Wu Zhao, Zaki Tamer A, Meneveau Charles
Institute for Data Intensive Engineering and Science, Johns Hopkins University, Baltimore, MD 21218.
Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218.
Proc Natl Acad Sci U S A. 2020 Feb 18;117(7):3461-3468. doi: 10.1073/pnas.1916636117. Epub 2020 Feb 5.
Transition from laminar to turbulent flow occurring over a smooth surface is a particularly important route to chaos in fluid dynamics. It often occurs via sporadic inception of spatially localized patches (spots) of turbulence that grow and merge downstream to become the fully turbulent boundary layer. A long-standing question has been whether these incipient spots already contain properties of high-Reynolds-number, developed turbulence. In this study, the question is posed for geometric scaling properties of the interface separating turbulence within the spots from the outer flow. For high-Reynolds-number turbulence, such interfaces are known to display fractal scaling laws with a dimension [Formula: see text], where the 1/3 excess exponent above 2 (smooth surfaces) follows from Kolmogorov scaling of velocity fluctuations. The data used in this study are from a direct numerical simulation, and the spot boundaries (interfaces) are determined by using an unsupervised machine-learning method that can identify such interfaces without setting arbitrary thresholds. Wide separation between small and large scales during transition is provided by the large range of spot volumes, enabling accurate measurements of the volume-area fractal scaling exponent. Measurements show a dimension of [Formula: see text] over almost 5 decades of spot volume, i.e., trends fully consistent with high-Reynolds-number turbulence. Additional observations pertaining to the dependence on height above the surface are also presented. Results provide evidence that turbulent spots exhibit high-Reynolds-number fractal-scaling properties already during early transitional and nonisotropic stages of the flow evolution.
在光滑表面上从层流到湍流的转变是流体动力学中通向混沌的一条特别重要的途径。它通常通过湍流的空间局部斑块(斑点)的零星起始而发生,这些斑块在下游生长并合并,形成完全湍流的边界层。一个长期存在的问题是,这些初始斑点是否已经包含高雷诺数充分发展湍流的特性。在本研究中,针对将斑点内的湍流与外部流动分隔开的界面的几何缩放特性提出了这个问题。对于高雷诺数湍流,已知此类界面呈现分形缩放定律,其维度为[公式:见原文],其中高于2(光滑表面)的1/3超额指数源于速度波动的柯尔莫哥洛夫缩放。本研究中使用的数据来自直接数值模拟,斑点边界(界面)通过使用一种无监督机器学习方法来确定,该方法无需设置任意阈值就能识别此类界面。斑点体积范围大,在转变过程中小尺度和大尺度之间有很大间隔,从而能够准确测量体积 - 面积分形缩放指数。测量结果显示,在几乎5个数量级的斑点体积范围内,维度为[公式:见原文],即趋势与高雷诺数湍流完全一致。还给出了与表面上方高度依赖性相关的其他观测结果。结果提供了证据,表明湍流斑点在流动演化的早期过渡和非各向同性阶段就已经表现出高雷诺数分形缩放特性。