Towards systematic grid selection in LES: iterative identification of the coarse-graining length scale by minimizing the solution sensitivity
Siavash Toosi, Johan Larsson

TL;DR
This paper introduces a systematic method to identify the optimal spatial distribution of the coarse-graining length scale in LES by minimizing solution sensitivity, improving the accuracy and robustness of turbulence simulations.
Contribution
It proposes an iterative algorithm for selecting the optimal filter-width distribution in LES based on solution sensitivity minimization, a novel approach in turbulence modeling.
Findings
The optimal coarse-graining length scale is the largest scale with minimal solution sensitivity.
The method produces length scale fields similar to established best practices in LES.
An alternative explanation for the success of the dynamic procedure is derived.
Abstract
The accuracy of a large eddy simulation (LES) is determined by the accuracy of the model used to describe the effect of unresolved scales, the numerical errors of the resolved scales, and the optimality of the length scale that separates resolved from unresolved scales (the filter-width, or the coarse-graining length scale). This paper is focused entirely on the last of these, proposing a systematic algorithm for identifying the "optimal" spatial distribution of the coarse-graining length scale and its aspect ratio. The core idea is that the "optimal" coarse-graining length scale for LES is the largest length scale for which the LES solution is minimally sensitive to it. This idea is formulated based on an error indicator that measures the sensitivity of the solution and a criterion that determines how that error indicator should vary in space and direction to minimize the overall…
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Taxonomy
TopicsPhase Equilibria and Thermodynamics · Surfactants and Colloidal Systems · Theoretical and Computational Physics
