EAGER: Maximizing Spatial Resolution and Accuracy of PIV with Optical Flow Velocimetry

流体流动的研究，最经常今天通过测量速度场使用粒子图像测速仪。这是30多年来的标准方法，已被证明是一种有效和可靠的技术。然而，最近的工作表明，有可能通过使用不同的图像处理方法，用相同的设备进行测量，但精度和细节要高得多。该项目的目的是开发和验证一种新的算法，以获得从粒子图像的速度测量，以取代目前的最先进的状态。新的算法将显着推进在学术界，工业界和国家实验室的流体流量测量系统的能力。 完成的算法和验证将传播到广泛的潜在users.This研究的重点是一个新的算法的发展测速从示踪粒子的激光片照射的图像对。新的算法将直接替代最先进的粒子图像测速处理软件中使用的基于互相关的方法，但该方法不需要任何新设备，如相机或激光器，因为输入到软件中的采集图像对于两种算法是相同的。众所周知，即使是最先进的基于相关性的算法也会在从图像计算速度场时损失空间分辨率，这主要是由于在处理期间使用有限大小的询问窗口。新方法将利用高等数学与流体力学的支配定律相结合，形成一种稳健的、受物理启发的方法，以解决当前算法的缺点。新算法将使研究人员能够在使用传统实验硬件的同时，以比迄今为止更高的精度，分辨率和动态范围测量湍流中的速度。该项目的最终愿景是在进行研究以确定最佳分配模式后，将经过彻底测试的算法最终版本尽可能广泛地传播给流体动力学实验者。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Fluid flows are most often studied today by measuring the velocity fields using particle image velocimetry. This has been the standard approach for over thirty years and has proven to be an effective and reliable technique. However, recent work has shown that it is possible to produce measurements with the same equipment but much higher accuracy and detail by using a different method for processing the images. The aim of this project is to develop and validate a new algorithm to obtain velocity measurements from particle images to replace the current state of the art. The new algorithm will significantly advance the capabilities of fluid flow measurement systems employed in academia, industry, and national laboratories. The finished algorithms and validations will be disseminated to a wide range of potential users.This research focuses on the development of a novel algorithm for velocimetry from pairs of images of tracer particles illuminated by a laser sheet. The new algorithm will substitute directly for the cross-correlation based approaches used in state-of-the-art particle image velocimetry processing software, but the approach does not require any new equipment, such as cameras or lasers, since the acquired images input to the software are the same for both algorithms. It is well known that even the most advanced correlation-based algorithms suffer from a loss in spatial resolution when computing the velocity field from images due primarily to the use of finite-sized interrogation windows employed during processing. The new method will utilize advanced mathematics coupled with the governing laws of fluid mechanics to form a robust, physics-inspired method that will address the shortcomings of current algorithms. The novel algorithm will allow researchers to measure velocities in turbulent flows with significantly greater accuracy, resolution, and dynamic range than has been possible to date, while using conventional experimental hardware. The vision for the end of the project is to disseminate the thoroughly tested, final version of the algorithm to the widest group of fluid dynamic experimenters as possible, after conducting a study to determine the optimal mode of distribution.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.