论文标题

高雷诺数中惯性颗粒分布的量表依赖性统计数据

Scale-dependent statistics of inertial particle distribution in high Reynolds number turbulence

论文作者

Matsuda, Keigo, Schneider, Kai, Yoshimatsu, Katsunori

论文摘要

提出了惯性颗粒分布的多尺度统计分析,以研究载有颗粒不可压缩的各向同性湍流中聚类和空隙区域的统计特征。高雷诺数($re_λ\ gtrsim 200 $)的均质各向同性湍流的三维直接数值模拟,最高$ 10^9 $惯性粒子的stokes数字从0.05美元到$ 5.0 $不等。然后将正交小波分析应用于计算的粒子数密度字段。计算了粒子数密度分布的比例依赖性偏度和平坦度值,并评估了雷诺数$re_λ$和stokes number $ st $的影响。对于$ st \ sim 1.0 $,随着比例的减小,依赖比例的偏度和平坦值都变得更大,这表明在小尺度上进行间歇性聚类。对于$ st \ le 0.2 $,在中间尺度上的平坦度,即大于Kolmogorov量表的量表,并且小于流量的积分尺度,随着$ ST $的增加而增加,并且偏度在中间尺度上表现出负值。偏度的负值归因于空隙区域。这些结果表明,中间销售的空隙区域被明显,并间歇性地分布在如此小的stokes数字上。随着$re_λ$的增加,平坦度略有增加。对于$re_λ\ ge 328 $,偏度在大尺度上显示负值,这表明空隙区域在大尺度上发音,而簇在小尺度上发音。

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 ($Re_λ\gtrsim 200$) 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 $Re_λ$ 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 $Re_λ$ increases, the flatness increases slightly. For $Re_λ\ge 328$, 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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