Autonomic Closure for Large Eddy Simulations

Abstract

Motivated by the application of adjoint techniques for rapidly solving large optimization problems, a fundamentally new autonomic closure is discussed that allows an essentially model-free, dynamic subgrid-scale closure for large eddy simulations (LES). The autonomic closure addresses nonlinear, nonlocal, and nonequilibrium turbulence effects and, in its most general form, is based on all possible tensorally-invariant, dimensionally-consistent relations between the local subgrid-stress tensor and resolved scale primitive variables. This introduces a large matrix of spatially and temporally varying coefficients that can be optimized using a test filter approach and then applied at the LES filter scale by invoking scale similarity. The autonomic closure is intended to avoid the need to specify a model for the subgrid stresses, and instead allows the simulation itself to determine the best local relation between the subgrid stresses and resolved state variables. A priori tests of this approach are presented using data from direct numerical simulations of homogeneous isotropic turbulence, and application of the closure to practical simulations is discussed.

RYAN KING

National Renewable Energy Laboratory