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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

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Published on: December 4, 2017

Stochastic subgrid-scale modelling for non-equilibrium geophysical flows.

Meelis J Zidikheri¹, Jorgen S Frederiksen

¹Centre for Australian Weather and Climate Research, Bureau of Meteorology, Melbourne, Australia. m.zidikheri@bom.gov.au

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|December 2, 2009

Summary

This study applies non-equilibrium statistical mechanics to turbulence for parameterizing subgrid-scale eddies in large-eddy simulations (LESs). The new method accurately models ocean currents, improving geophysical fluid dynamics simulations.

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Published on: February 22, 2018

Area of Science:

Geophysical Fluid Dynamics
Turbulence Theory
Statistical Mechanics

Background:

Parameterizing subgrid-scale eddies is crucial for large-eddy simulations (LESs) in geophysical fluid dynamics.
Turbulence in geophysical flows, like the Antarctic Circumpolar Current, presents complex challenges for accurate modeling.

Purpose of the Study:

To develop and apply a direct stochastic modeling scheme for parameterizing subgrid-scale eddies.
To improve the accuracy of large-eddy simulations (LESs) in geophysical fluid dynamics.

Main Methods:

Utilized methods from non-equilibrium statistical mechanics of turbulence.
Employed a direct stochastic modeling scheme based on statistical closure theories.
Developed a generalized Langevin equation to represent subgrid-scale eddy effects.

Main Results:

Subgrid dissipation, stochastic forcing, and mean subgrid forcing were derived from high-resolution direct numerical simulations (DNS).
The developed parametrization scheme significantly improved the agreement between LES and DNS results.
Accurate modeling of baroclinically unstable subgrid-scale eddies was achieved.

Conclusions:

The direct stochastic modeling approach provides a robust method for parameterizing subgrid-scale eddies in LESs.
This technique enhances the fidelity of geophysical fluid dynamics simulations, particularly for flows like the Antarctic Circumpolar Current.
The study demonstrates the successful application of advanced statistical mechanics to practical problems in computational fluid dynamics.