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Clustering of vector nulls in homogeneous isotropic turbulence
Phys. Rev. Fluids 6, 024609 – Published 26 February, 2021
DOI: https://doi.org/10.1103/PhysRevFluids.6.024609
Abstract
We analyze the vector nulls of velocity, Lagrangian acceleration, and vorticity, coming from direct numerical simulations of forced homogeneous isotropic turbulence at . We show that the clustering of velocity nulls is much stronger than those of acceleration and vorticity nulls. These acceleration and vorticity nulls, however, are denser than the velocity nulls. We study the scaling of clusters of these null points with and with characteristic turbulence lengthscales. We also analyze datasets of point inertial particles with Stokes numbers , 3, and 6, at . Inertial particles display preferential concentration with a degree of clustering that resembles some properties of the clustering of the Lagrangian acceleration nulls, in agreement with the proposed sweep-stick mechanism of clustering formation.
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References (72)
- T. Ishihara, Y. Kaneda, and J. C. Hunt, Thin shear layers in high Reynolds number turbulence—DNS results, Flow, Turbul. Combust. 91, 895 (2013).
- F. Moisy and J. Jiménez, Geometry and clustering of intense structures in isotropic turbulence, J. Fluid Mech. 513, 111 (2004).
- M. Tanahashi, K. Fujibayashi, and T. Miyauchi, Fine scale eddy cluster and energy cascade in homogeneous isotropic turbulence, in Proceedings of the IUTAM Symposium on Computational Physics and New Perspectives in Turbulence (Springer, Berlin, 2008), pp. 67–72.
- T. Itoh, Y. Naka, Y. Minamoto, M. Shimura, and M. Tanahashi, Large-scale clustering of coherent fine-scale eddies in a turbulent mixing layer, Int. J. Heat Fluid Flow 72, 100 (2018).
- S. Goto and J. Vassilicos, Particle pair diffusion and persistent streamline topology in two-dimensional turbulence, New J. Phys. 6, 65 (2004).
- J. Dávila and J. C. Vassilicos, Richardson's Pair Diffusion and the Stagnation Point Structure of Turbulence, Phys. Rev. Lett. 91, 144501 (2003).
- P. McGavin and D. I. Pontin, Reconnection of vortex tubes with axial flow, Phys. Rev. Fluids 4, 024701 (2019).
- L. Chen, S. Goto, and J. Vassilicos, Turbulent clustering of stagnation points and inertial particles, J. Fluid Mech. 553, 143 (2006).
- K. Sreenivasan, A. Prabhu, and R. Narasimha, Zero-crossings in turbulent signals, J. Fluid Mech. 137, 251 (1983).
- S. Goto and J. Vassilicos, The dissipation rate coefficient of turbulence is not universal and depends on the internal stagnation point structure, Phys. Fluids 21, 035104 (2009).
- H. W. Liepmann and M. S. Robinson, Counting Methods and Equipment for Mean-Value Measurements in Turbulence Research (National Advisory Committee for Aeronautics, Washington, DC, 1953).
- T. Faber and J. C. Vassilicos, Turbulent pair separation due to multiscale stagnation point structure and its time asymmetry in two-dimensional turbulence, Phys. Fluids 21, 015106 (2009).
- S. Coleman and J. Vassilicos, A unified sweep-stick mechanism to explain particle clustering in two-and three-dimensional homogeneous, isotropic turbulence, Phys. Fluids 21, 113301 (2009).
- M. Uhlmann and A. Chouippe, Clustering and preferential concentration of finite-size particles in forced homogeneous-isotropic turbulence, J. Fluid Mech. 812, 991 (2017).
- S. O. Rice, Mathematical analysis of random noise, Bell Syst. Tech. J. 24, 46 (1945).
- M. Obligado, T. Teitelbaum, A. Cartellier, P. Mininni, and M. Bourgoin, Preferential concentration of heavy particles in turbulence, J. Turbul. 15, 293 (2014).
- S. Sumbekova, A. Cartellier, A. Aliseda, and M. Bourgoin, Preferential concentration of inertial sub-Kolmogorov particles: The roles of mass loading of particles, Stokes numbers, and Reynolds numbers, Phys. Rev. Fluids 2, 24302 (2017).
- J. Yao and F. Hussain, A physical model of turbulence cascade via vortex reconnection sequence and avalanche, J. Fluid Mech. 883, A51 (2020).
- L.-P. Wang and M. R. Maxey, Settling velocity and concentration distribution of heavy particles in homogeneous isotropic turbulence, J. Fluid Mech. 256, 27 (1993).
- T. Faber and J. C. Vassilicos, Acceleration-based classification and evolution of fluid flow structures in two-dimensional turbulence, Phys. Rev. E 82, 026312 (2010).
- S. Goto and J. Vassilicos, Self-similar clustering of inertial particles and zero-acceleration points in fully developed two-dimensional turbulence, Phys. Fluids 18, 115103 (2006).
- L. Baker, A. Frankel, A. Mani, and F. Coletti, Coherent clusters of inertial particles in homogeneous turbulence, J. Fluid Mech. 833, 364 (2017).
- J.-S. Ferenc and Z. Néda, On the size distribution of poisson voronoi cells, Physica A 385, 518 (2007).
- R. Monchaux, M. Bourgoin, and A. Cartellier, Preferential concentration of heavy particles: A Voronoï analysis, Phys. Fluids 22, 103304 (2010).
- F. Falkinhoff, M. Obligado, M. Bourgoin, and P. D. Mininni, Preferential Concentration of Free-Falling Heavy Particles in Turbulence, Phys. Rev. Lett. 125, 064504 (2020).
- S. B. Pope, Turbulent Flows (Cambridge University Press, Cambridge, UK, 2000).
- P. D. Mininni, D. Rosenberg, R. Reddy, and A. Pouquet, A hybrid MPI–OpenMP scheme for scalable parallel pseudospectral computations for fluid turbulence, Parallel Comput. 37, 316 (2011).
- D. Rosenberg, P. D. Mininni, R. Reddy, and A. Pouquet, Gpu parallelization of a hybrid pseudospectral geophysical turbulence framework using cuda, Atmosphere 11, 178 (2020).
- Y. Li, E. Perlman, M. Wan, Y. Yang, C. Meneveau, R. Burns, S. Chen, A. Szalay, and G. Eyink, A public turbulence database cluster and applications to study lagrangian evolution of velocity increments in turbulence, J. Turbulence 9, N31 (2008).
- P. K. Yeung, D. A. Donzis, and K. R. Sreenivasan, Dissipation, enstrophy and pressure statistics in turbulence simulations at high reynolds numbers, J. Fluid Mech. 700, 5 (2012).
- D. Donzis and P. Yeung, Resolution effects and scaling in numerical simulations of passive scalar mixing in turbulence, Physica D 239, 1278 (2010).
- D. Buaria, A. Pumir, E. Bodenschatz, and P.-K. Yeung, Extreme velocity gradients in turbulent flows, New J. Phys. 21, 043004 (2019).
- M. Wan, S. Oughton, S. Servidio, and W. H. Matthaeus, On the accuracy of simulations of turbulence, Phys. Plasmas 17, 082308 (2010).
- P. Weiss, D. Oberle, D. W. Meyer, and P. Jenny, Impact of turbulence forcing schemes on particle clustering, Phys. Fluids 31, 061703 (2019).
- P. Kailasnath and K. Sreenivasan, Zero crossings of velocity fluctuations in turbulent boundary layers, Phys. Fluids A: Fluid Dynam. 5, 2879 (1993).
- E. Ott, Y. Du, K. R. Sreenivasan, A. Juneja, and A. K. Suri, Sign-Singular Measures: Fast Magnetic Dynamos, and High-Reynolds-Number Fluid Turbulence, Phys. Rev. Lett. 69, 2654 (1992).
- L. Sorriso-Valvo, V. Carbone, A. Noullez, H. Politano, A. Pouquet, and P. Veltri, Analysis of cancellation in two-dimensional magnetohydrodynamic turbulence, Phys. Plasmas 9, 89 (2002).
- P. Rodriguez Imazio and P. D. Mininni, Cancellation exponents in helical and nonhelical flows, J. Fluid Mech. 651, 241 (2010).
- P. Yeung and S. Pope, An algorithm for tracking fluid particles in numerical simulations of homogeneous turbulence, J. Comput. Phys. 79, 373 (1988).
- S. Angriman, P. D. Mininni, and P. J. Cobelli, Velocity and acceleration statistics in particle-laden turbulent swirling flows, Phys. Rev. Fluids 5, 064605 (2020).
- M. Taghizadeh-Popp, J. W. Kim, G. Lemson, D. Medvedev, M. J. Raddick, A. S. Szalay, A. R. Thakar, J. Booker, C. Chhetri, L. Dobos et al., SciServer: A science platform for astronomy and beyond, Astron. Comput. 33, 100412 (2020).
- V. Ramasubramani, B. D. Dice, E. S. Harper, M. P. Spellings, J. A. Anderson, and S. C. Glotzer, Freud: A software suite for high throughput analysis of particle simulation data, Comput. Phys. Commun. 254, 107275 (2020).
- A. L. Haynes and C. E. Parnell, A trilinear method for finding null points in a three-dimensional vector space, Phys. Plasmas 14, 082107 (2007).
- A. Haynes and C. Parnell, A method for finding three-dimensional magnetic skeletons, Phys. Plasmas 17, 092903 (2010).
- N. A. Murphy, C. E. Parnell, and A. L. Haynes, The appearance, motion, and disappearance of three-dimensional magnetic null points, Phys. Plasmas 22, 102117 (2015).
- W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling et al., Numerical Recipes, Vol. 3 (Cambridge University Press, Cambridge, UK, 1989).
- V. Dallas, J. C. Vassilicos, and G. F. Hewitt, Stagnation point von Kármán coefficient, Phys. Rev. E 80, 046306 (2009).
- M. Tanemura, Statistical distributions of Poisson Voronoi cells in two and three dimensions, Forma-Tokyo 18, 221 (2003).
- A. Okubo, Horizontal dispersion of floatable particles in the vicinity of velocity singularities such as convergences, Deep Sea Res. Oceangraph. Abs. 17, 445 (1970).
- A. D. Bragg, P. J. Ireland, and L. R. Collins, Mechanisms for the clustering of inertial particles in the inertial range of isotropic turbulence, Phys. Rev. E 92, 023029 (2015).
- S. Corrsin, Turbulence: Experimental methods, in Handbuch der Physik, edited by S. Flügge and C. Truesdell (Springer, 1963), pp. 524–589.
- D. O. Mora and M. Obligado, Estimating the integral length scale on turbulent flows from the zero crossings of the longitudinal velocity fluctuation, Exp. Fluids 61, 199 (2020).
- J. M. Smith, K. I. Hopcraft, and E. Jakeman, Fluctuations in the zeros of differentiable gaussian processes, Phys. Rev. E 77, 031112 (2008).
- S. Orey, Gaussian sample functions and the Hausdorf dimension of level crossings, Z. Wahrscheinlichkeitstheorie Verw Geb. 15, 249 (1970).
- M. Uhlmann and T. Doychev, Sedimentation of a dilute suspension of rigid spheres at intermediate Galileo numbers: The effect of clustering upon the particle motion, J. Fluid Mech. 752, 310 (2014).
- D. O. Mora, A. Aliseda, A. Cartellier, and M. Obligado, Characterizing 1D inertial particle clustering, arXiv:1906.09896.
- S. Frühwirth-Schnatter, Finite Mixture and Markov Switching Models (Springer Science & Business Media, Berlin, 2006).
- A. Chouippe and M. Uhlmann, On the influence of forced homogeneous-isotropic turbulence on the settling and clustering of finite-size particles, Acta Mech. 230, 387 (2019).
- I. A. Ibragimov, A note on the central limit theorems for dependent random variables, Theory Probab. Appl. 20, 135 (1975).
- R. C. Bradley, Jr, Central limit theorems under weak dependence, J. Multivariate Anal. 11, 1 (1981).
- H. Yoshimoto and S. Goto, Self-similar clustering of inertial particles in homogeneous turbulence, J. Fluid Mech. 577, 275 (2007).
- M. Momenifar and A. D. Bragg, Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence, Phys. Rev. Fluids 5, 034306 (2020).
- J. Bec, L. Biferale, G. Boffetta, A. Celani, M. Cencini, A. Lanotte, S. Musacchio, and F. Toschi, Acceleration statistics of heavy particles in turbulence, J. Fluid Mech. 550, 349 (2006).
- P. Huck, C. Bateson, R. Volk, A. Cartellier, M. Bourgoin, and A. Aliseda, The role of collective effects on settling velocity enhancement for inertial particles in turbulence, J. Fluid Mech. 846, 1059 (2018).
- A. Aliseda, A. Cartellier, F. Hainaux, and J. C. Lasheras, Effect of preferential concentration on the settling velocity of heavy particles in homogeneous isotropic turbulence, J. Fluid Mech. 468, 77 (2002).
- S. Elghobashi, On predicting particle-laden turbulent flows, Appl. Sci. Res. 52, 309 (1994).
- S. Balachandar and J. K. Eaton, Turbulent dispersed multiphase flow, Annu. Rev. Fluid Mech. 42, 111 (2010).
- D. O. Mora, A. Cartellier, and M. Obligado, Experimental estimation of turbulence modification by inertial particles at moderate , Phys. Rev. Fluids 4, 074309 (2019).
- A. J. Petersen, L. Baker, and F. Coletti, Experimental study of inertial particles clustering and settling in homogeneous turbulence, J. Fluid Mech. 864, 925 (2019).
- R. Monchaux and A. Dejoan, Settling velocity and preferential concentration of heavy particles under two-way coupling effects in homogeneous turbulence, Phys. Rev. Fluids 2, 104302 (2017).
- T. Wittemeier and J. S. Shrimpton, Explanation of differences in experimental and computational results for the preferential concentration of inertial particles, Comput. Fluids 173, 37 (2018).
- www.sciserver.org.