4.7 Article

Kolmogorov similarity scaling for one-particle Lagrangian statistics

Journal

PHYSICS OF FLUIDS
Volume 23, Issue 9, Pages -

Publisher

AMER INST PHYSICS
DOI: 10.1063/1.3643852

Keywords

convergence of numerical methods; extrapolation; flow simulation; laminar flow; statistical analysis; stochastic processes

Funding

  1. National Science Foundation [CBET-0553867, 1139037]
  2. Div Of Chem, Bioeng, Env, & Transp Sys
  3. Directorate For Engineering [1139037] Funding Source: National Science Foundation

Ask authors/readers for more resources

We use direct numerical simulation data up to a Taylor scale Reynolds number R-lambda = 1000 to investigate Kolmogorov similarity scaling in the inertial sub-range for one-particle Lagrangian statistics. Although similarity scaling is not achieved at these Reynolds numbers for the Lagrangian velocity structure function, we show clearly that it is achieved for the Lagrangian acceleration frequency spectrum and the scaling range becomes wider with increasing Reynolds number. Stochastic and heuristic model calculations suggest that the difference in behavior observed for the structure function and spectrum is simply a consequence of different rates of convergence to scaling behavior with increasing Reynolds number. Our estimate C-0 approximate to 6.9 +/- 0.2 for the Lagrangian structure function constant is close to earlier estimates based on extrapolation of the peak value of the compensated structure function. The results presented here suggest prospects for studying Kolmogorov similarity for Lagrangian statistics using the latest innovations in simulation, and measurement techniques are more hopeful than previously suggested in the literature. (C) 2011 American Institute of Physics. [doi:10.1063/1.3643852]

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available