A time self-adaptive multilevel algorithm for large-eddy simulation

An extension of the multilevel method applied to LES proposed in Terracol et al. [J. Comput. Phys. 167 (2001) 439] is introduced here to reduce the CPU times in unsteady simulation of turbulent flows. Flow variables are decomposed into several wavenumber bands, each band being associated to a computational grid in physical space. The general framework associated to such a decomposition is presented, and a new adapted closure is proposed for the subgrid terms which appear at each filtering level, while the closure at the finest level is performed with a classical LES model. CPU time saving is obtained by the use of V-cycles, as in the multigrid terminology. The main part of the simulation is thus performed on the coarse levels, while the smallest resolved scales are kept frozen (quasi-static approximation [Comput. Methods Appl. Mech. Engrg. 159 (1998) 123]). This allows to reduce significantly the CPU times in comparison with classical LES, while the accuracy of the simulation is preserved by the use of a fine discretization level. To ensure the validity of the quasi-static approximation, a dynamic evaluation of the time during which it remains valid is performed at each level through an a priori error estimation of the small-scales time variation. This leads to a totally self-adaptive method in which both the number of levels and the integration times on each grid level are evaluated dynamically. The method is assessed on a fully unsteady time-developing compressible mixing layer at a low-Reynolds number for which a DNS has also been performed, and in the inviscid case. Finally, a plane channel flow configuration has been considered. In all cases, the results obtained are in good agreement with classical LES performed on a fine grid, with CPU time reduction factors of up to five.