Overview of the Lattice Boltzmann Method
The Transitional Flow Interface uses the lattice Boltzmann method to solve the Boltzmann BGK equation, which is a simplified form of the more general Boltzmann equation. The BGK equation (in the absence of volume forces) is given below:
where ξ is the particle velocity, x is the position, t is the time, f(ξ ,x ,t) is the distribution function (which represents the total number of particles in the phase space dξdx), feq is the local equilibrium distribution, n is the number density, u is the bulk velocity, and τ is the relaxation time. This equation is similar to the Boltzmann equation, except the complex collision term has been replaced by a much simpler term that implies a constant relaxation time for all velocities to return to equilibrium. The equilibrium function in N dimensions is given by
(3-1)
The equation set is still nonlinear as feq(ξ ,u ,ρ) is a nonlinear function of f(ξ ,x ,t) (see definitions of n and u). As in the Boltzmann equation, the macroscopic thermodynamic variables are defined as moment integrals of the distribution function. For example, the number density and fluid velocity are given by
where m is the molecular mass.
In the lattice Boltzmann approach, the BGK equation is projected onto a finite velocity quadrature. In this case each velocity direction in the lattice has an associated distribution function, which can be interpreted as the local number density of the gas moving with the velocity specified. Weights associated with each of the velocities are used when calculating the moments of the distribution functions, such as the macroscopic density and velocity. When the lattice used is larger than that required to solve the Navier–Stokes equations, the lattice Boltzmann method is effectively an optimized discrete velocity method for solving the BGK equation
The Boltzmann Equations become
(3-2)
where there are now i distribution functions, fi, associated with each of the discrete velocity directions, ξi, and each having an associated equilibrium function, . The number density and velocity become:
The velocity lattice and equilibrium functions used are critical in determining the accuracy of the final solution. The approach used to generate the equilibrium functions and velocity lattice used by COMSOL Multiphysics is described in detail in Ref. 1. The distribution function f(ξ ,x ,t) is expanded in the Hermite polynomials. The velocity space is approximated by a Gauss–Hermite quadrature. This approach is closely related to Grad’s moment scheme for solving the Boltzmann equation (Ref. 2). The Hermite polynomials are chosen because the lower-order velocity moments of the distribution functions depend only on the lower-order coefficients of the Hermite polynomials, so that truncating the expansion has a minimal effect on the moments themselves.
The functions are derived by expanding the drifting Maxwellian distribution in the Hermite polynomials to a given order. Using Equation 3-1 and the orthogonality and completeness of the Hermite basis this equation results:
where neq is the equilibrium number density (usually the local number density), ueq is the equilibrium velocity (usually the local velocity), and H(n)(ξ) is the nth N-dimensional Hermite polynomial, given by
with
The expansion for the isothermal case, evaluated in the Gauss–Hermite quadrature, is given below, with terms according to progressively higher orders of approximation indicated (Ref. 1):
(3-3)
here wi is the weight associated with the velocity quadrature and cs is the characteristic speed, which in the BGK model is given by
The higher-order terms are typically significant only at higher Mach numbers. While rarefied flows can be simulated with second-order or even first-order equilibrium functions, a set of distribution functions up to third order are provided for completeness.
It is important to realize that highly accurate solutions of the Boltzmann equation are difficult to obtain in the transitional region. The accuracy of the Transitional Flow interface is strongly dependent on the number of lattice directions in the quadrature, and in general it is best to use the largest number possible within hardware and time constraints. You can assess the level of accuracy of the simulation by comparing the results obtained with solutions produced by the Free Molecular Flow interface in the molecular flow limit. The Transitional Flow interface also solves flows in the slip flow and molecular flow limits, which can be used for benchmarking.