Stochastic Estimation of the Structure of Turbulent Fields
Stochastic Estimation of the Structure of Turbulent Fields
复制标题
DOI：
10.1007/978-3-7091-2676-9_3
复制
发表时间：
1996
期刊：
影响因子：
--
通讯作者：
R. Adrian
中科院分区：
文献类型：
--
作者：
R. Adrian
随机估计方法是根据给定的事件数据，通过近似平均场来导出结构。估计的场满足连续性方程，并且具有正确的长度和/或时间尺度。讨论了一般随机估计的基本概念及其在条件平均估计中的具体应用。本文发展了随机场及其条件平均的线性随机估计作为主要工具，并证明了其准确性。线性随机估计可以用给定事件数据与被估计量之间的二阶相关函数表示。这在条件平均、它们所代表的连贯结构和相关函数之间建立了一个简单的联系。通过考虑越来越复杂的事件：单点向量、两点向量、局部变形张量、多点向量、时空向量和空间波数事件，探讨了选择事件和解释给定事件集的估计的相关问题。导出了一般的运动学和统计性质，描述了各种类型湍流的随机估计结构，并将其与底层相干结构联系起来。
The stochastic estimation method educes structure by approximating an average field in terms of event data that are given. The estimated fields satisfy the continuity equation, and they possess the correct scales of length and/or time. The fundamental concepts of general stochastic estimation and the specific application of this technique to the estimation of conditional averages are discussed. Linear stochastic estimation of random fields and of their conditional averages is developed as the principal tool, and its accuracy is demonstrated. The linear stochastic estimate is expressible in terms of second order correlation functions between the given event data and the quantity being estimated. This establishes a simple link between conditional averages, the coherent structure that they represent and correlation functions. The related problems of selecting events and interpreting the estimates that result from a given set of events are explored by considering events of increasing complexity: single-point vectors, two-point vectors, local deformation tensors, multi-point vectors, space-time vectors, and space-wave-number events. General kinematic and statistical properties are derived, and stochastically estimated structures from various types of turbulent flows are described and related to the underlying coherent structures.