Wall-resolved wavelet-based adaptive large-eddy simulation of bluff-body flows with variable thresholding

Abstract

The wavelet-based eddy-capturing approach with variable thresholding is extended to bluff-body flows, where the obstacle geometry is enforced through Brinkman volume penalization. The use of a spatio-temporally varying threshold allows one to perform adaptive large-eddy simulations with the prescribed fidelity on a near optimal computational mesh. The space-time evolution of the threshold variable is achieved by solving a transport equation based on the Lagrangian path-line diffusive averaging methodology. The coupled wavelet-collocation/volume-penalization approach with variable thresholding is illustrated for a turbulent incompressible flow around an isolated stationary prism with square cross-section. Wavelet-based adaptive large-eddy simulations supplied with the one-equation localized dynamic kinetic energy-based model are successfully performed at moderately high Reynolds number. The present study demonstrates that the proposed variable thresholding methodology for wavelet-based modelling of turbulent flows around solid obstacles is feasible, accurate and efficient.

Wavelet-based adaptive large-eddy simulation of supersonic channel flow

“…By employing models that automatically switch off in well-resolved flow regions, the control of the overall physical fidelity can be achieved by means of the adaptive wavelet-based filtering procedure (De Stefano & Vasilyev 2014), thereby forming a completely unified eddy-resolving modelling framework, capable of continuously changing between WA-LES, CVS and wavelet-based adaptive direct numerical simulation (WA-DNS) regimes, within a single simulation. The filtering parameters can be automatically adjusted, both spatially and temporally, based on objective physically based criteria throughout the course of the simulation, while targeting specific flow phenomena, which leads to the intelligent simulation of turbulent flows (Nejadmalayeri et al 2014; De Stefano, Nejadmalayeri & Vasilyev 2016). As the filtering parameters are tightened, a greater portion of the turbulent fields is retained and resolved, while lessening the effect of the SGS model, which eventually becomes negligible.…”

“…A few authors have considered the low-Mach-number regime of compressible transport equations, for instance, investigating CVS of mixing layers (Roussel & Schneider 2010). Furthermore, research has been limited to a relatively narrow set of configurations, including homogeneous isotropic turbulence (Goldstein et al 2005; De Stefano & Vasilyev 2010), as well as turbulent wake flows behind bluff bodies (De Stefano & Vasilyev 2014; De Stefano et al 2016). Though the latter feature bounded flows, the Reynolds number was in the transitional regime and the boundary layer remained laminar.…”

Hierarchical Adaptive Eddy-Capturing Approach for Modeling and Simulation of Turbulent Flows

“…By applying the combined approach, the simulation of the turbulent flow past a solid obstacle was considered in [36,37]. The application of the WTF operator (2) to the penalized momentum equations results in the following penalized equation for the wavelet-filtered perturbation velocity:…”

A diffuse domain method for two-phase flows with large density ratio in complex geometries

“…2018), extended finite element methods (Fries & Belytschko 2010), immersed boundary methods (Schneider 2015; Stein, Guy & Thomases 2017), immersed interface methods (Li 2003; Chen, Li & Lin 2007; Gong et al. 2018; O'Brien & Bussmann 2018) and the volume penalty method (Shirokoff & Nave 2014; De Stefano, Nejadmalayeri & Vasilyev 2016), where the complex geometry is embedded in a larger, regular domain with a test function being used to enforce the boundary conditions at solid–fluid interfaces. Other methods include boundary integral methods (Biros, Ying & Zorin 2004; Mittal et al.…”