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arXiv physics/0312113physics.flu-dyncond-mat
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湍流能量级联generator的数据驱动推导

Data-driven derivation of the turbulent energy cascade generator

J. Cleve, T. Dziekan, J. Schmiegel, O. E. Barndorff-Nielsen, B. R. Pearson, K. R. Sreenivasan, M. Greiner

摘要:

在充分发展的湍流的随机乘性能量级联模型的框架内,推导出两点扩散器和累积量的表达式,同时考虑到从超度量到欧几里得两点距离的适当转换。从各种风洞和大气边界层记录中提取的替代能量耗散与两点统计的比较,允许多尺度指数和累积量的精确推导。这些指数作为概率级联发生器的参数估计的输入。

英文摘要:

Within the framework of random multiplicative energy cascade models of fully developed turbulence, expressions for two-point correlators and cumulants are derived, taking into account a proper conversion from an ultrametric to an Euclidean two-point distance. The comparison with two-point statistics of the surrogate energy dissipation, extracted from various wind tunnel and atmospheric boundary layer records, allows an accurate deduction of multiscaling exponents and cumulants. These exponents serve as the input for parametric estimates of the probabilistic cascade generator.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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