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

当空气或水流过物体时，摩擦会在物体表面附近形成一层薄层。在这个边界层中，相对流动速度迅速降至零。这一层在空气和流体动力学中特别重要，因为它决定了飞机机翼的阻力量，从而决定了总体燃油消耗。此外，边界层中的粘性和湍流效应在界面上产生力，并且在柔性表面的情况下，例如水中的旗帜或气泡，可以影响物体的形状。在许多工程和日常应用中，都会遇到界面上的水或空气流动。边界层（例如飞机机翼附近的气流）或涡轮机械（例如喷气发动机内部）都是流过固定刚性或移动表面的气流。另一方面，肺部的气流或流经静脉和动脉的血液涉及到可变形的表面，就像新一代可变形的飞机机翼一样。界面流动涉及不同介质之间的相互作用，例如水中的气泡、波浪和自由表面湍流。上述所有应用都是与流体结构相关的问题，其中主要关注的是穿过或接近表面的动量传输，流体运动和表面变形之间的相互耦合，或两者兼而有之。尽管计算流体动力学（CFD）在过去几十年中取得了相当大的进展，但流体-结构相互作用的固有建模仍然是CFD发展的前沿。因此，为了研究复杂的流动现象，需要高分辨率和可靠的实验。作为一种实验测量技术，粒子图像测速（PIV）可以通过注入小颗粒来测量空气或水的流速，这些小颗粒在照射时反射光。比较被照亮的种子流的两个连续图像，就可以计算出粒子图像的位移，从而计算出它们被输送的流速。PIV的非侵入性以及其固有的简单性和检索瞬时平面速度测量的能力使其成为学术和工业环境中实验流体相关动力学领域成熟的标准化测量技术，具有广泛的应用前景。迄今为止，大多数与PIV图像处理相关的研究都是为了提高流体速度提取的准确性，而涉及任意运动物体的PIV图像分析却很少受到关注。从实验和图像分析的角度来看，在移动物体附近获得足够分辨率的可靠、准确的速度测量被认为是一个全球性的挑战。PIV的这一基本限制使得典型的实验被限制在没有界面或其他边界的视场中，这阻碍了对观察到的现象的理解，因为边界运动和流体力之间的耦合无法表征。特别是在动脉、肺或空气弹性研究中，这有严格的限制。本文的目标是在PIV图像分析中引入一种新的图像处理技术，以便在动态界面附近提取高保真、准确和良好分辨的流速场。这种能力将允许对移动几何形状附近的流动现象进行适当的表征，有助于理解并为CFD验证提供实验数据。

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.