Eyink Gregory L, Benveniste Damien
Department of Applied Mathematics & Statistics, The Johns Hopkins University, Baltimore, Maryland 21218, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Feb;87(2):023011. doi: 10.1103/PhysRevE.87.023011. Epub 2013 Feb 19.
Synthetic models of Eulerian turbulence like so-called kinematic simulations (KS) are often used as computational shortcuts for studying Lagrangian properties of turbulence. These models have been criticized by Thomson and Devenish (2005), who argued on physical grounds that sweeping decorrelation effects suppress pair dispersion in such models. We derive analytical results for Eulerian turbulence modeled by Gaussian random fields, in particular for the case with zero mean velocity. Our starting point is an exact integrodifferential equation for the particle pair separation distribution obtained from the Gaussian integration-by-parts identity. When memory times of particle locations are short, a Markovian approximation leads to a Richardson-type diffusion model. We obtain a time-dependent pair diffusivity tensor of the form K(ij)(r,t)=S(ij)(r)τ(r,t), where S(ij)(r) is the structure-function tensor and τ(r,t) is an effective correlation time of velocity increments. Crucially, this is found to be the minimum value of three times: the intrinsic turnover time τ(eddy)(r) at separation r, the overall evolution time t, and the sweeping time r/v(0) with v(0) the rms velocity. We study the diffusion model numerically by a Monte Carlo method. With inertial ranges like the largest achieved in most current KS (about 6 decades long), our model is found to reproduce the t(9/2) power law for pair dispersion predicted by Thomson and Devenish and observed in the KS. However, for much longer ranges, our model exhibits three distinct pair-dispersion laws in the inertial range: a Batchelor t(2) regime, followed by a Kraichnan-model-like t(1) diffusive regime, and then a t(6) regime. Finally, outside the inertial range, there is another t(1) regime with particles undergoing independent Taylor diffusion. These scalings are exactly the same as those predicted by Thomson and Devenish for KS with large mean velocities, which we argue hold also for KS with zero mean velocity. Our results support the basic conclusion of Thomson and Devenish (2005) that sweeping effects make Lagrangian properties of KS fundamentally differ from those of hydrodynamic turbulence for very extended inertial ranges.
像所谓的运动学模拟(KS)这样的欧拉湍流合成模型,常被用作研究湍流拉格朗日特性的计算捷径。这些模型受到了汤姆森和德文什(2005年)的批评,他们基于物理理由认为,扫掠去相关效应会抑制此类模型中的粒子对扩散。我们推导了由高斯随机场建模的欧拉湍流的解析结果,特别是零平均速度的情况。我们的出发点是从高斯分部积分恒等式得到的粒子对分离分布的精确积分 - 微分方程。当粒子位置的记忆时间短时,马尔可夫近似会导致一个理查森型扩散模型。我们得到了形式为(K_{(ij)}(r,t)=S_{(ij)}(r)\tau(r,t))的时间相关对扩散率张量,其中(S_{(ij)}(r))是结构函数张量,(\tau(r,t))是速度增量的有效相关时间。关键的是,发现这是三个时间的最小值:分离(r)处的固有周转时间(\tau_{(eddy)}(r))、整体演化时间(t)以及以均方根速度(v(0))扫掠的时间(r/v(0))。我们通过蒙特卡罗方法对扩散模型进行了数值研究。对于像大多数当前KS中实现的最大惯性范围(约6个数量级长),我们的模型被发现能重现汤姆森和德文什预测并在KS中观察到的粒子对扩散的(t^{9/2})幂律。然而,对于长得多的范围,我们的模型在惯性范围内表现出三种不同的粒子对扩散定律:一个巴彻勒(t^2) regime,接着是一个类似克莱奇南模型的(t^1)扩散 regime,然后是一个(t^6) regime。最后,在惯性范围之外,存在另一个(t^1) regime,粒子在此经历独立的泰勒扩散。这些标度与汤姆森和德文什对具有大平均速度的KS所预测的完全相同,我们认为这对于零平均速度的KS也成立。我们的结果支持了汤姆森和德文什(2005年)的基本结论,即对于非常扩展的惯性范围,扫掠效应使得KS的拉格朗日特性与流体动力学湍流的拉格朗日特性有根本不同。