High-Speed-Camera-System for 3D-Measurements of Flow Fields

用于流场 3D 测量的高速摄像系统

• 批准号: 525772482
• 金额: --
• 依托单位: Universität Bayreuth
• 依托单位国家: 德国
• 项目类别: Major Research Instrumentation
• 财政年份: 2023
• 资助国家: 德国
• 起止时间: 2022-12-31 至 无数据
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/525772482?language=en
• 关键词: Speed; Camera; System; 3D; Measurements

Two high-speed cameras and accessories are to be purchased. These form the key component for the complete three-dimensional reconstruction of compressible flow fields and for the identification of sound sources in turbulent flows. The numerical method for this is a data assimilation, which minimizes the difference between synthetic images from a direct numerical calculation and the real Schlieren images from the high-speed cameras. Methodically, time-resolved images of a flow from two different perspectives are to be taken with the cameras. These images can be based, for example, on density gradients or on introduced particles or smoke. The data obtained are complemented by existing measurement technology, for example with the help of microphones and a thermal camera. In a further step, flow calculations of the same process based on Navier-Stokes equations will be performed. For this purpose, initial and boundary conditions for the calculation have to be specified. The flow depends on these conditions. Especially for a turbulent inlet, the actual flow pattern is very unique. In the planned research projects, however, initial and boundary conditions are not specified, but are determined by optimization in such a way that the difference between the high-speed images and synthetic images based on the flow field and the modeled optical setup is as small as possible. This process is also called data assimilation and uses similar methods which recently acquire momentum in Physics-informed Machine Learning. Corresponding preliminary work with only one camera and a plane flow is available in the working group. With the help of the two high-speed cameras proposed for procurement here, complex, three-dimensional flows can be investigated. The speed of the cameras allows the investigation of transsonic flows and aeroacoustic phenomena. The result of the optimization is the complete, three-dimensional flow. All flow variables are available for further investigation after data assimilation. All analyses, which are usually reserved for numerical computation, can thus be investigated on the real experiment. In particular, a modal decomposition of the flow is to be performed. This will complement work within the group to determine coherent turbulent structures. So far, this can only be done on a numerical basis. The cameras to be acquired will allow this work to be carried out on the experiment instead.

将购买两台高速摄像机和配件。它们构成了可压缩流场的完整三维重建和湍流中声源识别的关键组件。其数值方法是数据同化，它最大限度地减少了直接数值计算的合成图像与高速摄像机的真实纹影图像之间的差异。系统地，用相机从两个不同的角度拍摄流的时间分辨图像。这些图像可以基于例如密度梯度或引入的颗粒或烟雾。现有的测量技术对获得的数据进行了补充，例如借助麦克风和热像仪。下一步，将根据纳维-斯托克斯方程对同一过程进行流量计算。为此，必须指定计算的初始条件和边界条件。流量取决于这些条件。特别是对于湍流入口，实际的流型非常独特。然而，在计划的研究项目中，并未指定初始条件和边界条件，而是通过优化来确定，以使高速图像与基于流场和建模光学设置的合成图像之间的差异尽可能小。这个过程也称为数据同化，并使用最近在物理信息机器学习中获得动力的类似方法。工作组中提供了仅用一台相机和平面流程进行的相应前期工作。借助此处建议采购的两台高速摄像机，可以研究复杂的三维流动。相机的速度允许研究跨音速流和气动声学现象。优化的结果是完整的三维流。数据同化后，所有流动变量均可用于进一步研究。因此，所有通常用于数值计算的分析都可以在实际实验中进行研究。特别是，要执行流的模态分解。这将补充该小组内确定相干湍流结构的工作。到目前为止，这只能在数字基础上完成。将获得的相机将允许这项工作在实验上进行。