Collaborative Research: Hybrid-Compatible Deformation Processing of Performance Critical Components

增材制造已成为制造复杂机械部件的可行途径，在航空航天、国防、汽车和能源领域具有重要应用。不幸的是，由于内部缺陷，通过增材制造制造的机器部件往往不可靠。这就禁止了它们的工业用途，因为有缺陷的部件可能以意想不到的方式响应正常的服务条件或过早失效。该奖项支持建立一种新型混合增材制造无缺陷部件的方法，因此直接影响经济福利和国家安全。这种混合方法将利用局部剧烈变形修复缺陷。支持这项研究的建模工作将使高质量的增材制造组件的快速制造成为可能。该项目还将支持一些课堂教学计划，包括那些专注于K-12、本科和研究生水平的计划。这些措施包括(i)将研究成果纳入交互式教育电脑游戏和（ii）通过可在开放的社交媒体平台上观看的视频短片传播。该项目的目标是通过混合后处理方法促进增材制造部件的缺陷控制。为了实现这一目标，该方法将涉及在增材制造过程中系统地使用相互交织的步骤中的塑性变形，以减轻体积缺陷。建模工作将涉及梯度塑性应变下材料微观结构演变的详细表征。感兴趣的显微组织参数包括晶粒组织和缺陷组织。这些参数的变形响应将使用就地加载平台进行研究，该平台将与现有的电子显微镜和x射线计算机断层扫描仪一起工作。变形应变场将通过二次电子成像使用数字图像相关来表征。这些应变场将与不断变化的微观结构参数相关联，这些参数将同时被表征。将验证用于预测表面微观结构作为加工条件函数的过程建模框架，并用于确定后处理增材制造微结构的最佳混合策略。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Additive manufacturing has emerged as a viable route for fabricating complex machine components that have important applications in the aerospace, defense, automotive and energy sectors. Unfortunately, machine components made through additive manufacturing are often unreliable due to internal defects. This prohibits their industrial use as defective components can respond to normal service conditions in unexpected ways or fail prematurely. This award supports research to establish a novel hybrid-additive method for fabrication of defect-free components, and therefore directly impacts economic welfare and national security. This hybrid approach will repair defects using local severe deformation. Modeling efforts that will support this research will enable rapid fabrication of high quality additively manufactured components. The project will also support several classroom teaching initiatives including those focused at the K-12, undergraduate and graduate levels. These include (i) incorporation of research results into an interactive educational computer game and (ii) dissemination through short video-scribe movies available for viewing in open social media platforms. The goal of this project is to facilitate defect control in additively manufactured components through hybrid post-processing methods. For achieving this goal, the methodology will involve systematic use of plastic deformation in interwoven steps during additive manufacturing for mitigation of volumetric defects. Modeling efforts will involve detailed characterization of material microstructure evolution under graded plastic strain. Microstructure parameters of interest include grain structure and defect structure. The deformation response of these parameters will be studied using in situ loading platforms that will work with existing electron microscopes and X-Ray computed tomography machines. Deformation strain fields will be characterized using digital image correlation through secondary electron imaging. These strain fields will be correlated with the evolving micro-structure parameters that will be characterized simultaneously. A process modeling framework for prediction of the surface microstructure as a function of processing conditions will be validated and used to determine optimal hybrid strategies for post processing additively manufactured microstructures.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.