Surface-sampled simulations of turbulent flow at high Reynolds number
Abstract
A new approach to turbulence simulation, based on a combination of large-eddy simulation (LES) for the whole flow and an array of non-space-filling quasi-direct numerical simulations (QDNS), which sample the response of near-wall turbulence to large-scale forcing, is proposed and evaluated. The technique overcomes some of the cost limitations of turbulence simulation, since the main flow is treated with a coarse-grid LES, with the equivalent of wall functions supplied by the near-wall sampled QDNS. Two cases are tested, at friction Reynolds number Re$_\tau$=4200 and 20,000. The total grid node count for the first case is less than half a million and less than two million for the second case, with the calculations only requiring a desktop computer. A good agreement with published DNS is found at Re$_\tau$=4200, both in terms of the mean velocity profile and the streamwise velocity fluctuation statistics, which correctly show a substantial increase in near-wall turbulence levels due to a modulation of near-wall streaks by large-scale structures. The trend continues at Re$_\tau$=20,000, in agreement with experiment, which represents one of the major achievements of the new approach. A number of detailed aspects of the model, including numerical resolution, LES-QDNS coupling strategy and sub-grid model are explored. A low level of grid sensitivity is demonstrated for both the QDNS and LES aspects. Since the method does not assume a law of the wall, it can in principle be applied to flows that are out of equilibrium.
- Publication:
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International Journal for Numerical Methods in Fluids
- Pub Date:
- November 2017
- DOI:
- 10.1002/fld.4395
- arXiv:
- arXiv:1704.08368
- Bibcode:
- 2017IJNMF..85..525S
- Keywords:
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- Physics - Fluid Dynamics;
- Computer Science - Computational Engineering;
- Finance;
- and Science;
- Physics - Computational Physics
- E-Print:
- Author accepted version. Accepted for publication in the International Journal for Numerical Methods in Fluids on 26 April 2017