EAPSI: Identification of Transport Barriers in Two-Dimensional Turbulence

EAPSI：识别二维湍流中的传输障碍

• 批准号: 1515202
• 负责人: Benjamin Faber
• 金额: $ 0.51万
• 依托单位: Faber Benjamin J
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1515202&HistoricalAwards=false
• 关键词: EAPSI; Identification; Transport; Barriers; Two

Knowing the location and evolution of transport barriers within a fluid provides an important tool in predicting how particles disperse, a prime example being how an oil spill spreads on the ocean surface. A turbulent, two-dimensional fluid, like the surface of the ocean, can have distinct regions where the fluid does and does not mix, which determines how particles are transported across the surface of the fluid. Those non-mixing regions are known as transport barriers, as particles outside cannot move into or across the transport barrier. This project will use laboratory-produced two-dimensional turbulence to experimentally test and refine recently developed, novel mathematical methods for identifying transport barriers. This research will be conducted in collaboration with Dr. Hua Xia, an expert in experimental two-dimensional fluid turbulence, at Australian National University in Canberra, Australia.Historically, identifying coherent structures (transport barriers) in a fluid by way of finite time Lyapunov exponents is an intensive task that requires detailed resolution of the fluid velocity field. Recently, mathematical methods for identifying coherent structures based on braid theory have been developed and applied to several test cases. These methods are advantageous as they can identify coherent structures from a small number of surface particle trajectories, decreasing the computational cost and increasing the method applicability. This research will implement and improve the braid-theoretic identification scheme by testing the algorithms with surface particle trajectories taken from experiments in which turbulence is driven by Faraday waves. This project aims to develop a computational framework that can then be applied in situ to surface particle trajectories both inside and outside of laboratory experiments. This NSF EAPSI award is funded in collaboration with the Australian Academy of Science.

了解流体中传输障碍的位置和演变为预测颗粒如何分散提供了一个重要工具，一个主要的例子是石油泄漏如何在海洋表面扩散。 湍流的二维流体，如海洋的表面，可以具有流体混合和不混合的不同区域，这决定了颗粒如何在流体表面上传输。 这些非混合区域被称为传输屏障，因为外部的颗粒不能移动到传输屏障中或穿过传输屏障。 该项目将使用实验室产生的二维湍流来实验测试和改进最近开发的用于识别传输障碍的新颖数学方法。 该研究将与澳大利亚堪培拉的澳大利亚国立大学实验二维流体湍流专家华夏博士合作进行。历史上，通过有限时间的李雅普诺夫指数识别流体中的相干结构（传输障碍）是一项密集的任务，需要详细解析流体速度场。 最近，数学方法识别相干结构的辫子理论的基础上已经开发和应用到几个测试用例。 这些方法是有利的，因为它们可以从少量的表面粒子轨迹中识别相干结构，降低计算成本并增加方法的适用性。 本研究将实施和改进的辫子理论的识别方案，通过测试的算法与表面粒子的轨迹取自实验中，湍流驱动的法拉第波。 该项目旨在开发一个计算框架，然后可以在实验室实验内外原位应用于表面粒子轨迹。 这个NSF EAPSI奖是与澳大利亚科学院合作资助的。