While today’s CFD simulations are mainly based on Reynolds-Averaged Navier-Stokes (RANS) turbulence models, it is becoming increasingly clear that certain classes of flows are better covered by models in which all or a part of the turbulence spectrum is resolved in at least a portion of the numerical domain. Such methods are termed Scale-Resolving Simulation (SRS) models in this document.

There are two main motivations for using SRS models in favor of RANS formulations. The first reason for using SRS models is the need for additional information that cannot be obtained from the RANS simulation. Examples are acoustics simulations where the turbulence generates noise sources, which cannot be extracted with accuracy from RANS simulations. Other examples are unsteady heat loading in unsteady mixing zones of flow streams at different temperatures, which can lead to material failure, or multi-physics effects like vortex cavitation, where the unsteady turbulence pressure field is the cause of cavitation. In such situations, the need for SRS can exist even in cases where the RANS model would in principle be capable of computing the correct time-averaged flow field.

The second reason for using SRS models is related to accuracy. It is known that RANS models have their limitations in accuracy in certain flow situations. RANS models have shown their strength essentially for wall-bounded flows, where the calibration according to the law-of-the-wall provides a sound foundation for further refinement. For free shear flows, the performance of RANS models is much less uniform. There is a wide variety of such flows, ranging from simple self-similar flows such as jets, mixing layers, and wakes to impinging flows, flows with strong swirl, massively separated flows, and many more. Considering that RANS models typically already have limitations covering the most basic self-similar free shear flows with one set of constants, there is little hope that even the most advanced Reynolds Stress Models (RSM) will eventually be able to provide a reliable foundation for all such flows. (For an overview of RANS modeling, see Durbin, Pettersson and Reif, 2003 5; Wilcox, 2006 39; or Hanjalic and Launder, 2011 13.)

For free shear flows, it is typically much easier to resolve the largest turbulence scales, as they are of the order of the shear layer thickness. In contrast, in wall boundary layers the turbulence length scale near the wall becomes very small relative to the boundary layer thickness (increasingly so at higher Re numbers). This poses severe limitations for Large Eddy Simulation (LES) as the computational effort required is still far from the computing power available to industry (Spalart, 1997 30). (For an overview of LES modeling, see Geurts, 2004 12, and Wagner et al., 2007 36.) For this reason, hybrid models are under development where large eddies are resolved only away from walls and the wall boundary layers are covered by a RANS model. Examples of such global hybrid models are Detached Eddy Simulation (DES, see Spalart, 2000 31) or Scale-Adaptive Simulation (SAS, see Menter and Egorov, 2010 18). More recent developments include the Shielded Detached Eddy Simulation (SDES) and the Stress-Blended Eddy Simulation (SBES).

A further step is to apply a RANS model only in the innermost part of the wall boundary layer and then to switch to a LES model for the main part of the boundary layer. Such models are termed Wall-Modeled LES (WMLES) (for example, Shur et al., 2008 27). Finally, for large domains, it is frequently necessary to cover only a small portion with SRS models, while the majority of the flow can be computed in RANS mode. In such situations, zonal or embedded LES methods are attractive because they enable you to specify ahead of time the region where LES is required. Such methods are typically not new models in the strict sense, but enable the combination of existing models/technologies in a flexible way in different portions of the flowfield. Important elements of zonal models are interface conditions, which convert turbulence from RANS mode to resolved mode at pre-defined locations. In most cases, this is achieved by introducing synthetic turbulence based on the length and time scales from the RANS model.

There are many hybrid RANS-LES models, often with somewhat confusing naming conventions, that vary in the range of turbulence eddies they can resolve. For a general overview of SRS modeling concepts, see Fröhlich and von Terzi, 2008 8, Sagaut et al, 2006 25.

SRS models are very challenging in their proper application to industrial flows. The models typically require special attention to various details such as:

Unfortunately, there is no unique model covering all industrial flows, and each individual model poses its own set of challenges. In general, when using a CFD code, you must understand the intricacies of the SRS model formulation in order to be able to select the optimal model and to use it efficiently. This document is intended to support you in the basic understanding of such models and to provide best practice guidelines for their usage. The discussion is focused on the models available in the Ansys CFD software.

This document is intended as an addition to the code-specific Theory and User Documentation available for both Ansys Fluent™ and Ansys CFX™. The Theory and User Documentation describes in detail how to select and activate these models, so that information is not repeated here. This document is intended to provide a general understanding of the underlying principles and the associated limitations of each of the described modeling concepts. It also covers the types of flows for which the models are suitable as well as flows where they will likely not work well. Finally, the impact of numerical settings on model performance is discussed.

In accordance with the intention of providing recommendations for day-to-day work, several appendices can be found at the end of this document for quick reference of the most important points.