Coarse-grained transport of a turbulent flow via moments of the Reynolds-averaged Boltzmann equation

TL;DR

This paper introduces new coarse-grained variables based on moments of the Reynolds-averaged Boltzmann equation for turbulent flows, enabling the application of existing closure methods and connecting to classical fluid dynamics models.

Contribution

It develops a novel framework for turbulence modeling using moments of the Reynolds-averaged Boltzmann equation, linking kinetic theory with turbulence closure techniques.

Findings

Bound on the global relative entropy of the coarse-grained state.

Grad moment closure is suitable for truncating the hierarchy.

Derivation of Navier-Stokes and higher-order closures from the coarse-grained equations.

Abstract

Here we introduce new coarse-grained variables for a turbulent flow in the form of moments of its Reynolds-averaged Boltzmann equation. With the exception of the collision moments, the transport equations for the new variables are identical to the usual moment equations, and thus naturally lend themselves to the variety of already existing closure methods. Under the anelastic turbulence approximation, we derive equations for the Reynolds-averaged turbulent fluctuations around the coarse-grained state. We show that the global relative entropy of the coarse-grained state is bounded from above by the Reynolds average of the fine-grained global relative entropy, and thus obeys the time decay bound of Desvillettes and Villani. This is similar to what is observed in the rarefied gas dynamics, which makes the Grad moment closure a good candidate for truncating the hierarchy of the coarse-grained moment equations. We also show that, under additional assumptions on the form of the coarse-grained collision terms, one arrives at the Navier-Stokes closure, which can be naturally extended to the Burnett and super-Burnett orders. Finally, we suggest crude parameterizations of the coarse-grained collision terms for use as starting points in numerical simulation and modeling.