Efficient algorithm for simulating homogeneous turbulent shear flow without remeshing

Brucker, Kyle A.; Isaza, Juan C.; Vaithianathan, T.; Collins, Lance R.

doi:10.1016/j.jcp.2006.10.018

Cited by 48 publications

(35 citation statements)

References 22 publications

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“…Equations (2.1) and (2.2) are solved using a pseudo-spectral algorithm with de-aliasing based on a combination of truncation and phase-shift (Patterson & Orszag 1971;Johnson 1998;Brucker et al 2007) on a flow domain comprised of a cube with each side of length 2π (in arbitrary units). We use 512 grid points in each direction and achieve a moderate Reynolds number based on the Taylor microscale (R λ = 227).…”

Section: Fluid Phasementioning

confidence: 99%

Preferential concentration and relative velocity statistics of inertial particles in Navier–Stokes turbulence with and without filtering

Ray

Collins

2011

J. Fluid Mech.

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Section: Fluid Phasementioning

confidence: 99%

Preferential concentration and relative velocity statistics of inertial particles in Navier–Stokes turbulence with and without filtering

Ray

Collins

2011

J. Fluid Mech.

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“…Schumacher & Eckhardt (2000) and Horiuchi & Ozawa (2011) introduced artificial body forces to drive a mean shear gradient between stress-free surfaces, but this creates thin layers near the surfaces, and the impermeability condition prevents large-scale motions from developing. A different strategy for avoiding discrete remeshings in fully spectral codes is that of Brucker et al (2007), who used an especially developed Fourier transform essentially equivalent to remeshing at each time step.…”

Section: Numericsmentioning

confidence: 99%

Coherent structures in statistically-stationary homogeneous shear turbulence

Dong¹

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“…Zemach 1998; Brucker et al 2007) on a standard periodic cube of length 2π (in arbitrary units). We use 128 grid points in each direction, which yields R λ ≈ 95.…”

Section: Fluid Phasementioning

confidence: 99%

Investigation of sub-Kolmogorov inertial particle pair dynamics in turbulence using novel satellite particle simulations

Ray

Collins

2013

J. Fluid Mech.

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Clustering (or preferential concentration) of weakly inertial particles suspended in a homogeneous isotropic turbulent flow is driven primarily by the smallest eddies at the so-called Kolmogorov scale. In particle-laden large-eddy simulations (LES), these small scales are not resolved by the grid and hence their effect on both the resolved flow scales and the particle motion have to be modelled. In order to predict clustering in a particle-laden LES, it is crucial that the subgrid model for the particles captures the mechanism by which the subgrid scales affect the particle motion (Ray & Collins, J. Fluid Mech., vol. 680, 2011, pp. 488-510). In this paper, we describe novel satellite particle simulations (SPS), in which we study the clustering and relative velocity statistics of inertial particles at separation distances well below the Kolmogorov length scale. SPS is designed to isolate pairwise interactions of particles, and is therefore well suited for developing two-particle models. We show that the power-law dependence of the radial distribution function (RDF), a statistical measure of clustering, is predicted by the SPS in excellent agreement with direct numerical simulations (DNS) for Stokes numbers up to 3, implying that no explicit information from the inertial range is required to accurately describe particle clustering. This result further explains our successful prediction of the RDF power using the drift-diffusion model of Chun et al. (J. Fluid Mech., vol. 536, 2005, pp. 219-251) for St 0.4. We also consider the second-order longitudinal relative velocity structure function for the particles; we show that the SPS is able to capture its power-law exponent for St 0.5 and attribute the disagreement at larger St to the effect of the larger scales of motion not captured by the SPS. Further, the SPS is able to capture the 'caustic activation' of the structure function at zero separation and predict the critical St and rate of activation in agreement with the DNS (Salazar & Collins, J. Fluid. Mech., vol. 696, 2012, pp. 45-66). We show comparisons between filtered DNS and equivalently filtered SPS, and the findings are similar to the unfiltered case. Overall, SPS is an efficient and accurate computational tool for investigating particle pair dynamics at small separations, as well as an interesting platform for developing LES subgrid models designed to accurately reproduce particle clustering.

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Efficient algorithm for simulating homogeneous turbulent shear flow without remeshing

Cited by 48 publications

References 22 publications

Preferential concentration and relative velocity statistics of inertial particles in Navier–Stokes turbulence with and without filtering

Preferential concentration and relative velocity statistics of inertial particles in Navier–Stokes turbulence with and without filtering

Coherent structures in statistically-stationary homogeneous shear turbulence

Investigation of sub-Kolmogorov inertial particle pair dynamics in turbulence using novel satellite particle simulations

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