EAGER: Particle Concentration Measurements in Turbulent Flows using Magnetic Resonance Imaging

EAGER：使用磁共振成像测量湍流中的颗粒浓度

• 批准号: 1662422
• 负责人: John Eaton
• 金额: $ 9.97万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-15 至 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1662422&HistoricalAwards=false
• 关键词: EAGER; Particle; Concentration; Measurements; Turbulent

The behavior of small solid particles such as sand, dust or volcanic ash moving in water or air flows is an important consideration in a wide range of fields. For example, environmental dust can shorten a jet engine's service life by 90 percent. State-of-the-art experiments can only collect particle data in highly simplified systems. A new technique is being developed that uses conventional medical Magnetic Resonance Imaging systems to make quantitative measurements of how particles are distributed in complex systems. The data sets produced would have broad benefits for engineers, as well as for researchers studying environmental, biological, and fundamental physical systems. A series of validation experiments will be carried out to complete development of the imaging technique and to establish its accuracy and limitations. After the technique has been developed, two additional experiments will be performed to demonstrate broad societal benefits of the new measurements: one by assisting the design of more dust-resistant aircraft engines and the other by illuminating how inhaled dust or spray droplets move through the human nose. Following the successful completion of this project, researchers would have a general method to aid in their understanding of any system where particles are carried by air or water currents.Preliminary experiments have demonstrated that Magnetic Resonance Imaging can be used to measure the concentration of microparticles quantitatively and in three dimensions. The proposed work begins with a detailed set of validation experiments to test the range, resolution, and accuracy of the new experimental method across a range of flow conditions and particle concentrations. Following the validation experiments, two application-relevant test cases will be employed as test beds for continued development of the technique. The first will explore the behavior of particles in an internal impingement cooling geometry frequently employed in aircraft turbine engine cooling systems. In the second test case, particle concentration will be measured inside a model human nasal passage. In addition to developing the technique, the test cases allow for new understanding of particle transport in two disparate fields of significant research interest. The impact of the project has the potential to extend well past the scope of this proposal, as the technique could prove useful for computational model validation, fundamental particle-laden flow research, or a number of other research areas.

小的固体颗粒，如沙子，灰尘或火山灰在水流或气流中的运动行为是广泛领域的重要考虑因素。 例如，环境灰尘会使喷气发动机的使用寿命缩短90%。 最先进的实验只能在高度简化的系统中收集粒子数据。 目前正在开发一种新技术，使用传统的医学磁共振成像系统来定量测量粒子在复杂系统中的分布情况。 所产生的数据集将为工程师以及研究环境、生物和基础物理系统的研究人员带来广泛的好处。 将进行一系列验证实验，以完成成像技术的开发，并确定其准确性和局限性。 该技术开发完成后，将进行两项额外的实验，以证明新测量方法的广泛社会效益：一个是通过协助设计更防尘的飞机发动机，另一个是通过阐明吸入的灰尘或喷雾液滴如何通过人类鼻子移动。 该项目成功完成后，研究人员将有一个通用的方法来帮助他们了解任何由空气或水流携带颗粒的系统。初步实验表明，磁共振成像可以用于定量和三维测量微粒的浓度。 拟议的工作开始于一组详细的验证实验，以测试新实验方法在一系列流动条件和颗粒浓度下的范围、分辨率和准确度。 在验证实验之后，将采用两个与应用相关的测试用例作为测试床，以继续开发该技术。第一部分将探讨飞机涡轮机发动机冷却系统中经常采用的内部冲击冷却几何结构中颗粒的行为。 在第二个测试用例中，将在模型人体鼻腔通道内测量颗粒浓度。 除了开发技术，测试案例允许在两个不同的领域的重大研究兴趣的粒子传输的新的理解。 该项目的影响有可能远远超出本提案的范围，因为该技术可能被证明对计算模型验证、基本粒子流研究或其他一些研究领域有用。

项目成果

Development and validation of an MRI-based method for 3D particle concentration measurement

• DOI: 10.1016/j.ijheatfluidflow.2018.04.006
• 发表时间: 2018-06-01
• 期刊: INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
• 影响因子: 2.6
• 作者: Borup, Daniel D.;Elkins, Christopher J.;Eaton, John K.
• 通讯作者: Eaton, John K.

Experimental Analysis of a Particle Separator Design with Full-Field Measurements

全场测量颗粒分离器设计的实验分析

• 发表时间: 2019
• 期刊: ASME IGTI Turbo Expo 2019
• 作者: Borup, D.;Elkins, C.;Eaton, J.
• 通讯作者: Eaton, J.