论文标题
快速生成的高斯随机字段，用于直接的随机传输数值模拟
Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport
论文作者
论文摘要
我们提出了一种基于修改光谱表示，傅立叶和斑点的组合来构建高斯随机场（GRF）的新型离散方法。该方法旨在直接对V-Langevin方程进行直接数值模拟。后者是对各种物理系统中异常随机转运的刻板印象描述。从欧拉（Eulerian）的角度来看，我们的方法旨在提高收敛速率。从拉格朗日的角度来看，我们的其他方法对湍流速度场中粒子轨迹的描述相关：确切的拉格朗日不变定律得到了很好的复制。从计算的角度来看，我们的方法的速度是标准数值表示的两倍。
We propose a novel discrete method of constructing Gaussian Random Fields (GRF) based on a combination of modified spectral representations, Fourier and Blob. The method is intended for Direct Numerical Simulations of the V-Langevin equations. The latter are stereotypical descriptions of anomalous stochastic transport in various physical systems. From an Eulerian perspective, our method is designed to exhibit improved convergence rates. From a Lagrangian perspective, our method others a pertinent description of particle trajectories in turbulent velocity fields: the exact Lagrangian invariant laws are well reproduced. From a computational perspective, our method is twice as fast as standard numerical representations.
