# An Overview of Hybrid RANS-LES Models Developed for Industrial CFD
## 1 Introduction  
Historically, industrial Computational Fluid Dynamics (CFD) simulations have been based on Reynolds-averaged Navier-Stokes (RANS) turbulence modeling concepts. While computationally efficient, RANS models cannot always provide the degree of accuracy or the level of (unsteady) information required during the design process. Since the resolution of the entire turbulent spectrum in the entire flow domain using direct numerical simulations (DNS) techniques is insufficient, divide-and-conquer strategies are employed. This means that only parts of the turbulent spectrum are resolved, or the turbulence is only resolved in a part of the computational domain. Such methods are termed scale-resolving simulation (SRS) methods in this article. Classical examples in which RANS cannot provide all of the necessary information are aero-acoustics simulations, whereby the turbulence generates noise sources that cannot be extracted accurately from RANS simulations. Other examples are flows with unsteady heat-loading due to flow streams of different temperatures, which can lead to material failure, or multi-physics effects such as vortex cavitation, in which the unsteady turbulence pressure field is the cause of cavitation. In such situations, the need for SRS can exist, even when a RANS model would in principle be capable of computing the correct time-averaged flow field. The second reason for using SRS models is accuracy. RANS models have shown their strength for wall-bound flows, whereby 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 swirls, 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 advancedReynolds stress models (RSM) will eventually be able to provide a reliable foundation for all such flows. For an overview of RANS modeling and its limitations, see [PERSON] et al. [1], [PERSON] [2], [PERSON] and [PERSON] [3], and [PERSON] et al. [4]. For free shear flows, it is often feasible to resolve the largest turbulence scales, as they are of the order of the shear layer thickness. In contrast, in wall boundary layers, the turbulent 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 simulations (LES), as the computational effort required is still far from the computing power available to the industry (e.g., [PERSON] [5]). For an overview of LES modeling and its resource requirements, see [PERSON] [6] and [PERSON] [7]. For this reason, hybrid models are increasingly applied, whereby large eddies are resolved 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) ([PERSON], [8], [PERSON] [9], [PERSON] et al. [10]), scale-adaptive simulation (SAS) ([PERSON] and [PERSON] [11] and [PERSON] et al. [12]), and Partially Averaged Navier-Stokes (PANS) models ([PERSON] et al. [13; 14]). More advanced versions of DES include delayed DES (DDES), shear-layer-adapted (SLA) DDES (DDES-SLA), and improved DDES (IDDES) ([PERSON] et al. [15], [PERSON] et al. [16], [PERSON] et al. [17], [PERSON] [18]). More recent developments are the shielded detached eddy simulation (SDES) and the stress-blended eddy simulation (SBES) models ([PERSON] [19]). 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) models (e.g., [PERSON] et al. [15]).