Turbulence modeling by time-series methods
classification
⚛️ physics.data-an
physics.flu-dyn
keywords
hypothesismodelmodelingorderseparatestationarystatisticsturbulence
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A general model for stationary, time-wise turbulent velocity is presented and discussed. This approach, inspired by modeling ideas of Barndorff-Nielsen and Schimgel, is coherent with the K41 hypothesis of local isotropy, and it allows us to separate second-order statistics from higher order ones. The model can be motivated by Taylor's hypothesis and a relation between time and spatial spectra. Second order statistics are used to separate the deterministic kernel function and the weakly stationary driving noise. A non-parametric estimation method for the turbulence intermittency is suggested.
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