Applying numerical modeling to experimental data for improved optical diagnostics of fluid flows

将数值模型应用于实验数据以改进流体流动的光学诊断

• 批准号: RGPIN-2018-04675
• 负责人: Nobes, David
• 金额: $ 2.33万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=660999
• 关键词: Applying; numerical; modeling; experimental; data

Experimental research into the motion of fluid in academic and industrial applications is now dominated by digital techniques. Cameras are used to take images of tracer particles seeded into the flow to track their movement, inferring the motion of the fluid. This technology has been developed over the last 30 years to a point where it is now compatible with even the most detailed numerical simulations. Importantly, these experimental techniques include all of the physics of the flow problem. They are therefore used as direct validation of the numerical approaches as well as a tool in academia and industry to investigate a wide variety of flows. A large family of these techniques now exist based on particle image velocimetry (PIV) and particle tracking velocimetry (PTV). These multi-camera systems have many challenges in the setup, the collection of data and the processing through to descriptive velocity fields.****A new approach to collect images of particle locations over three dimensions (3D) from a single camera is based on collecting the entire light field seen by the camera. Termed plenoptic imaging, the camera has a microlens array that allows small angle perspective viewing of particle locations. This type of imaging system, using only a single camera, promises to be significantly easier to install and setup in a flow system, especially where viewing access is limited. It also allows, for the first time, realistic measurement of three-dimensional flows at the microscale such as the flow in porous media and microscale biological flows. This project will continue to develop this type of camera system for experimental use by developing a general calibration procedure, data collection and processing and advanced approaches based on PTV and numerical models of particle motion to provide high-quality flow measurement.****With any particle imaging velocimetry technique, an appropriate methodology is needed to determine the uncertainty in the derived velocity vector. As yet, no generalised method for determining the uncertainty in a PIV or PTV measurement is available due to the complex interaction of the experimental setup and the computational processing of the data collected. This is a significant fundamental problem that has a strong impact across the experimental thermo-fluid community, both in academia and industry. A significant part of this project will be the development of a generalised methodology for determining the uncertainty in all of these types of particle image velocity measurement systems.****This project will train HQP in the areas of optical instrumentation and fluid mechanics developing new knowledge and science. Impact will be felt in both academia and industry where these techniques are unitized.******

在学术和工业应用中对流体运动的实验研究现在由数字技术主导。摄像机用来拍摄注入流体的示踪粒子的图像，以跟踪它们的运动，推断流体的运动。在过去的30年里，这项技术已经发展到现在甚至可以与最详细的数值模拟兼容。重要的是，这些实验技术包括所有的流动问题的物理。因此，它们被用作数值方法的直接验证，以及学术界和工业界研究各种流动的工具。基于粒子图像测速技术（PIV）和粒子跟踪测速技术（PTV），目前已有大量的此类技术。这些多相机系统在设置、数据收集和通过描述速度场的处理方面存在许多挑战。****一种从单个相机收集三维（3D）粒子位置图像的新方法是基于收集相机所看到的整个光场。称为全光学成像，相机有一个微透镜阵列，允许小角度透视观察粒子的位置。这种类型的成像系统仅使用一个摄像头，在流体系统中安装和设置非常容易，特别是在观察通道有限的情况下。它也允许，第一次，在微观尺度上的三维流动的现实测量，如多孔介质中的流动和微观尺度的生物流动。该项目将继续开发这种类型的相机系统用于实验，通过开发通用校准程序，数据收集和处理以及基于PTV和粒子运动数值模型的先进方法，以提供高质量的流量测量。****对于任何粒子成像测速技术，都需要一种适当的方法来确定导出速度矢量的不确定性。到目前为止，由于实验设置和收集数据的计算处理的复杂相互作用，尚无确定PIV或PTV测量不确定度的通用方法。这是一个重要的基本问题，在学术界和工业界的实验热流体界都有很强的影响。该项目的一个重要部分将是开发一种通用的方法来确定所有这些类型的粒子图像速度测量系统的不确定性。****该项目将培养HQP在光学仪器和流体力学领域发展新的知识和科学。将这些技术统一起来的学术界和工业界都将感受到影响。******