Investigation of the effects of subgrid-scale turbulence on resolvable-scale statistics

The effects of the subgrid-scale (SGS) turbulence on the resolvable-scale statistics as well as the effects of SGS models on large-eddy simulation (LES) are studied. It is shown that the SGS turbulence evolves the resolvable-scale joint probability density function (JPDF) through the conditional means of the SGS stress, the SGS scalar flux, and their production rate, which must be reproduced by the SGS model for LES to predict correctly the one-point resolvable-scale statistics, a primary goal of LES. This necessary condition is used as the basis for studying SGS physics and for testing SGS models. Theoretical predictions, measurements data, and numerical simulation results are combined to investigate the effects of filter size, the dependence of the SGS turbulence on the flow dynamics, and SGS models performance using new a priori and a posteriori tests developed in this research.; For inertial-range filter scales, LES statistics of the energy- and flux-containing scales are generally considered to be insensitive to the SGS model employed. To examine this premise, the effects of the subgrid-scale (SGS) velocity, scalar, and SGS models on the resolvable-scale velocity-scalar joint probability density function (JPDF) are studied. The mean SGS stress and SGS scalar flux production rate is predicted using Lumley's assumption (Lumley 1967), which is consistent with Kolmogorov's hypothesis. Analyses of these statistics using data obtained in a slightly heated turbulent jet show that the mean SGS stress, SGS scalar flux, and their production rates have filter-scale dependencies consistent with predictions, suggesting that the SGS turbulence has diminishing influence on the lower-order resolvable-scale statistics for inertial-range filter scales and supporting the premise of LES at the level of lower-order statistics. The measured conditional SGS stress and SGS flux as well as the conditional production rates have a strong dependence on the resolvable-scale velocity and scalar, indicating strong flow history effects, and decrease much slower than the predicted filter dependencies, indicating that the SGS turbulence has non-trivial effects on the high-order resolvable-scale statistics even for inertial-range filter scales.; For energy-containing filter scales, previous studies have shown that LES results depend strongly on the SGS models. To study the effects of the SGS turbulence on the resolvable-scale velocity statistics for such filter scales, the SGS stress in the atmospheric surface layer is studied using measurement data (HATS 2000). Analysis of the conditional SGS stress and the conditional stress production rate conditional on the resolvable-scale velocity show that both buoyancy and shear play important roles in the physics of the SGS stress. Strong buoyancy and vertical shear associated with updrafts and positive streamwise velocity fluctuations cause conditional forward energy transfer and strong anisotropy in the conditional SGS stress. Downward returning flows associated with large convective eddies result in much less anisotropic SGS stress and conditional energy backscatter. Predictions of the conditional SGS stress and the conditional stress production rate predicted using several SGS models are compared with measurements. None of the models tested are able to predict correctly the trends of both statistics. The deficiencies of the SGS models that cause inaccurate LES statistics, such as the over-prediction of the mean shear and under-prediction of the vertical velocity skewness, are identified.; To study the effects of the SGS turbulence on the resolvable-scale velocity-scalar statistics for energy-containing filter scales, the SGS scalar flux in the atmospheric surface layer is studied using field measurements data. The results show that the conditional scalar flux and its production rate depend on the resolvable-scale velocity and temperature fluctuations, suggesting that these conditional variables have strong inf...