Understanding Mist Flow Dynamics in Through-tool Minimum Quantity Lubrication Drilling

了解通过工具微量润滑钻井中的雾流动力学

• 批准号: 1760985
• 负责人: Li-Jung Tai
• 金额: $ 31.97万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1760985&HistoricalAwards=false
• 关键词: Understanding; Mist; Flow; Dynamics; Through

This award develops knowledge required to design cutting tools and select flow parameters for minimum quantity lubrication (MQL) machining. MQL is known for its advantages of significant reduction in water waste, energy use, and overall costs as compared to traditional wet processes. This research project will investigate the science behind MQL machining and rapidly implement the results into production-level operations through the collaboration with Ford Motor Company. Since the project has broad applicability to automotive, aerospace, electronics and defense industries, it directly and positively impacts American economic welfare and national security. Additionally, the project includes plans for hands-on training and research experience on advanced machining processes for undergraduate students via course integration, summer internship, and Research Experience for Undergraduates (REU) programs. By leveraging an on-going Research Experience for Teachers (RET) program at Texas A&M, this project also includes outreach activities to high schools on design of modern cutting tools to promote STEM field. The close collaboration with the industrial partner also provides a unique environment to align these plans with the needs in the manufacturing industry.This research incorporates experimental and numerical approaches that address the fundamental science of minimum quantity lubrication. Drilling is the target process as it is common in manufacturing, whereas drilling is complex and cannot be observed visually. The project has three main objectives: Objective 1 characterizes the flow out of internal channels based on geometrical, system, and machining parameters. An MQL flow testbed will be used to emulate the mist flow in machining and allow visual access to the cutting zone with a high-speed camera. Objective 2 addresses interactions between flow structure and drill-workpiece motion and thus will predict the fluid coverage on the tool edges and faces. The flow test results will be compared with computational fluid dynamics (CFD) using both single- and dual-phase flow analyses. Objective 3 will determine the effects of mist flow on drilling performance, including torque, thrust force, built-up edge, and wear, on production systems at the Ford AME MQL laboratory. The knowledge generated will enable MQL-specific tool design and selection, adaptive MQL systems, and process development. The broader impacts include improved MQL implementation in the manufacturing industry and collaborative activities between the industry and academia for the workforce development.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.

该奖项开发了设计切削刀具和选择最小量润滑（MQL）加工的流量参数所需的知识。与传统湿法工艺相比，MQL以其显著减少水浪费、能源使用和总成本的优势而闻名。该研究项目将调查MQL加工背后的科学，并通过与福特汽车公司的合作，将结果迅速实施到生产级操作中。由于该项目广泛适用于汽车、航空航天、电子和国防工业，因此对美国的经济福祉和国家安全产生直接而积极的影响。此外，该项目还包括通过课程整合，暑期实习和本科生研究经验（REU）计划为本科生提供先进加工工艺的实践培训和研究经验的计划。通过利用德克萨斯州A M正在进行的教师研究经验（RET）计划，该项目还包括对高中进行现代切割工具设计的推广活动，以促进STEM领域。与工业合作伙伴的密切合作也提供了一个独特的环境，使这些计划与制造业的需求保持一致。这项研究结合了实验和数值方法，解决了最小量润滑的基础科学。钻孔是目标工艺，因为它在制造中很常见，而钻孔很复杂，无法目视观察。该项目有三个主要目标：目标1根据几何、系统和加工参数描述内部通道的流出特性。MQL流量试验台将用于模拟加工中的雾流，并允许通过高速摄像机对切割区域进行视觉访问。目标2解决了流动结构和钻头-工件运动之间的相互作用，因此将预测工具边缘和表面上的流体覆盖。将使用单相和双相流动分析将流动测试结果与计算流体动力学（CFD）进行比较。 目标3将在福特AME MQL实验室的生产系统上确定雾流对钻井性能的影响，包括扭矩、推力、积屑和磨损。生成的知识将使特定于MQL的工具设计和选择，自适应MQL系统和过程开发成为可能。更广泛的影响包括改进制造业的MQL实施以及工业界和学术界之间的劳动力发展合作活动。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

An optical tomographic method to characterize the mist distribution in MQL Tools

• DOI: 10.1016/j.jmapro.2020.12.025
• 发表时间: 2021-02
• 期刊: Journal of Manufacturing Processes
• 影响因子: 6.2
• 作者: J. Raval;Bruce L. Tai

Characterization and Performance of Minimum Quantity Lubricants in Through-Tool Drilling

• DOI: 10.26776/ijemm.05.04.2020.01
• 发表时间: 2020-10
• 作者: A. Patil;J. Raval;T. Bangma;I. Edinbarough;Bruce L. Tai;David Stephenseon;Obeidat Suleiman;Wayne Hung

Effect of Oil Flow Rate on Production Through-Tool Dual Channel MQL Drilling

石油流量对双通道 MQL 钻井生产的影响

• DOI: 10.1115/msec2020-8375
• 发表时间: 2021
• 期刊: ASME 2020 15th International Manufacturing Science and Engineering Conference
• 作者: Raval, Jay K.;Stephenson, David A.;Tai, Bruce L.
• 通讯作者: Tai, Bruce L.

Multiphase flow distribution in mql drilling using optical intensity distribution based approach

使用基于光强度分布的方法在 MQL 钻井中进行多相流分布

• 发表时间: 2019
• 期刊: Manufacturing science and engineering
• 作者: Raval, Jay;Hung, Wayne NP;Tai, Bruce L.
• 通讯作者: Tai, Bruce L.

Mist Flow in Through-Tool Minimum Quantity Lubrication Drilling: Two-Phase Flow Simulation and Experimental Observation

通过工具微量润滑钻井中的雾流：两相流模拟和实验观察

• DOI: 10.1115/1.4056146
• 发表时间: 2023
• 期刊: Journal of Manufacturing Science and Engineering
• 作者: Raval, Jay K.;Tai, Bruce L.
• 通讯作者: Tai, Bruce L.