Boffetta G., Celani A., Cencini M., Lacorata G., Vulpiani A.
Dipartimento di Fisica Generale and Istituto Nazionale Fisica della Materia, Universita di Torino, Via Pietro Giuria 1, 10125 Torino, Italy.
Chaos. 2000 Mar;10(1):50-60. doi: 10.1063/1.166475.
We study relative dispersion of passive scalar in nonideal cases, i.e., in situations in which asymptotic techniques cannot be applied; typically when the characteristic length scale of the Eulerian velocity field is not much smaller than the domain size. Of course, in such a situation usual asymptotic quantities (the diffusion coefficients) do not give any relevant information about the transport mechanisms. On the other hand, we shall show that the Finite Size Lyapunov Exponent, originally introduced for the predictability problem, appears to be rather powerful in approaching the nonasymptotic transport properties. This technique is applied in a series of numerical experiments in simple flows with chaotic behaviors, in experimental data analysis of drifter and to study relative dispersion in fully developed turbulence. (c) 2000 American Institute of Physics.
我们研究非理想情况下被动标量的相对扩散，即无法应用渐近技术的情形；通常是当欧拉速度场的特征长度尺度不比域大小小很多时。当然，在这种情况下，通常的渐近量（扩散系数）并不能给出关于输运机制的任何相关信息。另一方面，我们将表明，最初为可预测性问题引入的有限尺寸李雅普诺夫指数，在处理非渐近输运性质方面似乎相当强大。该技术应用于一系列具有混沌行为的简单流动的数值实验、漂流器的实验数据分析以及研究充分发展湍流中的相对扩散。（c）2000美国物理研究所。
