New SGS model for turbulence uses mutual information maximization tied to inter-scale equilibrium to estimate parameters without empirical prescription, matching prior values and performing comparably in box and channel flow tests.
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physics.flu-dyn 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Sparse regression yields explicit invariant polynomial SGS closures for LES on anisotropic grids that achieve neural-network accuracy with simpler forms and lower computational cost.
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Information-Preserving SGS model based on the local inter-scale equilibrium hypothesis
New SGS model for turbulence uses mutual information maximization tied to inter-scale equilibrium to estimate parameters without empirical prescription, matching prior values and performing comparably in box and channel flow tests.
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Discovery of Sparse Invariant Subgrid-Scale Closures via Dissipation-Controlled Training for Large Eddy Simulation on Anisotropic Grids
Sparse regression yields explicit invariant polynomial SGS closures for LES on anisotropic grids that achieve neural-network accuracy with simpler forms and lower computational cost.