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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.

当空气或水流过物体时，摩擦会导致物体表面附近形成一层薄层。在该边界层中，朝向主体的相对流速迅速减小至零。该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。在许多工程和日常应用中都会遇到水或空气在界面上的流动。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）是静止刚性或移动表面上流动的示例。另一方面，肺部的气流或流经静脉和动脉的血液涉及可变形的表面，新一代可变形的飞机机翼也是如此。界面流动涉及不同介质之间的相互作用，例如介质。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靠近表面的动量传输、流体运动和表面变形之间的交互耦合，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长足的进步，但流体-结构相互作用的固有建模仍然处于 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) 允许通过注入在照明时反射光的小颗粒来测量空气或水的流速。然后，通过比较被照射的种子流的两个连续图像，可以计算粒子图像的位移，从而计算出它们在其中传输的流的速度。其非侵入性、固有的简单性以及检索瞬时平面速度测量值的能力，使 PIV 成为学术和工业环境中实验流体相关动力学领域成熟、标准化的测量技术，具有广泛的应用。虽然迄今为止大多数与 PIV 图像处理相关的研究都旨在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可靠、准确、具有足够分辨率的速度测量被认为是世界范围内的挑战。 PIV 的这种基本限制使得典型的实验仅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，这提出了严格的限制。本文的目的是在 PIV 图像分析中引入一种新的图像处理技术，以便能够提取动态界面附近的高保真、准确且分辨率良好的流速场。此功能将允许正确表征移动几何形状附近的流动现象，帮助理解并为 CFD 验证提供实验数据。