Buzzicotti Michele, Biferale Luca, Toschi Federico
Department of Physics and INFN, University of Rome "Tor Vergata," Via della Ricerca Scientifica 1, 00133 Rome, Italy.
Department of Applied Physics, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands and Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerche, 00185 Rome, Italy.
Phys Rev Lett. 2020 Feb 28;124(8):084504. doi: 10.1103/PhysRevLett.124.084504.
By means of high-resolution numerical simulations, we compare the statistical properties of homogeneous and isotropic turbulence to those of the Navier-Stokes equation where small-scale vortex filaments are strongly depleted, thanks to a nonlinear extra viscosity acting preferentially on high vorticity regions. We show that the presence of such smart small-scale drag can strongly reduce intermittency and non-Gaussian fluctuations. Our results pave the way towards a deeper understanding on the fundamental role of degrees of freedom in turbulence as well as on the impact of (pseudo)coherent structures on the statistical small-scale properties. Our work can be seen as a first attempt to develop smart-Lagrangian forcing or drag mechanisms to control turbulence.
通过高分辨率数值模拟，我们将均匀各向同性湍流的统计特性与纳维-斯托克斯方程的统计特性进行了比较。在纳维-斯托克斯方程中，由于一种优先作用于高涡度区域的非线性附加粘性，小尺度涡旋丝被强烈消耗。我们表明，这种智能小尺度阻力的存在可以显著降低间歇性和非高斯涨落。我们的结果为更深入理解湍流中自由度的基本作用以及（伪）相干结构对统计小尺度特性的影响铺平了道路。我们的工作可被视为开发智能拉格朗日强迫或阻力机制以控制湍流的首次尝试。
