论文标题
多时间结构功能和湍流的拉格朗日缩放
Multi-time structure functions and the Lagrangian scaling of turbulence
论文作者
论文摘要
我们使用两个具有平均流动和湍流的旋转流的数据来定义和表征多个时间拉格朗日结构的功能：泰勒绿色的数值流和vonKármán实验室实验。数据是从示踪剂在前一种情况下的数值整合，也是从后者中的三维粒子跟踪测量值获得的。显示多时间统计数据可减少惯性范围内大尺度的污染。鉴定出来自平均流量的污染物的时间尺度，确定了两个不同的拉格朗日缩放范围。多时间结构函数的结果还表明，拉格朗日间歇性不是大规模流动效应的结果。可以在不知道强迫机制或边界条件的情况下使用多个时间的拉格朗日结构函数，从而允许其在不同的流量几何形状中应用。
We define and characterize multi-time Lagrangian structure functions using data stemming from two swirling flows with mean flow and turbulent fluctuations: A Taylor-Green numerical flow, and a von Kármán laboratory experiment. Data is obtained from numerical integration of tracers in the former case, and from three-dimensional particle tracking velocimetry measurements in the latter. Multi-time statistics are shown to decrease the contamination of large scales in the inertial range scaling. A time scale at which contamination from the mean flow becomes dominant is identified, with this scale separating two different Lagrangian scaling ranges. The results from the multi-time structure functions also indicate that Lagrangian intermittency is not a result of large-scale flow effects. The multi-time Lagrangian structure functions can be used without prior knowledge of the forcing mechanisms or boundary conditions, allowing their application in different flow geometries.
