Can Explicit Subgrid Models Enhance Implicit LES Simulations? A GPU-Oriented High-Order-Solver Perspective
Gonzalo Rubio, Gerasimos Ntoukas, Miguel Ch\'avez-M\'odena, Oscar Mari\~no, Bernat Font, Oriol Lehmkuhl, Eusebio Valero, Esteban Ferrer

TL;DR
This paper investigates how explicit subgrid models interact with implicit dissipation in high-order DG methods on GPUs, revealing conditions where SGS models are beneficial or redundant in turbulence simulations.
Contribution
It provides a comprehensive analysis of the interplay between implicit DG dissipation and explicit SGS models, offering practical guidance for high-order turbulence simulations on GPU architectures.
Findings
SGS models are unnecessary when split-form DG schemes ensure stability.
Adding SGS models does not improve accuracy in well-resolved LES.
Explicit SGS models help at high Reynolds numbers with insufficient resolution.
Abstract
High-order Discontinuous Galerkin (DG) methods offer excellent accuracy for turbulent flow simulations, especially when implemented on GPU-oriented architectures that favor very high polynomial orders. On modern GPUs, high-order polynomial evaluations cost roughly the same as low-order ones, provided the DG degrees of freedom fit within device memory. However, even with high-order discretizations, simulations at high Reynolds numbers still require some level of under-resolution, leaving them sensitive to numerical dissipation and aliasing effects. Here, we investigate the interplay between intrinsic DG dissipation mechanisms (implicit dissipation) -- in particular split forms and Riemann solvers -- and explicit subgrid-scale models in Large Eddy Simulations (LES). Using the three-dimensional Taylor--Green vortex at and an inviscid case (), we evaluate kinetic…
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Taxonomy
TopicsModel Reduction and Neural Networks · Fluid Dynamics and Turbulent Flows · Advanced Numerical Methods in Computational Mathematics
