# An Overview of Hybrid RANS-LES Models Developed for Industrial CFD
## 5 Summary and Outlook  
Substantial progress has been made in the last two decades in the development of reliable hybrid RANS-LES methods. For the current group, the SBES model offers an optimal platform for the different application scenarios for such approaches, as SBES can be run in classical DES-like mode, whereby the boundary layers are covered by RANS and free shear flows are covered by LES methods. In addition, SBES can operate in WMLES mode inside boundary layers when triggered by either synthetic turbulence or upstream obstacles, such as a backward-facing step. SBES is also computationally efficient, as it allows a delayed update of the two-equation RANS model portion, resulting in costs per  
Figure 16: (**a**) Grid used for the NASA hump simulation. (**b**) Turbulent structures in the LES domain (Q-criterion colored in line with spanwise velocity component). Figure 17: (**a**) Skin friction (cf) and (**b**) wall pressure coefficients (cp) from NASA hump flow simulations. Comparison of WMLES and WALE methods in the LES domain. iteration close to those of a pure LES model. Last but not least, the approach is generic and allows the combination of existing RANS and LES models, which is especially attractive for industrial codes with many models, both on the RANS and the LES sides. The question remains of what the will future bring. Clearly, with the combination of exiting RANS and LES methods in the generic SBES formulation, improvements for both RANS and LES methods can be directly integrated into the hybrid model. In other words, any improvement on either modeling side will automatically lead to improvements in the hybrid RANS-LES formulation. Both RANS and LES formulations will benefit from Machine Learning (ML), as can be anticipated from RANS studies (e.g., [PERSON] et al. [46]) and LES studies (e.g., [PERSON] et al. [47]). The potential might be higher on the LES side, as the RANS part mainly influences the boundary layer and can be already controlled quite flexibly by the free parameters of the GEKO model. ML for LES could potentially lead to large reductions in computation effort in the LES zone, thereby significantly reducing the turn-around time. Considering that most ML techniques for LES are carried out on Cartesian meshes, hybrid RANS-LES methods might be well-positioned to benefit from ML, as the LES part away from walls can often be covered by Cartesian-dominated grids (octree). The application of WFLES and WMLES inside boundary layers is a much more difficult problem. The resolution requirements are still too high for realistic Reynolds numbers, and flexible methods will be required that allow the upstream thin boundary layers to be handled in RANS mode (including the laminar-turbulent transition) and to automatically trigger the simulation into LES mode once the mesh is fine enough to resolve the boundary layer turbulence. F.M. : Main text and R&D direction. A.H.: Simulations Ahmed car on Octree grids, A.M. and D.K. : Remaining CFD simulations. All authors have read and agreed to the published version of the manuscript. This work was funded by ANSYS Inc. and by the Ministry of Science and Higher Education of the Russian Federation as part of World-class Research Center program: Advanced Digital Technologies (contract No. 075-15-2020-934 of 17.11.2020). Not applicable. Not new data were created or analyzed in this study. Data sharing is not applicable to this article. The material in this report was prepared with the help of colleagues at ANSYS, namely [PERSON], [PERSON], and [PERSON], as well as with the help of colleagues at NTS in St. Petersburg, namely [PERSON] and [PERSON]. Special thanks to [PERSON] for his support of the work exposed herein. Some of the test cases were run in the framework of the EU projects DESIDER and ATAAC.