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Organized structures, memory, and the decay of turbulence

机译:有组织的结构,记忆和湍流的衰减

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The rapid increase in computational power has led to an unprecedented enhancement of our ability to study the behavior of complex systems in the physical, biological, and social sciences. However, there are still many systems that are too complex to tackle. A turbulent fluid is the archetypal example of such a complex system. Its complexity is manifested as the appearance of organized structures across all of the scales available to a turbulent fluid. Thus, the task that a numerical analyst working on turbulence faces is to reduce the complexity of the problem into something manageable, which at the same time preserves the essential features of the problem. Although much knowledge about the Eu-ler and Navier-Stokes equations has accumulated over the years (1-8), it has proven very difficult to incorporate this knowledge in the construction of effective models. The work of Hald and Stinis (9) in this issue of PNAS is an attempt toward the construction of an effective model that utilizes qualitative information about the structure of a turbulent flow. The work in ref. 9 rests on the idea that the organization of a fluid flow in vortices leads to "long memory" effects, i.e., the motion of a vortex at one scale is influenced by the past history of the motion of vortices in other scales. This line of thought first appeared in the work of Alder and Wain-wright (ref. 10; see also ref. 11 for a recent review on memory and problem reduction).
机译:计算能力的迅速提高导致我们研究物理,生物和社会科学中复杂系统行为的能力得到空前提高。但是,仍然有许多系统太复杂而无法解决。湍流的流体就是这种复杂系统的典型例子。它的复杂性表现为在湍流流体可利用的所有尺度上有组织的结构的出现。因此,从事湍流研究的数值分析人员所面临的任务是将问题的复杂性降低到可管理的水平,同时保留问题的基本特征。尽管多年来(1-8年)积累了许多关于Eu-ler和Navier-Stokes方程的知识,但是事实证明,将这些知识整合到有效模型的构建中非常困难。在本期PNAS中,Hald和Stinis(9)的工作试图建立一种有效的模型,该模型利用有关湍流结构的定性信息。参考文献中的工作。图9基于这样的思想,即涡流中的流体流动的组织导致“长时间记忆”效应,即,一个尺度上的涡流的运动受到其他尺度上的涡流运动的过去历史的影响。这种思想首先出现在Alder和Wain-wright的著作中(参考文献10;关于记忆和减少问题的最新评论,另见参考文献11)。

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