实现。金属AM技术，如使用粉床和高功率激光的选择性激光熔化(SLM)，在制造复杂几何形状的高性能部件方面尤其有利，而不会产生模具成本，使早期采用者在全球市场上具有竞争优势。阻碍金属AM技术在工业上有效实施的关键挑战之一是零件质量的不一致性，而AM零件中的孔洞对其影响很大。气孔的大小在一到一百微米之间，是在加工过程中产生的内部缺陷，会导致零件性能的巨大变化。金属AM中的气孔形成是复杂的，而且还不完全了解，因此很难预测质量控制。该奖项证实了金属AM零件中气孔问题的基础研究需要。该项目解决了SLM中大量微观金属颗粒的加热、熔化和凝固的多尺度和多物理耦合过程的原创性研究。研究结果不仅将建立工艺参数、材料性能和气孔属性之间的关联，还可能导致减少气孔缺陷的新技术，从而有可能加速金属AM在美国工业中的应用。此外，该项目将为满足金属AM工业需求的劳动力培训做出贡献，并吸引高中生学习先进制造技术。本研究的目的是区分SLM的气孔形成机制，并从理论上预测、分析和实验表征SLM零件的孔隙率。在路易斯维尔大学(UofL)和阿拉巴马大学(UA)的这项合作研究中，将开发一种混合数值模拟技术，用于粒子分辨模拟，能够捕捉SLM中不同的气孔形成机制。该模型将通过小型样品制作的SLM实验进行验证，其中包括用于测量过程温度和熔池动力学的红外热成像仪。制作的试件将使用微尺度X射线计算机层析成像进行测量和分析，以获得详细的孔隙率属性的统计数据，并与数值模拟的结果进行比较。研究工作将扩展到研究工艺参数与SLM中孔隙率的形态和分布之间的关系，以及估计将气孔缺陷降至最低的工艺窗口。如果成功，这项研究将提炼出一种复杂的多物理现象的知识，并将提供重要的见解，详细说明不同孔隙形成的特定机制的关键。研究结果将包括在路易斯维尔大学校区添加剂制造能力中心的培训材料中，使SLM技术从业者更好地了解工艺参数、气孔形成和关键AM制造部件的机械性能之间的关系。

Additive manufacturing (AM) has created a new paradigm of integrated materials, design and manufacturing innovations for effective product development and realization across a broad range of industries. Metal AM technologies such as selective laser melting (SLM), which uses a powder-bed and a high power laser, are especially beneficial in making complex-geometry, high-performance components without incurring tooling costs, giving early adopters a competitive advantage in the global market. One of the key challenges that hinder efficient metal AM technology implementation in industry is part quality inconsistency that is significantly affected by porosity in AM parts. Pores, with sizes of one to one hundred microns, are internal defects generated during the process and that cause large variations in part performance. Pore formation in metal AM is complex and not fully understood, making it difficult to predict for quality control. This award corroborates basic research needs of the porosity issue in metal AM parts. The project tackles original research on the coupled multi-scale and multi-physics process of heating, melting and solidification of numerous microscopic metallic particles in SLM. Research findings will not only establish correlations between the process parameters, material properties and pore attributes, but may also lead to novel techniques for mitigating pore defects, and thus, have a potential to accelerate metal AM adoption in U.S. industry. In addition, this project will contribute toward workforce training for metal AM industrial needs and attract high school students into advanced manufacturing technologies. The objectives of this research are to distinguish pore formation mechanisms in SLM and to theoretically predict, analyze and experimentally characterize the porosity in SLM parts. In this collaborative research between the University of Louisville (UofL) and the University of Alabama (UA), a hybrid numerical modeling technique will be developed for particle-resolved simulations capable of capturing different pore formation mechanisms in SLM. The model will be validated by SLM experiments of small-scale specimen fabrications, incorporating an infrared thermal imager for process temperature and melt-pool dynamics. The fabricated specimens will be measured using micro-scale x-ray computed-tomography and analyzed to attain statistical data of detailed porosity attributes for comparison with the results from numerical modeling. The research efforts will be extended to study the relationship between process parameters and morphology and distribution of porosity in SLM, and to estimate process windows that minimize pore defects. If successful, this study will distill knowledge of a convoluted multi-physics phenomenon and will offer significant insight detailing the key to particular mechanisms of different pore formations. The research results will be included in the training materials for the Additive Manufacturing Competency Center on the University of Louisville campus, providing practitioners of the SLM technology with better understanding of the relationship between processing parameters, porosity formation, and mechanical properties of critical AM-fabricated components.