Abstract
The absence of sub-grid scale (SGS) motions leads to severe errors in particle pair dynamics, which represents a great challenge to the large eddy simulation of particle-laden turbulent flow. In order to address this issue, data from direct numerical simulation (DNS) of homogenous isotropic turbulence coupled with Lagrangian particle tracking are used as a benchmark to evaluate the corresponding results of filtered DNS (FDNS). It is found that the filtering process in FDNS will lead to a non-monotonic variation of the particle collision statistics, including radial distribution function, radial relative velocity, and the collision kernel. The peak of radial distribution function shifts to the large-inertia region due to the lack of SGS motions, and the analysis of the local flowstructure characteristic variable at particle position indicates that the most effective interaction scale between particles and fluid eddies is increased in FDNS. Moreover, this scale shifting has an obvious effect on the odd-order moments of the probability density function of radial relative velocity, i.e. the skewness, which exhibits a strong correlation to the variance of radial distribution function in FDNS. As a whole, the radial distribution function, together with radial relative velocity, can compensate the SGS effects for the collision kernel in FDNS when the Stokes number based on the Kolmogorov time scale is greater than 3.0. However, it still leaves considerable errors for \({ St}_\mathrm{k }<3.0\).
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Abbreviations
- DPM:
-
Discrete particle model
- FDNS:
-
Filtered direct numerical simulation
- HIT:
-
Homogeneous isotropic turbulence
- LES:
-
Large eddy simulation
- PDF:
-
Probability density function
- RDF (g):
-
Radial distribution function (dimensionless)
- SGS:
-
Sub-grid scale
- SPS:
-
Satellite particle simulation
- L :
-
Length of the simulation domain
- \(N_{\mathrm{cell} }\) :
-
Number of cells in the simulation field
- \(N_{\mathrm{p} }\) :
-
Number of particles
- d :
-
Diameter of particle
- R :
-
Separation distance of particle pair at collision radius
- r :
-
Separation distance of particle pair
- \(V_\mathrm{field} \) :
-
Volume of the domain
- \(V_s \) :
-
Volume of the annulus with radius r
- \({ St}_\mathrm{k }\) :
-
Particle Stokes number based on the Kolmogorov scale
- \(S_{ij,\mathrm{p}} \) :
-
Strain tensor rate of the flow at particle location
- \(R_{ij,\mathrm{p}} \) :
-
Rotation tensor rate of the flow at particle location
- r.m.s.:
-
Root mean square
- \(w_\mathrm{r}\) :
-
Radial relative velocity (dimensionless)
- \(w_\mathrm{r}^- \) :
-
Radial relative velocity in inward direction
- \(\beta \) :
-
Particle collision kernel
- \(\tau _\mathrm{p} \) :
-
Particle relaxation time
- \(\tau _\mathrm{k}\) :
-
Kolmogorov time scale of turbulence
- \({{\varvec{T}}}_{\mathrm{E }}\) :
-
Eulerian integral time scale of turbulence
- \(\eta \) :
-
Kolmogorov length scale of turbulence
- \(\nu _\mathrm{k} \) :
-
Kolmogorov velocity of the turbulence
References
Grabowski, W.W., Wang, L.P.: Growth of cloud droplets in a turbulent environment. Annu. Rev. Fluid Mech. 45, 293–324 (2013)
Liubin, P., Paolo, P.: Turbulence-induced relative velocity of dust particles. IV. Collis Kernel. Astrophys. J. 797, 101 (2014)
Senior, R.C., Grace, J.R.: Integrated particle collision and turbulent diffusion model for dilute gas-solid suspensions. Powder Technol. 96, 48–78 (1998)
Squires, K.D., Eaton, J.K.: Preferential concentration of particles by turbulence. Phys. Fluids A Fluid Dyn. 3, 1169–1178 (1991)
Wang, L.P., Maxey, M.R.: Settling velocity and concentration distribution of heavy particles in homogeneous isotropic turbulence. J. Fluid Mech. 256, 27–68 (1993)
Dejoan, A., Monchaux, R.: Preferential concentration and settling of heavy particles in homogeneous turbulence. Phys. Fluids 25, 013301–013316 (2013)
Reade, W.C., Collins, L.R.: Effect of preferential concentration on turbulent collision rates. Phys. Fluids 12, 2530–2540 (2000)
Luo, K., Fan, J., Jin, H., et al.: LES of the turbulent coherent structures and particle dispersion in the gas-solid wake flows. Powder Technol. 147, 49–58 (2004)
Sun, W., Zhong, W., Zhang, Y.: LES-DPM simulation of turbulent gas-particle flow on opposed round jets. Powder Technol. 270, 302–311 (2015)
Wang, T., He, Y., Yan, S., et al.: Cluster granular temperature and rotational characteristic analysis of a binary mixture of particles in a gas-solid riser by mutative Smagorinsky constant SGS model. Powder Technol. 286, 73–83 (2015)
Wang, Q., Squires, K.D.: Large eddy simulation of particle laden turbulent channel flow. Phys. Fluids 8, 1207–1223 (1996)
Fede, P., Simonin, O.: Numerical study of the subgrid fluid turbulence effects on the statistics of heavy colliding particles. Phys. Fluids 18, 045103 (2006)
Pozorski, J., Apte, S.V.: Filtered particle tracking in isotropic turbulence and stochastic modeling of subgrid-scale dispersion. Int. J. Multiph. Flow 35, 118–128 (2009)
Jin, G., He, G.-W., Wang, L.-P.: Large-eddy simulation of turbulent collision of heavy particles in isotropic turbulence. Phys. Fluids 22, 055106 (2010)
Voßkuhle, M., Pumir, A., Lévêque, E., et al.: Prevalence of the sling effect for enhancing collision rates in turbulent suspensions. J. Fluid Mech. 749, 841–852 (2014)
Ray, B., Collins, L.R.: Preferential concentration and relative velocity statistics of inertial particles in Navier Stokes turbulence with and without filtering. J. Fluid Mech. 680, 488–510 (2011)
Benyahia, S., Sundaresan, S.: Do we need sub-grid scale corrections for both continuum and discrete gas-particle flow models? Powder Technol. 220, 2–6 (2012)
Chen, J., Jin, G.: Large-eddy simulation of turbulent preferential concentration and collision of bidisperse heavy particles in isotropic turbulence. Powder Technol. 314, 281–290 (2017)
Fede, P., Simonin, O., Villedieu, P., et al.: Stochastic modeling of the turbulent subgrid fluid velocity along inertial particle trajectories. In: Proceedings of the Summer Program, 247–258. Stanford, USA (2006)
Berrouk, A., Laurence, D., Riley, J., et al.: Stochastic Modeling of Fluid Velocity Seen by Heavy Particles for Two-Phase LES of Non-homogeneous and Anisotropic Turbulent Flows. Springer, Netherlands (2007)
Shotorban, B., Mashayek, F.: A stochastic model for particle motion in large-eddy simulation. J. Turbul. 7, N18 (2006)
Bini, M., Jones, W.P.: Large-eddy simulation of particle-laden turbulent flows. J. Fluid Mech. 614, 207–252 (2008)
Jin, G.D., He, G.W.: A nonlinear model for the subgrid timescale experienced by heavy particles in large eddy simulation of isotropic turbulence with a stochastic differential equation. New J. Phys. 15, 035011 (2013)
Wang, L.-P., Wexler, A.S., Zhou, Y.: Statistical mechanical description and modelling of turbulent collision of inertial particles. J. Fluid Mech. 415, 117–153 (2000)
Bec, J., Biferale, L., Cencini, M., et al.: Intermittency in the velocity distribution of heavy particles in turbulence. J. Fluid Mech. 646, 527–536 (2010)
Park, G.I., Bassenne, M., Urzay, J., et al.: A simple dynamic subgrid-scale model for LES of particle-laden turbulence. Phys. Rev. Fluids 2, 044301 (2017)
Leonid, I.Z.: Vladimir: statistical models for predicting pair dispersion and particle clustering in isotropic turbulence and their applications. New J. Phys. 11, 103018 (2009)
Zaichik, L.I., Alipchenkov, V.M.: Statistical models for predicting particle dispersion and preferential concentration in turbulent flows. Int. J. Heat Fluid Flow 26, 416–430 (2005)
Zaichik, L.I., Alipchenkov, V.M.: Pair dispersion and preferential concentration of particles in isotropic turbulence. Phys. Fluids 15, 1776–1787 (2003)
Chun, J., Koch, D.L., Rani, S.L., et al.: Clustering of aerosol particles in isotropic turbulence. J. Fluid Mech. 536, 219–251 (2005)
Rani, S.L., Dhariwal, R., Koch, D.L.: A stochastic model for the relative motion of high Stokes number particles in isotropic turbulence. J. Fluid Mech. 756, 870–902 (2014)
Ray, B., Collins, L.R.: Investigation of sub-Kolmogorov inertial particle pair dynamics in turbulence using novel satellite particle simulations. J. Fluid Mech. 720, 192–211 (2013)
Mazzitelli, I.M., Fornarelli, F., Lanotte, A.S., et al.: Pair and multi-particle dispersion in numerical simulations of convective boundary layer turbulence. Phys. Fluids 26, 055110 (2014)
He, G., Jin, G., Yang, Y.: Space-time correlations and dynamic coupling in turbulent flows. Annu. Rev. Fluid Mech. 49, 51–70 (2017)
Guo, L., Li, D., Zhang, X., et al.: LES prediction of space-time correlations in turbulent shear flows. Acta Mech. Sin. 28, 993–998 (2012)
Zhao, X., He, G.-W.: Space-time correlations of fluctuating velocities in turbulent shear flows. Phys. Rev. E 79, 046316 (2009)
He, G.-W., Wang, M., Lele, S.K.: On the computation of space-time correlations by large-eddy simulation. Phys. Fluids 16, 3859–3867 (2004)
Eswaran, V., Pope, S.B.: An examination of forcing in direct numerical simulations of turbulence. Comput. Fluids 16, 257–278 (1988)
Balachandar, S., Maxey, M.R.: Methods for evaluating fluid velocities in spectral simulations of turbulence. J. Comput. Phys. 83, 96–125 (1989)
Sundaram, S., Collins, L.R.: Collision statistics in an isotropic particle-laden turbulent suspension. Part 1. Direct numerical simulations. J. Fluid Mech. 335, 75–109 (1997)
Maxey, M.R.: The gravitational settling of aerosol particles in homogeneous turbulence and random flow fields. J. Fluid Mech. 174, 441–465 (1987)
Salazar, J.P.L.C., Collins, L.R.: Inertial particle relative velocity statistics in homogeneous isotropic turbulence. J. Fluid Mech. 696, 45–66 (2012)
Kruis, F.E., Kusters, K.A.: The collision rate of particles in turbulent flow. Chem. Eng. Commun. 158, 201–230 (1997)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grants 51390494, 51306065, and 51276076), the Foundation of State Key Laboratory of Coal Combustion (Grant FSKLCCB1702).
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Xiong, Y., Li, J., Liu, Z. et al. The influence of sub-grid scale motions on particle collision in homogeneous isotropic turbulence. Acta Mech. Sin. 34, 22–36 (2018). https://doi.org/10.1007/s10409-017-0720-5
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DOI: https://doi.org/10.1007/s10409-017-0720-5