Comparison of Sub-Grid Scale Models for Large-Eddy Simulation using a High-Order Spectral Element Approximation of the Compressible Navier-Stokes Equations at Low Mach Number

This study investigates the properties and performance of different sub-grid scale (SGS) models for the large eddy simulation (LES) of low Mach compressible flows using high-order spectral elements. We compare the classical Smagorinsky-Lilly and Vreman models against two dynamic SGS (DSGS) variants: a time-dependent residual-based model (R-DSGS) and a time-independent version (T-DSGS). These models are evaluated based on numerical stability, extrema minimization, discontinuity preservation, and energy transfer across scales. Benchmarks include passively advected tracers, nonlinear systems with discontinuities, gravity-driven stratified flows, and homogenous isotropic turbulence. All models effectively preserve sharp discontinuities, though Vreman and both DSGS variants more significantly reduce oscillations in advection problems. For high-order spectral element stability, R-DSGS and T-DSGS prove more robust than Smagorinsky or Vreman. While Smagorinsky and Vreman better resolve fine-scale structures in shear flows, the nodal R-DSGS implementation exhibits superior energy conservation. Overall, the nodal R-DSGS model outperforms the other candidates across most metrics—particularly compared to its element-based counterpart and remains on par regarding the others. This suggests R-DSGS is a highly effective model for stabilizing transport-dominated problems in high-order spectral element frameworks.

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Publication Details

Journal
Communications in Computational Physics
Published
2026-05-31
DOI
https://doi.org/10.4208/cicp.oa-2025-0351
Citations
2
Primary Topic
Computational Fluid Dynamics and Aerodynamics
Type
preprint
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preprint

Comparison of Sub-Grid Scale Models for Large-Eddy Simulation using a High-Order Spectral Element Approximation of the Compressible Navier-Stokes Equations at Low Mach Number

Yassine Tissaoui, Sohail R. Reddy, Francis X. Giraldo, Felipe A. V. de Braganca Alves et al.
2 citations
Communications in Computational Physics
Computational Fluid Dynamics and Aerodynamics
preprint

Comparison of Sub-Grid Scale Models for Large-Eddy Simulation using a High-Order Spectral Element Approximation of the Compressible Navier-Stokes Equations at Low Mach Number

Yassine Tissaoui, Sohail R. Reddy, Francis X. Giraldo, Felipe A. V. de Braganca Alves, Simone Marras
preprint en
2 citations

Abstract

This study investigates the properties and performance of different sub-grid scale (SGS) models for the large eddy simulation (LES) of low Mach compressible flows using high-order spectral elements. We compare the classical Smagorinsky-Lilly and Vreman models against two dynamic SGS (DSGS) variants: a time-dependent residual-based model (R-DSGS) and a time-independent version (T-DSGS). These models are evaluated based on numerical stability, extrema minimization, discontinuity preservation, and energy transfer across scales. Benchmarks include passively advected tracers, nonlinear systems with discontinuities, gravity-driven stratified flows, and homogenous isotropic turbulence. All models effectively preserve sharp discontinuities, though Vreman and both DSGS variants more significantly reduce oscillations in advection problems. For high-order spectral element stability, R-DSGS and T-DSGS prove more robust than Smagorinsky or Vreman. While Smagorinsky and Vreman better resolve fine-scale structures in shear flows, the nodal R-DSGS implementation exhibits superior energy conservation. Overall, the nodal R-DSGS model outperforms the other candidates across most metrics—particularly compared to its element-based counterpart and remains on par regarding the others. This suggests R-DSGS is a highly effective model for stabilizing transport-dominated problems in high-order spectral element frameworks.

Communications in Computational PhysicsVol. 40(3)
New Jersey Institute of Technology (US), University of Wisconsin–Madison (US), Naval Postgraduate School (US)
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Computational Fluid Dynamics and Aerodynamics
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