A New Approach to LES Modeling
Abstract
Large eddy simulation (LES) is a promising technique for the prediction of turbulent fluid flows of practical interest. In LES, the largest scales of turbulence are simulated while the effects of the discarded small scales are modeled. However, there are important flow situations, such as turbulence near walls, that current LES techniques do not simulate reliably. In a new approach to LES modeling, stochastic estimation techniques are used to formally optimize the LES model. This yields an approximation to the ideal LES evolution, which is guaranteed to reproduce the single-time statistics of the filtered turbulence, and to minimize the expected difference between the evolution of a filtered turbulence and the LES. Using direct numerical simulation (DNS) statistical data to perform the estimates, several such models have been formulated for different turbulent flows and different LES filter definitions. These models perform remarkably well. They also yield important insights into the required properties of good LES models. To make these models useful however, it is necessary to eliminate the need for detailed statistical data from DNS. When the small scales are assumed isotropic, this can be accomplished through a combination of Kolmogorov inertial range scaling, the quasi-normal approximation and a dynamic procedure, and the resulting model is as accurate as that based on DNS data. Near walls, a variety of other theoretical considerations significantly constrain the required statistics, and using this, a formulation requiring minimal empirical input is being devised.
- Publication:
-
APS Division of Fluid Dynamics Meeting Abstracts
- Pub Date:
- November 2003
- Bibcode:
- 2003APS..DFD.GB001M