A scale-dependent dynamic model for large-eddy simulation: application to a neutral atmospheric boundary layer

Abstract

A scale-dependent dynamic subgrid-scale model for large-eddy simulation of turbulent flows is proposed. Unlike the traditional dynamic model, it does not rely on the assumption that the model coefficient is scale invariant. The model is based on a second test-filtering operation which allows us to determine from the simulation how the coefficient varies with scale. The scale-dependent model is tested in simulations of a neutral atmospheric boundary layer. In this application, near the ground the grid scale is by necessity comparable to the local integral scale (of the order of the distance to the wall). With the grid scale and/or the test-filter scale being outside the inertial range, scale invariance is broken. The results are compared with those from (a) the traditional Smagorinsky model that requires specification of the coefficient and of a wall damping function, and (b) the standard dynamic model that assumes scale invariance of the coefficient. In the near-surface region the traditional Smagorinsky and standard dynamic models are too dissipative and not dissipative enough, respectively. Simulations with the scale-dependent dynamic model yield the expected trends of the coefficient as a function of scale and give improved predictions of velocity spectra at different heights from the ground. Consistent with the improved dissipation characteristics, the scale-dependent model also yields improved mean velocity profiles.

The Effect of Filter Dimension on the Subgrid-Scale Stress, Heat Flux, and Tensor Alignments in the Atmospheric Surface Layer

“…Now both two-and three-dimensional filterings give similar results in both magnitude and structure. Note that all previous experiments and analyses (Tong et al 1999(Tong et al , 1998Porté-Agel et al 1998, 2000a,b, 2001aHiggins et al 2003;Horst et al 2004;Kleissl et al 2003) are performed with the two-dimensional horizontal filtering technique.…”

“…To investigate the characteristics of subgridscale (SGS) variables and to evaluate closure models for large eddy simulation (LES), several field experiments have recently been performed in the atmospheric surface layer using various horizontal arrays of sonic anemometers (Tong et al 1999(Tong et al , 1998Porté-Agel et al 2000a,b, 2001aHiggins et al 2003Higgins et al , 2004Horst et al 2004;Kleissl et al 2003Kleissl et al , 2004Sullivan et al 2003). In these experiments, two-dimensional filtering was used to compute the components of the SGS stress tensor.…”

Fine‐scale modeling of the boundary layer wind field over steep topography

“…The numerical formulation of an appropriate SGS model is a matter of current research [e.g., Kumar et al, 2006;Chamecki et al, 2006]. While dynamic SGS models are very important in creating a correct nearsurface flow over flat terrain [Porté-Agel et al, 2000] or help in finding correct roughness parameterizations for heterogeneous terrain [Bou-Zeid et al, 2007], the current study focuses on the reconstruction of mean flow characteristics in very steep terrain using a standard 1.5-order TKE closure. The same approach has successfully been used in other studies involving steep terrain [e.g., Chow et al, 2006].…”

Evaluation of subgrid-scale models in large-eddy simulation of flow past a two-dimensional block

“…In this study, we test the performance of the Lagrangian scaledependent dynamic model (Porté-Agel et al, 2000;Stoll and Porté-Agel, 2006a) and the modulated gradient model (Lu and Porté-Agel, 2010) to study the flow past a two-dimensional (2D) block. This validation case is chosen because 2D block is commonly considered as an idealized building due to its simplicity in geometry, while still possessing the basic characteristics of a building block.…”

“…The scale-dependent dynamic model (Porté-Agel et al, 2000) was developed in order to generalize the standard dynamic model to include scale dependence. To achieve this, a secondary test filter is applied to determine the scale-dependence factor b C 2 s ð2DÞ= C 2 s ðDÞ.…”