Will RANS Survive LES? A View of Perspectives

[+] Author and Article Information
K. Hanjalic

Thermal and Fluids Sciences, Department of Multi-scale Physics, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlandshanjalic@ws.tn.tudeft.nl

J. Fluids Eng 127(5), 831-839 (Sep 01, 2005) (9 pages) doi:10.1115/1.2037084 History:

The paper provides a view of some developments and a perspective on the future role of the Reynolds-averaged Navier-Stokes (RANS) approach in the computation of turbulent flows and heat transfer in competition with large-eddy simulations (LES). It is argued that RANS will further play an important role, especially in industrial and environmental computations, and that the further increase in the computing power will be used more to utilize advanced RANS models to shorten the design and marketing cycle rather than to yield the way to LES. We also discuss some current and future developments in RANS aimed at improving their performance and range of applicability, as well as their potential in hybrid approaches in combination with the LES strategy. Limitations in LES at high Reynolds (Re) and Rayleigh (Ra) number flows and heat transfer are revisited and some hybrid RANS/LES routes are discussed. The potential of very large eddy simulations (VLES) of flows dominated by (pseudo)-deterministic eddy structures, based on transient RANS (T-RANS) and similar approaches, is discussed and illustrated in an example of “ultra-hard” (very high Ra) thermal convection.

Copyright © 2005 by American Society of Mechanical Engineers
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Figure 1

A conjectured prospect on utilization of the available computing power by different computational approaches

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Figure 2

Instantaneous temperature on the cube surface (above) and thermal plumes around the cube, defined by the isosurface of T=24.5°C (below). (a) view from the front, (b) view from the back. The flow is in the x direction (8).

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Figure 3

Velocity vectors in the midplane of a DOHC IC engine at CA=120°, 3D RANS (18). Left: k-ε; right: SMC.

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Figure 4

Nozzle configuration and computational view of streamlines and surface temperature

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Figure 5

Velocity vectors in a plane at z∕D=0.54 above the impinging plane. Top: k-ε+WF (left), EBM (right); bottom: k-v2-f (left), PIV measurements (right) (28).

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Figure 6

Nusselt number predicted by different models. Top: k-ε+WF (left), EBM+GGDH (right); bottom: k-v2-f (left), LCT measurements (right) (28).

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Figure 7

Nusselt number distribution across the jets centerlines for two locations (28)

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Figure 8

Hybrid RANS (v2-f)+LES (dynamic sgs) velocity in a plane channel (38). A, B, and C indicate three different Re numbers, and 1 and 2 indicate two different grids.

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Figure 9

T-RANS predictions of Nu number (above) and of hydrodynamic (λν) and thermal (λθ) wall layer thickness (bellow) in R-B convection over ten decades of Ra number (40)

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Figure 10

T-RANS instantaneous trajectories in R-B convection for Ra=2×1014(Pr=0.71). Left: at midplane (z∕H=0.5); right: close to the top wall (z∕H=0.925)(40).




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