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Published 2004 | Published
Book Section - Chapter Open

Dynamic modeling of α in the isotropic lagrangian averaged navier-stokes-α equations

Abstract

A dynamic procedure for the Lagrangian Averaged Navier- Stokes-α (LANS-α) equations is developed where the variation in the parameter α in the direction of anisotropy is determined in a self-consistent way from data contained in the simulation itself. In order to derive this model, the incompressible Navier-Stokes equations are Helmholtz-filtered at the grid and a test filter levels. A Germano type identity is derived by comparing the filtered subgrid scale stress terms with those given in the LANS-α equations. Assuming constant α in homogenous directions of the flow and averaging in these directions, results in a nonlinear equation for the parameter α, which determines the variation of α in the non-homogeneous directions or in time. Consequently, the parameter α is calculated during the simulation instead of a pre-defined value. As an initial test, the dynamic LANS-α model is used to compute isotropic homogenous forced and decaying turbulence, where α is constant over the computational domain, but is allowed to vary in time. The resulting simulations are compared with direct numerical simulations and with the LANS-α simulations using fixed value of α. As expected, α is found to change rapidly during the first eddy turn-over time during the simulations. It is also observed that by using the dynamic LANS-α procedure a more accurate simulation of the isotropic homogeneous turbulence is achieved. The energy spectra and the total kinetic energy decay are captured more accurately as compared with the LANS-α simulations using a fixed α. The current results suggest some promising applications of this dynamic LANS-α model, such as to a spatially varying turbulent flow, which we hope to undertake in future research.

Additional Information

© 2004 by ASME. The research in this paper was partially supported by the AFOSR contract F49620-02-1-0176. The authors would like to thank B. Kosovic for his initial help in the derivation of the dynamic model and T. Lund for helpful discussions.

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