CAREER: Thermomechanical Response and Fatigue Performance of Surface Layers Engineered by Finish Machining: In-situ Characterization and Digital Process Twin

职业：精加工表面层的热机械响应和疲劳性能：原位表征和数字工艺孪生

• 批准号: 2143806
• 负责人: Julius Schoop
• 金额: $ 50.73万
• 依托单位: University of Kentucky Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143806&HistoricalAwards=false
• 关键词: CAREER; Thermomechanical; Response; Fatigue; Performance

Finish machining is a widely used process for precision component manufacture. Not only does it achieve required dimensional accuracy, finish machining also dictates the part surface integrity. The surface layer altered by machining subject to severe and localized thermal and mechanical loading and exhibit properties far different from the bulk material. Though shallow (order of 10 to 100 microns thick), it plays a critical role in part performance, especially, for dynamic loading. Furthermore, the surface material response in such finishing operations is complicated and challenging to study because of the small length scale and extreme deformation conditions. This Faculty Early Career Development (CAREER) award will pursue fundamental knowledge of the effects of finish machining on the behavior and performance of advanced metals such as titanium alloys, using a digital process twin (i.e., virtual representation of a physical process) approach to increase the quality and life of high-value components. The research outcomes have a potential to improve productivity and competitiveness of the US manufacturing industry, with a broad application potential in the aerospace, biomedical, and automotive sectors. The project team will collaborate closely with leading regional and national aerospace manufacturers to identify and address key technical requirements and workforce education needs. In addition, partnership with the Society of Women Engineers will be leveraged to recruit and train a more diverse workforce with full participation of female and underrepresented minority students.The core research objective of this CAREER project is the realization of model-based intelligent finish machining through the systematic study and modeling of finishing-specific material response to the thermomechanical loads in finish machining. Using a high-resolution novel process characterization testbed, the project team will perform advanced in-situ measurements of surface material response in finishing-specific conditions. Based on insights from in-situ characterizations from finish machining experiments, this study will evaluate semi-analytical digital process twin models by benchmarking their predictive performance and speed against established numerical approaches, such as finite element modeling. The project will also leverage high-resolution digital image correlation techniques to study strain localization effects during both finish machining itself, and crack initiation events during subsequent fatigue testing using micro-specimens extracted from machined surface layers. By modeling the process-induced structure response of finished surfaces in a faster and more reliable manner, the research effort will lay a groundwork for a more efficient development approach for finish machining processes.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.

精加工是精密零件制造中广泛使用的工艺。它不仅能达到所需的尺寸精度，精加工还能保证零件表面的完整性。通过机械加工改变的表面层受到严重的和局部的热和机械载荷，并表现出与本体材料截然不同的性质。虽然厚度较浅（约10至100微米厚），但它在零件性能中起着关键作用，特别是在动态加载时。此外，由于小的长度尺度和极端的变形条件，在这样的精加工操作中的表面材料响应是复杂的并且具有挑战性的。这个教师早期职业发展（CAREER）奖将追求精加工对先进金属（如钛合金）的行为和性能的影响的基础知识，使用数字工艺孪生（即，物理过程的虚拟表示）方法来提高高价值组件的质量和寿命。研究成果有可能提高美国制造业的生产力和竞争力，在航空航天、生物医学和汽车行业具有广泛的应用潜力。该项目团队将与领先的区域和国家航空航天制造商密切合作，以确定和解决关键的技术要求和劳动力教育需求。此外，我们还将与美国女工程师协会（Society of Women Engineers）合作，招募和培养更多女性和少数族裔学生参与的多元化人才队伍。CAREER项目的核心研究目标是通过系统研究精加工特定材料对精加工中热机械载荷的响应并建立模型，实现基于模型的智能精加工。使用高分辨率的新工艺表征测试平台，项目团队将在特定的精加工条件下对表面材料的响应进行先进的现场测量。基于精加工实验中的原位表征的见解，本研究将通过将其预测性能和速度与已建立的数值方法（如有限元建模）进行基准测试来评估半分析数字工艺孪生模型。该项目还将利用高分辨率数字图像相关技术研究精加工过程中的应变局部化效应，以及随后使用从加工表面层提取的微试样进行疲劳测试过程中的裂纹萌生事件。通过以更快、更可靠的方式模拟加工表面的过程诱导结构响应，研究工作将为更有效的精加工过程开发方法奠定基础。该奖项反映了NSF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。

项目成果

A Novel Approach for In-Situ Characterization and Probabilistic Prediction of Cutting Tool Fatigue in Machining of Ti-6Al-4V

• DOI: 10.1016/j.mfglet.2023.10.002
• 发表时间: 2023-10
• 期刊: Manufacturing Letters
• 影响因子: 3.9
• 作者: Avery Hartley;Jenna Money;J. Schoop

Physics-Informed Uncertainty Quantification in Modeling of Machining-Induced Residual Stress

机械加工残余应力建模中基于物理的不确定性量化

• DOI: 10.1016/j.procir.2023.03.025
• 发表时间: 2023
• 期刊: Procedia CIRP
• 作者: Hasan, Md Mehedi;Schoop, Julius
• 通讯作者: Schoop, Julius

A Review of Constitutive Models and Thermal Properties for Nickel-based Superalloys Across Machining-Specific Regimes

特定加工状态下镍基高温合金本构模型和热性能的综述

• DOI: 10.1115/1.4056749
• 发表时间: 2023
• 期刊: Journal of Manufacturing Science and Engineering
• 作者: Thornton, E-Lexus;Zannoun, Hamzah;Vomero, Connor;Caudill, Daniel;Schoop, Julius
• 通讯作者: Schoop, Julius

Analysis of burr formation in finish machining of nickel-based superalloy with worn tools using micro-scale in-situ techniques

• DOI: 10.1016/j.ijmachtools.2023.104030
• 发表时间: 2023-05
• 期刊: International Journal of Machine Tools and Manufacture
• 影响因子: 14
• 作者: H. Zannoun;J. Schoop