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

拟议的工作将使用实验和基于网络的流体动力学的新方法来解决湍流中与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，并有助于教育新一代学生掌握综合流体动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，将建立一种新型的分形小翼主动网格，该网格在大尺度范围内注入动能，但不会产生平均剪切。为了解决湍流中的空间相互作用，将构建另一个新的活动网格，该网格产生均匀的湍流动能梯度，没有平均速度剪切。数据将在风洞中使用热学和粒子成像测速法获得。这两种新的基本流的结果将揭示级联、能量跨尺度初始分布的作用以及空间扩散速率。该项目还将研究湍流的小尺度亚部分的演化。为了以3D方式跟踪这些流体斑块的时间演变，我们将使用最近开发的Web-Services可访问的公共湍流数据库，该数据库包含强制各向同性湍流的1024^4时空历史。将研究从文献和新的实验结果中得知的全球演变的异同，为项目提供智力价值，并建立LES的亚电网尺度模型的含义。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个自由度的系统的更大推动力的一部分。这些系统的大规模数值模拟，今天，在具有重要社会影响（全球变化，能源等）的科学讨论的中心阶段。在数据密集型科学新范式的背景下，更好地整合物理理解、实验和基于网络的大型数据库分析，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。

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.