**
Eulerian and Lagrangian statistics from particle tracking data
**

**Jakob Mann and Søren Ott**

*
Wind Energy Department, Risø National Laboratory, Denmark*

jakob.mann@risoe.dk

**ABSTRACT:**

Several hundreds flow-following particles are tracked with video cameras in
approximately homogeneous and isotropic turbulence generated between
oscillating grids. From these data several interesting statistical
properties of turbulence can be inferred. The mean square separation of
particles initially located close to each other will, according to
Richardson and Obukhov, increase as
C t^{3}, where
is the
energy dissipation, as long as the separation is smaller than the
integral scale.
The constant C is determined to be approximately 0.5.
Theoretical predictions of C range from 0.01 (from kinematic simulation)
to more than 5 (Kraichnan).
We attempt to explain why kinematic simulation gives a too small C.
The spatio-temporal Eulerian velocity correlation R_{E}(x,t) is
compared to models, and the Corrsin hypothesis relating this to the
Lagrangian autocorrelation function R_{L}(t) is tested.