Advanced Particle Image Velocimetry image processing near dynamic interfaces adopting unsteady CFD mesh technology

采用非定常CFD网格技术的近动态界面的高级粒子图像测速图像处理

基本信息

批准号：
EP/L010755/1
负责人：
Raf Theunissen
金额：
$ 12.5万
依托单位：
University of Bristol
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FL010755%2F1
关键词：
Advanced Particle Image Velocimetry image

项目摘要

When air or water flows over an object, friction causes a thin layer to be formed in the immediate vicinity of the object's surface. In this boundary layer the relative flow velocity rapidly decreases to zero towards the body. This layer is of particular importance in air and fluid dynamics as it determines, for example, the amount of drag of an aircraft wing and therefore the overall fuel consumption. Moreover, viscous and turbulent effects in the boundary layer generate forces on the interface and, in case of flexible surfaces such as for example a flag or air bubble in water, can influence the shape of the object.The flow of water or air over interfaces is encountered in many engineering and day-to-day applications. Boundary layers (e.g. the airflow in the near vicinity of an airplane wing) or turbomachinery (e.g. inside a jet engine) are examples of flows over stationary rigid or moving surfaces. The airflow within lungs or blood running through veins and arteries on the other hand involve deformable surfaces, as is the new generation of shape-changing airplane wing. Interfacial flows involve the interaction between different media such as e.g. bubbles in water, waves and free surface turbulence. All of the applications above are fluid-structure-related problems where the primary concerns are either the transport of momentum across or near the surface, the interactive coupling between fluid motion and surface deformation, or both. Although Computational Fluid Dynamics (CFD) has made considerable progress over the last decades, the inherent modelling of the fluid-structure interactions remains at the forefront of CFD development. To investigate the complex flow phenomena highly resolved and reliable experiments are therefore needed.As an experimental measurement technique Particle Image Velocimetry (PIV) allows the measurement of flow velocity of air or water by injecting small particles which reflect light when illuminated. Comparison of two consecutive images of that illuminated seeded flow then enables the calculation of the displacement of the particles' images and therefore the velocity of the flow in which they are transported. Its non-intrusive nature together with its intrinsic simplicity and capability of retrieving instantaneous planar velocity measurements have made PIV a mature, standardized measurement technique in the field of experimental fluid-related dynamics both in academic and industrial environments for a wide range of applications. While the majority of PIV image processing-related studies have been aimed so far at improving the accuracy of the fluid velocities extraction, PIV image analysis involving arbitrarily moving bodies has received limited to no attention. From both an experimental and image analysis point of view, it is considered a worldwide challenge to obtain reliable, accurate velocity measurements with sufficient resolution near moving objects. This fundamental limitation of PIV has driven typical experiments to be limited to fields of view that are free of interfaces or other boundaries, which hampers the understanding of observed phenomena as the coupling between boundary motion and fluid forces cannot be characterised. Especially in arterial, pulmonary or aero-elasticity research, this presents a stringent limitation.It is the objective of the proposed work to introduce a new image processing technique in PIV image analyses to enable the extraction of high-fidelity, accurate and well resolved flow velocity fields near dynamic interfaces. This capability will allow proper characterization of flow phenomena in the vicinity of moving geometries, aiding understanding and providing experimental data for CFD validation.

当空气或水流在物体上时，摩擦会导致在物体表面附近形成薄层。在这个边界层中，相对流速度迅速降低到身体的零。该层在空气和流体动力学中尤其重要，因为它决定了飞机机翼的阻力量以及整体油耗。此外，边界层中的粘性和湍流效应会在界面上产生力，并且在柔性表面（例如水中的旗帜或气泡）的情况下会影响物体的形状。边界层（例如，飞机翼附近的近附近气流）或涡轮机械（例如，在喷气发动机内部）是固定刚性或移动表面上流动的示例。另一方面，肺部或血液中的气流涉及可变形的表面，新一代改变了形状的飞机翼。界面流涉及不同介质（例如水中的气泡，波浪和自由表面湍流。上面的所有应用都是流体结构相关的问题，主要问题是动量跨表面或附近的动量运输，流体运动和表面变形之间的相互作用耦合，或两者兼有。尽管在过去几十年中，计算流体动力学（CFD）取得了长足的进步，但流体结构相互作用的固有建模仍然是CFD开发的最前沿。因此，为了研究复杂的流动现象，需要高度分辨和可靠的实验。作为实验测量技术，粒子图像速度计（PIV）允许通过注射小颗粒来测量空气或水的流速，从而反射时，这些颗粒在照亮时反射光。比较该照明的种子流的两个连续图像，然后可以计算粒子图像的位移，因此可以计算它们运输的流量的速度。它的非侵入性质，以及检索瞬时平面速度测量值的内在简单性和能力，使PIV成为在实验流体相关动力学领域的成熟，标准化的测量技术，用于各种应用程序和工业环境。迄今为止，大多数与PIV图像处理相关的研究的目的是提高流体速度提取的准确性，但涉及任意移动物体的PIV图像分析已受到限制。从实验和图像分析的角度来看，获得可靠，准确的速度测量值，并在移动对象附近有足够的分辨率来获得全球范围的挑战。 PIV的这种基本局限性使典型的实验仅限于没有界面或其他边界的视野，这阻碍了观察到的现象，因为无法表征边界运动和流体力之间的耦合。尤其是在动脉，肺或空气弹性研究中，这是一个严格的限制。这是拟议的工作的目的，是在PIV图像分析中引入一种新的图像处理技术，以便在动态接口附近提取高效率，准确且分辨出良好的流动速度场。该能力将允许在移动几何形状附近的流动现象正确表征，从而有助于理解并为CFD验证提供实验数据。