Development and Validation of a New Formulation of Hybrid Temporal Large Eddy Simulation

Abstract

Hybrid RANS-LES approaches have aroused interest for years since they provide unsteady information at a reduced numerical cost compared to LES. In the hybrid context, the use of temporal filtering, to control the energy partition between resolved and modeled scales, ensures a consistent bridging between RANS and LES models. In this regard, a new formulation of Hybrid Temporal Large Eddy Simulation (HTLES) is developed, aiming at improving the theoretical foundation of the model associated with an eddy-viscosity closure. The analytical development is performed, applying the Hybrid-Equivalence criterion, and the model is calibrated in decaying isotropic turbulence. In addition, an upgraded version of the approach is proposed to improve the behavior of the model in near-wall regions, introducing a two-fold shielding function and an internal consistency constraint to provide a suitable control of the RANS-to-LES transition. Applying HTLES to the k-ω SST model, the validation process is carried out on channel and periodic-hill flows, over a range of grids and Reynolds numbers. The predictive accuracy and the robustness to grid coarsening are assessed in these cases, ensuring that HTLES offers a cost-saving alternative to LES.

An application of the scale-adapted simulation to the unsteady flow across a tube bundle

“…There exists quite a rich variety of hybrid RANS/LES methodologies classified as zonal methods for which the zones targeted by either the RANS or the LES treatment are defined prior to the simulation and non-zonal methods where it is the model itself which is able to switch smoothly between the two modes according to some given criteria. The interested reader is referred to Chaouat (2017) for quite an exhaustive review of hybrid RANS/LES methods and to Duffal et al (2021) as an example of recent advances in the development of a seemless hybrid temporal filtered LES. The second alternative to elaborate a hybrid method is to retain the RANS framework but to revisit the derivation of its governing equations in a way that permits the derivation of a sound unsteady RANS (URANS) model.…”