4.5 Article Proceedings Paper

Strategies for turbulence modelling and simulations

Journal

INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
Volume 21, Issue 3, Pages 252-263

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/S0142-727X(00)00007-2

Keywords

turbulence; aerodynamics; simulation

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This is an attempt to clarify and size up the many levels possible for the numerical prediction of a turbulent flow, the target being a complete airplane, turbine, or car. Not all the author's opinions will be accepted, but his hope is to stimulate reflection, discussion, and planning. These levels still range from a solution of the steady Reynolds-Averaged Navier-Stokes (RANS) equations to a Direct Numerical Simulation, with Large-Eddy Simulation in between. However recent years have added intermediate strategies, dubbed VLES',URANS and DES. They are in experimental use and, although more expensive, threaten complex RANS models especially for bluff-body and similar flows. Turbulence predictions in aerodynamics face two principal challenges: (I) growth and separation of the boundary layer, and (II) momentum transfer after separation. (I) is simpler, but makes very high accuracy demands, and appears to give models of higher complexity little advantage. (II) is now the arena for complex RANS models and the newer strategies, by which time-dependent three-dimensional simulations are the norm even over two-dimensional geometries. In some strategies, grid refinement is aimed at numerical accuracy; in others it is aimed at richer turbulence physics. In some approaches, the empirical constants play a strong role even when the grid is very fine; in others, their role vanishes. For several decades, practical methods will necessarily be RANS, possibly unsteady, or RANS/LES hybrids, pure LES being unaffordable. Their empirical content will remain substantial, and the law of the wall will be particularly resistant. Estimates are offered of the grid resolution needed for the application of each strategy to full-blown aerodynamic calculations, feeding into rough estimates of its feasibility date, based an computing-power growth. (C) 2000 Elsevier Science Inc. All rights reserved.

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