高雷诺数湍流中惯性粒子分布的尺度相关统计

K. Matsuda, K. Schneider, K. Yoshimatsu
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引用次数: 7

摘要

提出了惯性粒子分布的多尺度统计分析方法,研究了含粒子不可压缩各向同性湍流中聚类和空穴区域的统计特征。三维直接数值模拟均质各向同性湍流在高雷诺数($Re_\lambda \gtrsim 200$)与高达$10^9$惯性粒子进行了斯托克斯数范围从$0.05$到$5.0$。然后将正交小波分析应用于计算得到的粒子数密度场。计算了颗粒数密度分布的尺度相关偏度和平坦度值,并评估了雷诺数$Re_\lambda$和斯托克斯数$St$的影响。对于$St \sim 1.0$,随着尺度的减小,尺度相关的偏度和平坦度值都变大,表明在小尺度下存在间歇性聚类。对于$St \le 0.2$,中间尺度(大于Kolmogorov尺度,小于流动积分尺度)的平整度随着$St$的增大而增大,偏度在中间尺度呈负值。偏度的负值归因于空洞区。这些结果表明,在如此小的Stokes数下,中间销售处的空洞区是明显的,并且是间歇性分布的。随着$Re_\lambda$的增加,平整度略有增加。对于$Re_\lambda \ge 328$,偏度在大尺度上呈现负值,表明在大尺度上存在空洞区,而在小尺度上存在团簇。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scale-dependent statistics of inertial particle distribution in high Reynolds number turbulence
Multiscale statistical analyses of inertial particle distributions are presented to investigate the statistical signature of clustering and void regions in particle-laden incompressible isotropic turbulence. Three-dimensional direct numerical simulations of homogeneous isotropic turbulence at high Reynolds number ($Re_\lambda \gtrsim 200$) with up to $10^9$ inertial particles are performed for Stokes numbers ranging from $0.05$ to $5.0$. Orthogonal wavelet analysis is then applied to the computed particle number density fields. Scale-dependent skewness and flatness values of the particle number density distributions are calculated and the influence of Reynolds number $Re_\lambda$ and Stokes number $St$ is assessed. For $St \sim 1.0$, both the scale-dependent skewness and flatness values become larger as the scale decreases, suggesting intermittent clustering at small scales. For $St \le 0.2$, the flatness at intermediate scales, i.e. for scales larger than the Kolmogorov scale and smaller than the integral scale of the flow, increases as $St$ increases, and the skewness exhibits negative values at the intermediate scales. The negative values of the skewness are attributed to void regions. These results indicate that void regions at the intermediate sales are pronounced and intermittently distributed for such small Stokes numbers. As $Re_\lambda$ increases, the flatness increases slightly. For $Re_\lambda \ge 328$, the skewness shows negative values at large scales, suggesting that void regions are pronounced at large scales, while clusters are pronounced at small scales.
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