Studying turbulent scale and space interactions using active grid wind tunnel and DNS database experiments

使用主动网格风洞和 DNS 数据库实验研究湍流尺度和空间相互作用

• 批准号: 1033942
• 负责人: Charles Meneveau
• 金额: $ 29.02万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1033942&HistoricalAwards=false
• 关键词: Studying; turbulent; scale; space; interactions

The proposed work will use novel approaches in both experimental and cyber-based fluid dynamics to address fundamental issues related to space and scale interactions in turbulent flows. The study of such interactions will impact predictive capabilities and help educate a new generation of students with know-how in integrated fluid dynamics experimentation and data-intensive science. To address multi-scale interactions in turbulence, a new type of active grid with fractal winglets will be built that injects kinetic energy over a broad range of scales but without generating a mean shear. To address spatial interactions in turbulence, another new active grid that produces a uniform turbulent kinetic energy gradient without mean velocity shear will be constructed. Data will be acquired in a wind-tunnel using thermal and particle image velocimetry. Results from these two new basic flows will shed light on the cascade, on the role of initial distribution of energy across scales, and on spatial diffusion rates. The project will also study the evolution of smaller-scale sub-portions of turbulent fluid. In order to follow in 3D the time-evolution of such fluid patches, we will use the recently developed Web-Services accessible public turbulence database that contains a 1024^4 space-time history of forced isotropic turbulence. Similarities and differences with the global evolution as known from the literature and the new experimental results will be studied providing the intellectual merit of the project, and also implications on subgrid-scale models for LES will be established. In terms of broader impacts, turbulence research as proposed here is part of a larger push to deal with systems with nonlinear complex behavior and many degrees of freedom. Large-scale numerical simulation of such systems is, today, at center stage of scientific discussions with important societal ramifications (global change, energy, etc.). Better integrating physical understanding, experimentation, and novel web-based analysis of large databases has the potential to generate new knowledge in the context of the emerging new paradigm of data-intensive science. Graduate education and training will stress the interplay between physical experimentation, simulation and the use of new cyber-based research tools.

这项拟议的工作将使用实验流体力学和基于网络的流体动力学的新方法来解决与湍流中空间和尺度相互作用有关的基本问题。对这种相互作用的研究将影响预测能力，并有助于培养新一代学生，使他们掌握综合流体力学实验和数据密集型科学的知识。为了解决湍流中的多尺度相互作用，将建立一种新型的带有分形翼的主动网格，它在广泛的尺度上注入动能，但不产生平均切变。为了解决湍流中的空间相互作用，将构造另一种新的活动网格，该网格产生没有平均速度切变的均匀湍流动能梯度。数据将在风洞中使用热像和粒子图像测速仪获取。这两个新的基本流动的结果将阐明级联、初始能量跨尺度分布的作用以及空间扩散速率。该项目还将研究较小尺度的湍流亚部分的演化。为了在3D中跟踪这种流体斑块的时间演变，我们将使用最近开发的Web服务可访问的公共湍流数据库，该数据库包含1024^4强迫各向同性湍流的时空历史。将研究与文献中已知的全球进化和新的实验结果的异同，提供该项目的智力优点，并将建立次网格尺度的大涡模拟的含义。就更广泛的影响而言，这里提出的湍流研究是处理具有非线性、复杂行为和多自由度系统的更大努力的一部分。今天，对这类系统的大规模数值模拟处于科学讨论的中心阶段，具有重要的社会影响(全球变化、能源等)。在新兴的数据密集型科学新范式的背景下，更好地整合对大型数据库的物理理解、实验和新颖的基于网络的分析，有可能产生新的知识。研究生教育和培训将强调物理实验、模拟和使用新的基于网络的研究工具之间的相互作用。