Measurement and Analysis of Unsteady Flows Using a Lagrangian Framework

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。

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.