Scale-adaptive turbulence modeling for LES over complex terrain

Statistical Analysis of Dynamic Subgrid Modeling Approaches in Large Eddy Simulation

“…In this regard, the transport of five invariants of the velocity gradient tensor through the "restricted Euler equations" is important for understanding the transport of energy flux in turbulent flows [2,15,16]. In previous studies [17][18][19], we demonstrate that these invariants play an essential role in modeling wall-layers in LES of atmospheric turbulence in wind farms, forests, and around mountains.…”

“…One of which (hereinafter SGS-B) employs the Germano identity in order to dynamically estimate both C k and C (e.g. see [17,40] for details). The accuracy of three dynamic subgrid models discussed above was thoroughly scrutinized in the literature, particularly in the context of wall-modeled LES e.g.…”

“…Our study here is one way to confirm a causal connection between vortex stretching and energy cascade. Another reason of considering vortex stretching to represent subgrid dissipation is that the vorticity field is more intermittent than the strain field [14][15][16][17]. The intermittency of turbulence is a result from the subtle balance between convective transport and diffusive dissipation.…”

“…Such negative local energy flux is equivalent to representing the effects of energy 'backscatter'. In previous work, we considered similar idea of representing energy flux in LES of atmospheric boundary layer flows over arrays of buildings [18], mountains [17], and wind turbines [19].…”

“…To account for the effect of vortex-stretching in the subgrid model, Nicoud and Ducros [31] considered the rotation tensor along with the strain tensor in the wall-adapting local eddy viscosity (WALE) model for wall-bounded turbulence. Similarly, Refs [17,18] considered the second invariant of the square of the velocity gradient tensor in the subgrid models for LES of atmospheric boundary layer flow over complex terrain [8]. In other words, the invariants of the velocity gradient tensor are very important particularly in turbulent flows, which help to understand necessary small scale information in closing the filtered Navier-Stokes system [2,[31][32][33][34].…”