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.

需要购买两台高速摄像机和配件。这些构成了可压缩流场完整三维重建和湍流声源识别的关键组成部分。用于此的数值方法是数据同化，其最小化来自直接数值计算的合成图像与来自高速相机的真实的纹影图像之间的差异。系统地，从两个不同的角度流的时间分辨的图像将与相机。这些图像可以基于例如密度梯度或引入的颗粒或烟雾。所获得的数据通过现有的测量技术进行补充，例如麦克风和热成像相机的帮助。在进一步的步骤中，将根据Navier-Stokes方程进行相同过程的流量计算。为此，必须指定计算的初始和边界条件。流量取决于这些条件。特别是对于湍流进气道，实际的流态是非常独特的。然而，在计划的研究项目中，初始和边界条件并不指定，而是通过优化来确定，使得高速图像与基于流场和建模的光学设置的合成图像之间的差异尽可能小。这个过程也被称为数据同化，并使用了最近在物理信息机器学习中获得动力的类似方法。工作组在只有一台摄像机和一个平面流的情况下进行了相应的初步工作。在这里建议采购的两台高速摄像机的帮助下，可以研究复杂的三维流动。相机的速度允许跨音速流动和气动声学现象的调查。优化的结果是完整的三维流。资料同化后，所有的流量变量可供进一步研究。所有的分析，这通常是保留的数值计算，因此可以调查的真实的实验。特别地，要执行流的模态分解。这将补充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进行。将获得的相机将允许这项工作在实验中进行。