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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.

当空气或水在物体上方流动时，摩擦会导致物体表面附近形成一层薄层。在该边界层中，相对流速迅速下降到零。这一层在空气和流体动力学中特别重要，因为它决定了例如飞机机翼的阻力大小，从而决定了总体燃料消耗。此外，边界层中的粘性和湍流效应会对界面产生作用力，对于柔性表面，例如水中的旗帜或气泡，可能会影响物体的形状。在许多工程和日常应用中，会遇到水或空气在界面上的流动。边界层(如机翼附近的气流)或叶轮机械(如喷气发动机内部)是在静止、刚性或运动表面上流动的例子。另一方面，肺内的气流或流经静脉和动脉的血液涉及可变形的表面，新一代变形飞机机翼也是如此。界面流动涉及不同介质之间的相互作用，如水中的气泡、波和自由表面湍流。所有上述应用都是与流体结构有关的问题，其中主要关注的是动量在表面上或附近的传输，流体运动和表面变形之间的交互耦合，或者两者兼而有之。尽管计算流体动力学(CFD)在过去的几十年中取得了长足的进步，但流体-结构相互作用的固有模型仍然处于CFD发展的前沿。为了研究复杂的流动现象，需要高分辨率和可靠的实验。粒子图像测速仪(PIV)作为一种实验测量技术，可以通过注入微小的粒子来测量空气或水的流动速度，这些粒子在照射时会反射光线。对两幅连续的照亮的种子流图像进行比较，就可以计算出粒子图像的位移，从而计算出它们所在流动的速度。它的非侵入性，加上其固有的简单性和恢复瞬时平面速度测量的能力，使PIV成为学术和工业环境中与流体相关的实验动力学领域的一种成熟的标准化测量技术，具有广泛的应用前景。虽然到目前为止，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精度，但涉及任意运动物体的PIV图像分析一直没有受到关注。从实验和图像分析的角度来看，在运动物体附近获得可靠、准确、具有足够分辨率的速度测量被认为是一个世界性的挑战。PIV的这一根本限制促使典型的实验局限于没有界面或其他边界的视场，这阻碍了对观察到的现象的理解，因为无法表征边界运动和流体力之间的耦合。特别是在动脉、肺或气动弹性的研究中，这是一个严格的限制。本工作的目的是在PIV图像分析中引入一种新的图像处理技术，以便能够提取高保真、准确和良好分辨率的动态界面附近的流动速度场。这一能力将允许正确描述运动几何附近的流动现象，有助于理解并为CFD验证提供实验数据。