Clark di Leoni P, Cobelli P J, Mininni P D
Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and IFIBA, CONICET, Cuidad Universitaria, Buenos Aires 1428, Argentina.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jun;89(6):063025. doi: 10.1103/PhysRevE.89.063025. Epub 2014 Jun 30.
We study wave turbulence in shallow water flows in numerical simulations using two different approximations: the shallow water model and the Boussinesq model with weak dispersion. The equations for both models were solved using periodic grids with up to 2048{2} points. In all simulations, the Froude number varies between 0.015 and 0.05, while the Reynolds number and level of dispersion are varied in a broader range to span different regimes. In all cases, most of the energy in the system remains in the waves, even after integrating the system for very long times. For shallow flows, nonlinear waves are nondispersive and the spectrum of potential energy is compatible with ∼k{-2} scaling. For deeper (Boussinesq) flows, the nonlinear dispersion relation as directly measured from the wave and frequency spectrum (calculated independently) shows signatures of dispersion, and the spectrum of potential energy is compatible with predictions of weak turbulence theory, ∼k{-4/3}. In this latter case, the nonlinear dispersion relation differs from the linear one and has two branches, which we explain with a simple qualitative argument. Finally, we study probability density functions of the surface height and find that in all cases the distributions are asymmetric. The probability density function can be approximated by a skewed normal distribution as well as by a Tayfun distribution.
浅水模型和具有弱色散的布辛涅斯克模型。这两种模型的方程都是在具有多达2048²个点的周期性网格上求解的。在所有模拟中,弗劳德数在0.015至0.05之间变化,而雷诺数和色散水平在更广泛的范围内变化以跨越不同的 regime。在所有情况下,即使对系统进行很长时间的积分,系统中的大部分能量仍保留在波中。对于浅水流,非线性波是无色散的,势能谱与 ∼k⁻² 标度兼容。对于更深的(布辛涅斯克)水流,从波和频谱(独立计算)直接测量的非线性色散关系显示出色散特征,势能谱与弱湍流理论的预测 ∼k⁻⁴/³ 兼容。在后一种情况下,非线性色散关系与线性色散关系不同,有两个分支,我们用一个简单的定性论证来解释。最后,我们研究了表面高度的概率密度函数,发现在所有情况下分布都是不对称的。概率密度函数可以用偏态正态分布以及泰芬分布来近似。