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On the Accuracy of Finite-Volume Schemes for Fluctuating Hydrodynamics

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arxiv 0906.2425 v2 pith:TGC3IHUA submitted 2009-06-12 physics.flu-dyn cond-mat.softcond-mat.stat-mech

classification physics.flu-dyncond-mat.softcond-mat.stat-mech
keywords equationsllnsaccuracydiscreteequilibriumfinite-volumewavelengthsaccurate
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This paper describes the development and analysis of finite-volume methods for the Landau-Lifshitz Navier-Stokes (LLNS) equations and related stochastic partial differential equations in fluid dynamics. The LLNS equations incorporate thermal fluctuations into macroscopic hydrodynamics by the addition of white-noise fluxes whose magnitudes are set by a fluctuation-dissipation relation. Originally derived for equilibrium fluctuations, the LLNS equations have also been shown to be accurate for non-equilibrium systems. Previous studies of numerical methods for the LLNS equations focused primarily on measuring variances and correlations computed at equilibrium and for selected non-equilibrium flows. In this paper, we introduce a more systematic approach based on studying discrete equilibrium structure factors for a broad class of explicit linear finite-volume schemes. This new approach provides a better characterization of the accuracy of a spatio-temporal discretization as a function of wavenumber and frequency, allowing us to distinguish between behavior at long wavelengths, where accuracy is a prime concern, and short wavelengths, where stability concerns are of greater importance. We use this analysis to develop a specialized third-order Runge Kutta scheme that minimizes the temporal integration error in the discrete structure factor at long wavelengths for the one-dimensional linearized LLNS equations. Together with a novel method for discretizing the stochastic stress tensor in dimension larger than one, our improved temporal integrator yields a scheme for the three-dimensional equations that satisfies a discrete fluctuation-dissipation balance for small time steps and is also sufficiently accurate even for time steps close to the stability limit.

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  1. Critical fluid dynamics in two and three dimensions

    nucl-th 2024-11 conditional novelty 6.0 of 10

    Direct numerical simulations of stochastic model H give a dynamic critical exponent z ≈ 3 in 3D and z ≈ 2 in 2D, with a crossover from mean-field z = 4 controlled by the renormalized shear viscosity.

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