Inproceedings,
Conditional Statistics Along Gradient Trajectories in Fluid Turbulence
High Performance Computing in Science and Engineering '09, 5, page 265-272. (2010)
Abstract
To investigate turbulent flows, direct numerical simulations (DNS) is playing more and more important roles benefitting from the modern computing technologies. Once the DNS data are obtained, according to different theory and purposes, the data analysis will be the core of the work at next stages. From the sizable capacity data for homogeneous shear turbulence, the conditional statistics along gradient trajectories have been investigated. It has been derived and also proved numerically that the two-point velocity difference structure functions along the same gradient trajectories have a linear scaling with respect to the arclength between the two points, different from the classical Kolmogorov scaling. In addition, the performance of the OpenMP parallelized code is satisfactory.
