2017
DOI: 10.1103/physreve.96.023309
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Comparative study of the discrete velocity and lattice Boltzmann methods for rarefied gas flows through irregular channels

Abstract: Rooted from the gas kinetics, the lattice Boltzmann method is a powerful tool in modeling hydrodynamics. In the past decade, it has been extended to simulate the rarefied gas flow beyond the Navier-Stokes level, either by using the high-order Gauss-Hermite quadrature, or by introducing the relaxation time that is a function of the gas-wall distance. While the former method, with a limited number of discrete velocities (i.e. D2Q36), is accurate up to the early transition flow regime, the latter method, with the… Show more

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Cited by 45 publications
(40 citation statements)
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“…Thus, the spectral Galerkin method becomes inefficient. A similar observation is also presented in [28].…”
Section: One-dimensional Numerical Experimentssupporting
confidence: 87%
“…Thus, the spectral Galerkin method becomes inefficient. A similar observation is also presented in [28].…”
Section: One-dimensional Numerical Experimentssupporting
confidence: 87%
“…ρ = M j =1 f x, v j w j with w j being the quadrature weight for the corresponding discretized velocity points v j . The discrete velocities are not necessarily equidistant, especially for low-speed microflows with large Knudsen numbers, where the distribution function varies rapidly around v = 0 due to gas-wall interaction and nonuniform velocity points with refinement in this area is more efficient to capture the variation of f [58]. However, it should be emphasized that the FFT-based convolution could be efficiently employed only when the frequency space is uniformly discretized, though the number of frequency components can be smaller than that of velocity grid points due to the spectral accuracy of the FSM [44].…”
Section: Discretization In the Molecular Velocity Spacementioning
confidence: 99%
“…This is further confirmed in Table 1, where the relative L 2 error of MFRs (calculated based on the DUGKS results), the number of iteration steps, and the total CPU time are listed for various rarefaction parameters δ and degrees of approximation polynomials in the HDG method. For each case at δ = 88.62, 20 uniform points were used to discretize the velocity space truncated in the range of [−4, 4] in each direction, while 24 non-uniform points [9] were employed for other cases. It is interesting to note that with the same number of triangles, the number of iterative steps of the CIS reaches a constant value as the degree of polynomials in the HDG discretization increases.…”
Section: Fast Convergence Of the Sis: Poiseuille Flow Between Two Parmentioning
confidence: 99%