Diffusion approximation in turbulent two-particle dispersion.
Diffusion approximation in turbulent two-particle dispersion.
复制标题
湍流双粒子分散体中的扩散近似。
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
D. Benveniste
中科院分区：
文献类型：
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作者：
G. Eyink;D. Benveniste
我们解决了流体粒子对统计的逆问题：我们表明，时间序列的概率密度函数（PDF）的分离可以精确地再现通过求解扩散方程与适当的时间依赖性扩散。扩散率张量由条件拉格朗日速度结构函数的时间积分给出，由PDF的比率加权。流体动力学湍流的物理假设（扫描，短记忆，平均场）产生更简单的积分公式，包括Kraichnan和Lundgren（K-L）的一个。我们评估后者使用的时空数据库从数值Navier-Stokes解驱动湍流。K-L公式在均方根分离处再现PDF很好，但由于忽略记忆效应，均方色散的增长率被高估。更一般的应用，我们的方法勾勒。
We solve an inverse problem for fluid particle pair statistics: we show that a time sequence of probability density functions (PDFs) of separations can be exactly reproduced by solving the diffusion equation with a suitable time-dependent diffusivity. The diffusivity tensor is given by a time integral of a conditional Lagrangian velocity structure function, weighted by a ratio of PDFs. Physical hypotheses for hydrodynamic turbulence (sweeping, short memory, mean-field) yield simpler integral formulas, including one of Kraichnan and Lundgren (K-L). We evaluate the latter using a space-time database from a numerical Navier-Stokes solution for driven turbulence. The K-L formula reproduces PDFs well at root-mean-square separations, but growth rate of mean-square dispersion is overpredicted due to neglect of memory effects. More general applications of our approach are sketched.