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湍流中流拓扑和条件统计的新观点。

A new view of flow topology and conditional statistics in turbulence.

机构信息

University of Michigan-Shanghai Jiaotong University Joint Institute, 800 Dongchuan Road, 200240 Shanghai, Republic of China.

出版信息

Philos Trans A Math Phys Eng Sci. 2013 Jan 13;371(1982):20120169. doi: 10.1098/rsta.2012.0169.

Abstract

By partitioning a turbulent flow field into relative simple units, the original complex system may be better understood from studying decomposed structures. In this paper, some general principles for identifying geometrical decomposition are discussed. Logically, to make analysis more objective and quantitative, the decomposed units need to be non-arbitrarily defined and space filling. Following this vein, we introduced two topological approaches satisfying these prerequisites and the relevant work is reviewed. For a given scalar variable, dissipation elements are defined as the spatial regions that the gradient trajectories of this scalar can share the same pair of scalar extremums (one maximum and one minimum), whereas for the general vector variables, vector tube segments are the part of vector tubes bounded by adjacent extremums of the magnitude of the given vector. Both structures can be characterized by representative shape parameters: the length scale and the extremum difference. On the basis of direct numerical simulation data, the statistics of the shape parameters have been studied. Physically, those structures reveal the 'nature' topology of turbulence, and thus their characteristic parameters reflect the flow properties. For instance, when the vector tube segment approach is applied to the velocity case, the negative skewness of the velocity derivative can be explained by the asymmetry of the joint probability density function of the shape parameters of streamtube segments. Conditional statistics based on these newly defined structures identify finer flow physics and are believed helpful for modelling improvement. Application examples illustrate that, in principle, these methods can generally be applied to different flow cases under different situations.

摘要

通过将湍流流场划分为相对简单的单元,可以通过研究分解结构更好地理解原始复杂系统。本文讨论了一些用于识别几何分解的一般原则。从逻辑上讲,为了使分析更加客观和定量,需要对分解单元进行非任意定义和空间填充。基于此,我们引入了两种满足这些前提的拓扑方法,并回顾了相关工作。对于给定的标量变量,耗散单元被定义为梯度轨迹可以共享同一对标量极值(一个最大值和一个最小值)的空间区域,而对于一般的向量变量,向量管段是由给定向量的大小的相邻极值限定的向量管的一部分。这两种结构都可以用代表性的形状参数来描述:长度尺度和极值差。基于直接数值模拟数据,研究了形状参数的统计特性。从物理上讲,这些结构揭示了湍流的“本质”拓扑,因此它们的特征参数反映了流动特性。例如,当向量管段方法应用于速度情况时,可以通过流管段形状参数的联合概率密度函数的不对称性来解释速度导数的负偏度。基于这些新定义的结构的条件统计可以识别更精细的流动物理特性,并且有助于改进模型。应用实例表明,这些方法原则上可以一般应用于不同情况下的不同流动情况。

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