
The applicability of Navier–Stokes equations is limited to near-equilibrium flows in which the gradients of density, velocity and energy are small. Here I propose an extension of the Chapman–Enskog approximation in which the velocity probability distribution function (PDF) is averaged in the coordinate phase space as well as the velocity phase space. I derive a PDF that depends on the gradients and represents a first-order generalization of local thermodynamic equilibrium. I then integrate this PDF to derive a hydrodynamic model. I discuss the properties of that model and its relation to the discrete equations of computational fluid dynamics. This article is part of the theme issue ‘Hilbert’s sixth problem’.
high Reynolds number, finite scale, Statistical mechanics of liquids, Foundations of fluid mechanics, coarse-graining, statistical physics
high Reynolds number, finite scale, Statistical mechanics of liquids, Foundations of fluid mechanics, coarse-graining, statistical physics
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