Sensitivity analysis of large-eddy simulations to subgrid-scale-model parametric uncertainty using polynomial chaos

Abstract

We address the sensitivity of large-eddy simulations (LES) to parametric uncertainty in the subgrid-scale model. More specifically, we investigate the sensitivity of the LES statistical moments of decaying homogeneous isotropic turbulence to the uncertainty in the Smagorinsky model free parameter Cs (i.e. the Smagorinsky constant). Our sensitivity methodology relies on the non-intrusive approach of the generalized Polynomial Chaos (gPC) method; the gPC is a spectral non-statistical numerical method well-suited to representing random processes not restricted to Gaussian fields. The analysis is carried out at Reλ, =, 100 and for different grid resolutions and Cs distributions. Numerical predictions are also compared to direct numerical simulation evidence. We have shown that the different turbulent scales of the LES solution respond differently to the variability in Cs. In particular, the study of the relative turbulent kinetic energy distributions for different Cs distributions indicates that small scales are mainly affected by changes in the subgrid-model parametric uncertainty.