Explicit Subgrid-scale Model Research Articles

Assessment of localized artificial diffusivity scheme for large-eddy simulation of compressible turbulent flows

The localized artificial diffusivity method is investigated in the context of large-eddy simulation of compressible turbulent flows. The performance of different artificial bulk viscosity models are evaluated through detailed results from the evolution of decaying compressible isotropic turbulence with eddy shocklets and supersonic turbulent boundary layer. Effects of subgrid-scale (SGS) models and implicit time-integration scheme/time-step size are also investigated within the framework of the numerical scheme used. The use of a shock sensor along with artificial bulk viscosity significantly improves the scheme for simulating turbulent flows involving shocks while retaining the shock-capturing capability. The proposed combination of Ducros-type sensor with a negative dilatation sensor removes unnecessary bulk viscosity within expansion and weakly compressible turbulence regions without shocks and allows it to localize near the shocks. It also eliminates the need for a wall-damping function for the bulk viscosity while simulating wall-bounded turbulent flows. For the numerical schemes used, better results are obtained without adding an explicit SGS model than with SGS model at moderate Reynolds number. Inclusion of a SGS model in addition to the low-pass filtering and artificial bulk viscosity results in additional damping of the resolved turbulence. However, investigations at higher Reynolds numbers suggest the need for an explicit SGS model. The flow statistics obtained using the second-order implicit time-integration scheme with three sub-iterations closely agrees with the explicit scheme if the maximum Courant–Friedrichs–Lewy is kept near unity.

Implicit Large-Eddy Simulation in Meteorology: From Boundary Layers to Climate

The dynamics of the atmosphere and oceans pose a severe challenge to the numerical modeler, due in large part to the broad range of scales of length and time that are encompassed. Modern numerical methods based on nonoscillatory finite volume (NFV) approximations provide a simple and effective means for mitigating this challenge by reproducing the large scale behavior of turbulent flows with no need for explicit subgrid-scale models. In this paper, we describe the remarkable properties of a particular NFV model, multidimensional positive definite advection transport algorithm, and highlight its application to a variety of meteorological and turbulent flows.

Simulation of transition and turbulence decay in the Taylor–Green vortex

Conventional large-eddy simulation (LES) and monotone integrated LES (MILES) are tested in emulating the dynamics of transition to turbulence in the Taylor–Green vortex (TGV). A variety of subgrid scale (SGS) models and high-resolution numerical methods are implemented in the framework of both incompressible and compressible fluid flow equations. Comparisons of the evolution of characteristic TGV integral measures are made with previously reported and new direct numerical simulation (DNS) data. The computations demonstrate that the convective numerical diffusion effects in the MILES methods can consistently capture the physics of flow transition and turbulence decay without resorting to an explicit SGS model, while providing accurate prediction of established theoretical findings for the kinetic energy dissipation, energy spectra, enstrophy and kinetic energy decay. All approaches tested provided fairly robust computational frameworks.

Impact of Subgrid-Scale Models on Jet Turbulence and Noise

Introduction V ISBAL and Rizzetta1 and Visbal et al.2 have recently performed large-eddy simulation (LES) calculations of turbulent channel flow and compressible isotropic turbulence decay without using any explicit subgrid-scale (SGS) model. In those simulations, spatial filtering was treated as an implicit SGS model. They also showed that use of an SGS model in those simulations did not produce results superior to those obtained without employing an SGS model. Bogey and Bailly3 also performed LES calculations for jet flows by using spatial filtering only. Moreover, they brought up the issue of the effects of the eddy–viscosity-based Smagorinsky SGS model on jet noise in yet another recent study.4,5 They showed that the high-frequency portion of the noise spectra was significantly suppressed by the eddy–viscosity. It is well understood that in turbulent flows the energy cascade is associated with a mean flux of energy that is directed from large scales toward small scales. The large scales contain the major part of the turbulent kinetic energy, and they continuously feed the turbulent kinetic energy via the cascade to the smallest eddies where it is dissipated. Because the grid resolution is too coarse to resolve all of the relevant length scales in an LES, the pile-up of energy at high wave numbers can be eliminated through the use of a spatial filter. Hence, the spatial filter can be thought of as an effective SGS model in an LES. In this study, we perform two jet simulations to study the impact of the SGS model on jet turbulence and far-field noise. The first simulation does not employ any explicit SGS model, but treats the spatial filter as an implicit SGS model. In the second simulation, we employ a localized version of the dynamic Smagorinsky model (DSM) (see Ref. 6) and keep all test case parameters the same as those in the first simulation. We examine the differences between the two simulations to quantify the effect of the SGS model on the near-field jet turbulence and the far-field noise. Although this study is similar to those done by Bogey and Bailly,4,5 our work additionally does a comparison of the two LES results with experimental jet noise spectra with the hope

Implicit subgrid‐scale modeling by adaptive local deconvolution

AbstractA class of implicit Subgrid‐Scale (SGS) models for Large‐Eddy Simulation (LES) is obtained from a new approach for the finite‐volume discretization of hyperbolic conservation laws. The extension of a standard deconvolution operator and the choice of a suitable numerical flux function result in a truncation error which can be forced to have physical significance. As determined by a modified‐differential‐equation analysis, the free parameters of this implicit SGS model can be adjusted to approximate a known explicit SGS model. Computational results for the viscous Burgers equation show that the model with parameters identified by evolutionary optimization gives significantly better predictions than other models. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Implicit subgrid-scale modeling by adaptive deconvolution

A new approach for the construction of implicit subgrid-scale models for large-eddy simulation based on adaptive local deconvolution is proposed. An approximation of the unfiltered solution is obtained from a quasi-linear combination of local interpolation polynomials. The physical flux function is modeled by a suitable numerical flux function. The effective subgrid-scale model can be determined by a modified-differential equation analysis. Discretization parameters which determine the behavior of the implicit model in regions of developed turbulence can be adjusted so that a given explicit subgrid-scale model is recovered to leading order in filter width. Alternatively, improved discretization parameters can be found directly by evolutionary optimization. Computational results for stochastically forced and decaying Burgers turbulence are provided. An assessment of the computational experiments shows that results for a given explicit subgrid-scale model can be matched by computations with an implicit representation. A considerable improvement can be achieved if instead of the parameters matching an explicit model discretization parameters determined by evolutionary optimization are used.

Implicit Turbulence Modeling for High Reynolds Number Flows

Implicit turbulence modeling is the numerical simulation of high Reynolds fluid flow using nonoscillatory finite volume (NFV) schemes without any explicit subgrid scale model. Here we investigate the ability of a particular NFV scheme, MPDATA, to simulate decaying turbulence in a triply periodic cube for a variety of viscosities, comparing our results to analogous pseudo-spectral studies. In the regime of direct numerical simulation, MPDATA is shown to agree closely with the pseudo-spectral results. As viscosity is reduced, the two model results diverge. We study the MPDATA results in the inviscid limit, using a combination of mathematical analysis and computational experiment. We validate these results as representing the turbulent flow in the limit of very high Reynolds number.