论文标题

极端事件会触发湍流衰减吗? - 管流中湍流衰减时间的数值研究

Do extreme events trigger turbulence decay? - a numerical study of turbulence decay time in pipe flows

论文作者

Nemoto, Takahiro, Alexakis, Alexandros

论文摘要

在层流管流中局部产生的湍流显示出在随机等待时间后突然腐烂或分裂。在实验室实验中,观察到的平均等待时间是随着雷诺数(RE)接近其临界值而增加双重指数的。为了了解这种双指数增加的起源,我们执行许多管道流动的直接数值模拟,并测量管道上最大轴向涡度场的累积直方图(湍流强度)。在湍流强度并不小的域中,我们观察到直方图被牙龈高度值分布良好。该域中的最小湍流强度大致对应于局部稳定的湍流与元稳定(边缘)状态之间的过渡值。在研究此分布中拟合参数的依赖性时,我们得出了这两个状态之间过渡的时间尺度随着RE接近其临界价值而增加双重指数。相反,在该域以下较小的湍流强度中,我们观察到该分布对RE的变化不明智。这意味着元稳定状态(到层状状态)的衰减时间是随机的,但平均是重新独立。我们的观察表明,Goldenfeld等人做出的猜想。在我们研究的RE范围内,满足了湍流衰减时间的双指数增加。我们还讨论了另一个极值分布,即Fréchet分布,而不是牙龈分布,以近似湍流的直方图加剧,这揭示了有趣的观点。

Turbulence locally created in laminar pipe flows shows sudden decay or splitting after a stochastic waiting time. In laboratory experiments, the mean waiting time was observed to increase double-exponentially as the Reynolds number (Re) approaches its critical value. To understand the origin of this double-exponential increase, we perform many pipe flow direct numerical simulations of the Navier-Stokes equations, and measure the cumulative histogram of the maximum axial vorticity field over the pipe (turbulence intensity). In the domain where the turbulence intensity is not small, we observe that the histogram is well-approximated by the Gumbel extreme-value distribution. The smallest turbulence intensity in this domain roughly corresponds to the transition value between the locally stable turbulence and a meta-stable (edge) state. Studying the Re dependence of the fitting parameters in this distribution, we derive that the time scale of the transition between these two states increases double-exponentially as Re approaches its critical value. On the contrary, in smaller turbulence intensities below this domain, we observe that the distribution is not sensible to the change of Re. This means that the decay time of the meta-stable state (to the laminar state) is stochastic but Re-independent in average. Our observation suggests that the conjecture made by Goldenfeld et al. to derive the double-exponential increase of turbulence decay time is approximately satisfied in the range of Re we studied. We also discuss using another extreme-value distribution, Fréchet distribution, instead of the Gumbel distribution to approximate the histogram of the turbulence intensify, which reveals interesting perspectives.

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