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

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
批准号:
EP/L010755/1
负责人:
Raf Theunissen
金额:
$12.5万
依托单位:
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
项目状态:
已结题
起止时间:
2014 至 --

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中文摘要
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英文摘要
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.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
DOI: --
发表时间: 2015-09
期刊:
影响因子: --
作者: [A. Masullo;R. Theunissen]
通讯作者: A. Masullo;R. Theunissen
DOI: 10.1007/s00348-015-2110-8
发表时间: 2016-02
期刊: Experiments in Fluids
影响因子: 2.4
作者: [A. Masullo;R. Theunissen]
通讯作者: A. Masullo;R. Theunissen
The feasibility of using CFD meshing in PIV image processing near curvy interfaces
在弯曲界面附近的 PIV 图像处理中使用 CFD 网格划分的可行性
DOI: --
发表时间: 2015
期刊:
影响因子: --
作者: [Masullo A]
通讯作者: Masullo A
Improvement in universal outlier detection by means of coherence adaptivity
通过相干适应性改进通用异常值检测
DOI: --
发表时间: 2015
期刊:
影响因子: --
作者: [Masullo A]
通讯作者: Masullo A
国内基金
海外基金
环形等离子体中的离子漂移波不稳定性和湍流的保结构Particle-in-Cell模拟
  • 批准号:
    11905220
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    25.0万元
  • 批准年份:
    2019
  • 负责人:
    肖建元
  • 依托单位:
基于多禁带光子晶体微球构建"Array on One Particle"传感体系
  • 批准号:
    21902147
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    27.0万元
  • 批准年份:
    2019
  • 负责人:
    崔杰铖
  • 依托单位:
空气污染(主要是diesel exhaust particle,DEP)和支气管哮喘关系的研究
  • 批准号:
    30560052
  • 项目类别:
    地区科学基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2005
  • 负责人:
    元熙哲
  • 依托单位: