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Conditional Statistics Along Gradient Trajectories in Fluid Turbulence

In: High Performance Computing in Science and Engineering '09

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  • Lipo Wang

    (RWTH-Aachen, Institut für Technische Verbrennung)

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.

Suggested Citation

  • Lipo Wang, 2010. "Conditional Statistics Along Gradient Trajectories in Fluid Turbulence," Springer Books, in: Wolfgang E. Nagel & Dietmar B. Kröner & Michael M. Resch (ed.), High Performance Computing in Science and Engineering '09, pages 265-272, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-04665-0_19
    DOI: 10.1007/978-3-642-04665-0_19
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