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An extended view of the inner-outer interaction model for wall-bounded turbulence using spectral linear stochastic estimation

机译:光谱线性随机估计的壁限湍流内外交互模型的延长视图

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Streamwise velocity fluctuations in the inner-region of wall-bounded turbulent flows can be predicted by the model of Marusic, Mathis & Hutchins (2010). Only a single large-scale velocity signal from an outer position in the logarithmic region is needed for the model, and all other parameters are determined from a once-off calibration experiment. Here we elucidate part of the model by investigating the scale-dependent coherence magnitude and phase throughout the boundary layer. The collection of coherent scales exhibits a shift with respect to the reference position that is shown to be independent of scale;; thus the large-scales are non-dispersive. Because these scales comprise a strong coherence, their signature in the inner-region is predicted from an input signal acquired at the geometric center of the log-region. Previously this was achieved via single-time stochastic estimation. Here we leverage the inherent advantages of spectral linear stochastic estimation for the prediction of these large-scales.
机译:通过Marusic,Mathis&Hutchins(2010)的模型可以预测壁限湍流流的内部区域中的流动速度波动。对于模型,仅需要来自对数区域中的外部位置的单个大规模速度信号,并且从一次关闭校准实验确定所有其他参数。在这里,我们通过在整个边界层中调查尺度相关的相干幅度和相位来阐明模型的一部分。相干尺度的集合表现出相对于参考位置的转变,该位置被呈现为尺度独立;因此,大规模是非分散的。因为这些尺度包括强的相干性,所以从在日志区域的几何中心获取的输入信号预测其在内部区域中的签名。以前这是通过单时间随机估计来实现的。在这里,我们利用光谱线性随机估计来预测这些大尺度的固有优点。

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