Turbulence modeling by time-series methods
Data Analysis, Statistics and Probability
2012-05-31 v1 Fluid Dynamics
Abstract
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.
Cite
@article{arxiv.1205.6614,
title = {Turbulence modeling by time-series methods},
author = {Vincenzo Ferrazzano and Claudia Klüppelberg},
journal= {arXiv preprint arXiv:1205.6614},
year = {2012}
}
Comments
18 pages, 4 figures, submitted