Surfacesampled simulations of turbulent flow at high Reynolds number
Abstract
A new approach to turbulence simulation, based on a combination of largeeddy simulation (LES) for the whole flow and an array of nonspacefilling quasidirect numerical simulations (QDNS), which sample the response of nearwall turbulence to largescale forcing, is proposed and evaluated. The technique overcomes some of the cost limitations of turbulence simulation, since the main flow is treated with a coarsegrid LES, with the equivalent of wall functions supplied by the nearwall 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 nearwall turbulence levels due to a modulation of nearwall streaks by largescale 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, LESQDNS coupling strategy and subgrid 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:

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:

 Physics  Fluid Dynamics;
 Computer Science  Computational Engineering;
 Finance;
 and Science;
 Physics  Computational Physics
 EPrint:
 Author accepted version. Accepted for publication in the International Journal for Numerical Methods in Fluids on 26 April 2017