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arXiv physics/0410148physics.flu-dyncond-mat.stat-mechhep-th
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随机受迫纳维-斯托克斯方程的大偏差方法

Large Deviation Approach to the Randomly Forced Navier-Stokes Equation

R. Collina, R. Livi, A. Mazzino

摘要:

随机受迫纳维-斯托克斯方程可以作为一个适当作用量的变分问题得到。由于不可压缩性,对场的横向分量的积分允许以大偏差泛函的形式投射作用。由于流体动力学算子是非线性的,因此可以通过围绕流体动力学方程的物理解线性化来实际计算产生波动统计的泛函积分。我们表明,这个过程产生的尺寸缩放K41理论预测的最低扰动阶,其中的扰动参数是逆雷诺数。此外,还得到了标度律前因子的显式表达式。

英文摘要:

The random forced Navier-Stokes equation can be obtained as a variational problem of a proper action. By virtue of incompressibility, the integration over transverse components of the fields allows to cast the action in the form of a large deviation functional. Since the hydrodynamic operator is nonlinear, the functional integral yielding the statistics of fluctuations can be practically computed by linearizing around a physical solution of the hydrodynamic equation. We show that this procedure yields the dimensional scaling predicted by K41 theory at the lowest perturbative order, where the perturbation parameter is the inverse Reynolds number. Moreover, an explicit expression of the prefactor of the scaling law is obtained.

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