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Measurement and Analysis of Unsteady Flows Using a Lagrangian Framework

Measurement and Analysis of Unsteady Flows Using a Lagrangian Framework
使用拉格朗日框架测量和分析非定常流动
批准号:
RGPIN-2016-03666
负责人:
Rival, David
金额:
$4.23万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
翻译
旋涡--强烈旋转的区域--通常被称为“流体运动的肌腱和肌肉”,因为它们负责质量和动量的传输。此外,涡量的产生、重新定向和湮灭的研究对于自然界和工程中广泛存在的各种非定常空气动力学、流体力学和血液动力学问题都是普遍存在的。无论是小尺度的扑翼飞行,还是大尺度的风力机叶片失速,了解涡量是如何在物体附近产生并重新定向到尾流中,对于这类系统中的优化和流动控制至关重要。幸运的是,由于目前相机、激光和处理能力的进步,时间分辨、体积成像的新方法目前正在被引入。这些新方法被称为“摇动盒子”(STB)或断层粒子跟踪测速(Tomo-PTV),旨在打破实验室和现场实验中长期存在的障碍。与现有的基于欧拉的成像技术,如层析粒子图像测速仪(Tomo-PIV)不同,这些新的拉格朗日方法在超高播种密度下提供了详细的拉格朗日跟踪信息(长路径线),在任何给定的时间步长约为100,000个跟踪粒子。这一新方法开辟了一个全新的分析技术领域,从定常和运动物体附近的压力场提取到尾流中的直接拉格朗日相干结构(LCS)识别。*由于复杂流动数值模拟方法的发展需要高质量的实验来验证和校准,这种新的拉格朗日实验技术有望为这些难以捉摸的问题提供亟需的洞察。这种具有挑战性的情况的例子包括:大范围时间和空间尺度的高雷诺数(湍流)流动;与建筑物的非定常空气动力和水动力相互作用;心脏中发现的多相流和过渡流;以及大气中阵风的特征。拟议的研究计划将探索使用这些新的基于拉格朗日的测量技术及其相关的后处理策略,作为一种手段,以提供对这种流动的潜在物理的洞察。该提案将首先描述Tomo-PTV测量的实施可能如何塑造我们在分析这些问题时所采取的方向。特别是,我们将研究联网跟踪颗粒及其加速内容的新配方如何能够提取流动特征,如压力。对于涡度,我们将研究非定常物体附近的测量如何提供对涡度产生及其在尾流中重新定向的洞察,从而确定可能的流动控制和优化的新途径。**
英文摘要
Vortices - regions of strong rotation - are often referred to as the 'sinews and muscle of fluid motions' for the very fact that they are responsible for the transport of mass and momentum. Furthermore, the study of vorticity production, reorientation and annihilation are ubiquitous to a broad range of unsteady aerodynamic, hydrodynamic and hemodynamic problems found both in nature and engineering. Whether at the small scales of flapping flight or at large scales of stall on wind-turbine blades, understanding how vorticity is generated near a body and reoriented into the wake is critical towards optimization and flow control in such systems. Fortunately, due to current advances in camera, laser and processing capabilities, new methodologies in time-resolved, volumetric imaging are currently being introduced. These new methods are referred to as 'Shake-The-Box' (STB) or Tomographic Particle Tracking Velocimetry (Tomo-PTV), and are slated to break down long-standing barriers in lab- and field-based experimentation. Unlike existing Eulerian-based imaging techniques such as Tomographic Particle Image Velocimetry (Tomo-PIV), these new Lagrangian approaches provide detailed Lagrangian tracking information (long pathlines) at ultra-high seeding densities, on the order of 100,000 tracked particles at any given time step. This new approach opens up a whole new gamut of analysis techniques from pressure-field extraction near steady and moving bodies to direct Lagrangian Coherent Structure (LCS) identification in wakes. ***Since the development of numerical modelling approaches for complex flows demands high-quality experimentation for their validation and calibration, such new Lagrangian experimental techniques are expected to provide much needed insight into these elusive problems. Examples of such challenging cases include: high Reynolds number (turbulent) flows with a large range of temporal and spatial scales; unsteady aerodynamic and hydrodynamic interactions with structures; multiphase and transitional flows such as are found in the heart; and gust characterization in the atmosphere. The proposed research program will explore the use of these new Lagrangian-based measurement techniques and their associated post-processing strategies as a means to offer insight into the underlying physics of such flows. The proposal will begin by describing how the implementation of Tomo-PTV measurements is likely to shape the direction we take when analyzing these problems. In particular, we will look at how new formulations for networking tracked particles and their acceleration content will enable extraction of flow features such as pressure. With vorticity, we will investigate how measurements near unsteady bodies will provide insight into vorticity production and its reorientation in the wake, thus identifying possible new avenues for flow control and optimization. **
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Measurement and Analysis of Unsteady Flows Using a Lagrangian Framework
  • 批准号:
    RGPIN-2016-03666
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.23万
  • 财政年份:
    2022
  • 负责人:
    Rival, David
  • 依托单位:
Measurement and Analysis of Unsteady Flows Using a Lagrangian Framework
  • 批准号:
    RGPIN-2016-03666
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.23万
  • 财政年份:
    2021
  • 负责人:
    Rival, David
  • 依托单位:
I2I Phase I: Testing of real-time aerodynamics sensor system under realistic conditions
  • 批准号:
    567659-2021
  • 项目类别:
    Idea to Innovation
  • 资助金额:
    $9.11万
  • 财政年份:
    2021
  • 负责人:
    Rival, David
  • 依托单位:
Characterizing the dynamics of transition on turbofan blades
  • 批准号:
    523776-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $8.74万
  • 财政年份:
    2021
  • 负责人:
    Rival, David
  • 依托单位:
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