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Turbulence-obstacle interactions in the Lagrangian framework: Applications for stochastic modeling in canopy flows

Ron Shnapp1,*, Yardena Bohbot-Raviv2, Alex Liberzon1, and Eyal Fattal2

  • 1School of Mechanical Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
  • 2Israel Institute for Biological Research, Ness Ziona 7410001, Israel

  • *ronshnapp@gmail.com

Phys. Rev. Fluids 5, 094601 – Published 1 September, 2020

DOI: https://doi.org/10.1103/PhysRevFluids.5.094601

Abstract

Lagrangian stochastic models are widely used to predict and analyze turbulent dispersion in complex environments, such as in various terrestrial and marine canopy flows. However, due to a lack of empirical data, it is still not understood how particular features of highly inhomogeneous canopy flows affect the Lagrangian statistics. In this work, we study Lagrangian short-time statistics by analyzing empirical Lagrangian trajectories in subvolumes of space that are small in comparison with the canopy height. For the analysis we used 3D Lagrangian trajectories measured in a dense canopy flow model in a wind-tunnel, using an extended version of real-time 3D particle tracking velocimetry. One of our key results is that the random turbulent fluctuations due to the intense dissipation were more dominant than the flow's inhomogeneity in affecting the short-time Lagrangian statistics. This amounts to a so-called quasihomogeneous regime of Lagrangian statistics at small scales. Using the Lagrangian dataset, we calculate the Lagrangian autocorrelation function and the second-order Lagrangian structure-function and extract associated parameters, namely, a Lagrangian velocity decorrelation timescale, Ti, and the Kolmogorov constant, C0. We demonstrate that in the quasihomogeneous regime, both these functions are well represented using a second-order Lagrangian stochastic model that was designed for homogeneous flows. Furthermore, we show that the spatial variations of the Lagrangian separation of scales, Ti/τη, and the Kolmogorov constant, C0, cannot be explained by the variation of the Reynolds number, Reλ, in space, and that Ti/τη was small as compared with homogeneous turbulence predictions at similar Reλ. We thus hypothesize that these characteristics occurred due to the injection of kinetic energy at small scales due to the so-called “wake-production” process, and we show empirical results supporting our hypothesis. These findings shed light on key features of Lagrangian statistics in flows with intense dissipation, and have direct implications for modeling short term dispersion in such complex environments.

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References (84)

  1. R. E. Britter and S. R. Hanna, Flow and dispersion in urban areas, Ann. Rev. Fluid Mech. 35, 469 (2003).
  2. R. Nathan, G. G. Katul, H. S. Horn, S. M. Thomas, R. Oren, R. Avissar, S. W. Pacala, and S. A. Levin, Mechanisms of long-distance dispersal of seeds by wind, Nature 418, 409 (2002).
  3. M. R. Raupach and A. S. Thom, Turbulence in and above plant canopies, Ann. Rev. Fluid Mech. 13, 97 (1981).
  4. M. R. Raupach, A Lagrangian analysis of scalar transfer in vegetation canopies, Quart. J. R. Metereol. Soc. 113, 107 (1987).
  5. E. Gavze and E. Fattal, Description of a turbulent cascade by a Fokker-Planck equation, Bound. Layer Meteorol. 169, 297 (2018).
  6. M. R. Raupach, Applying Lagrangian fluid mechanics to infer scalar source distributions from concentration profiles in plant canopies, Agric. Forest Meteorol. 47, 85 (1989).
  7. T. K. Flesch and J. D. Wilson, A two-dimensional trajectory-simulation model for non-Gaussian, inhomogeneous turbulence within plant canopies, Bound. Layer Meteorol. 61, 349 (1992).
  8. J. D. Wilson and B. L. Sawford, Review of Lagrangian stochastic models for trajectories in the turbulent atmosphere, Bound. Layer Meteorol. 78, 191 (1996).
  9. M. W. Rotach, S.-E. Gryning, and C. Tassone, A two-dimensional Lagrangian stochastic dispersion model for daytime conditions, Quarterly J. R. Meteorol. Soc. 122, 367 (1996).
  10. D. Baldocchi, Flux footprints within and over forest canopies, Bound. Layer Meteorol. 85, 273 (1997).
  11. R. Leuning, O. T. Denmead, A. Miyata, and J. Kim, Source/sink distributions of heat, water vapour, carbon dioxide and methane in a rice canopy estimated using Lagrangian dispersion analysis, Agric. Forest Meteorol. 104, 233 (2000).
  12. D. E. Aylor and T. K. Flesch, Estimating spore release rates using a Lagrangian stochastic simulation model, J. Appl. Meteorol. 40, 1196 (2001).
  13. R. W. Arritt, C. A. Clark, A. S. Goggi, H. Lopez Sanchez, M. E. Westgate, and J. M. Riese, Lagrangian numerical simulations of canopy air flow effects on maize pollen dispersal, Field Crops Res. 102, 151 (2007).
  14. S. C. Gleicher, M. Chamecki, S. A. Isard, Y. Pan, and G. G. Katul, Interpreting three-dimensional spore concentration measurements and escape fraction in a crop canopy using a coupled Eulerian-Lagrangian stochastic model, Agric. Forest Meteorol. 194, 118 (2014).
  15. T. Duman, A. Trakhtenbrot, D. Poggi, M. Cassiani, and G. G. Katul, Dissipation intermittency increases long-distance dispersal of heavy particles in the canopy sublayer, Bound. Layer Meteorol. 159, 41 (2016).
  16. E. Fattal, O. Buchman, and E. Gavze, A Lagrangian-stochastic model for pollutant dispersion in the urban boundary layer over complex terrain—Comparison with Haifa campaigns, in Proceedings of the 23rd Symposium on Boundary Layers and Turbulence (American Meteorological Society, 2018), Vol. 8A, p. 4.
  17. J. Finnigan, Turbulence in plant canopies, Ann. Rev. Fluid Mech. 32, 519 (2000).
  18. D. Poggi, G. G. Katul, and M. Cassiani, On the anomalous bahavior of the Lagrangian structure function similarity constant inside dense canopies, Atmos. Environ. 42, 4212 (2008).
  19. D. J. Thomson, Criteria for the selection of stochastic models of particle trajectories in turbulent flows, J. Fluid Mech. 180, 529 (1987).
  20. A. M. Reynolds, A second-order Lagrangian stochastic model for particle trajectories in inhomogeneous turbulence, Quarterly J. R. Meteorol. Soc. 125, 1735 (1999).
  21. W. J. Massman and J. C. Weil, An analitical one-dimensional second-order closure model for turbulence statistics and the Lagrangian timescale within and above plant canopies of arbitrary structure, Bound. Layer Meteorol. 91, 81 (1999).
  22. Ü. Rannik, M. Aubinet, O. Kurbanmuradov, K. K. Sabelfeld, T. Markkanen, and T. Vesala, Footprint analysis for measurements over a heterogeneous forest, Bound. Layer Meteorol. 97, 137 (2000).
  23. D. Poggi, G. Katul, and J. Albertson, Scalar dispersion within a model canopy: Measurements and three-dimensional Lagrangian models, Adv. Water Res. 29, 326 (2006).
  24. M. R. Raupach, J. J. Finnigan, and Y. Brunet, Coherent eddies and turbulence in vegetative canopies: The mixing-layer analogy, Bound. Layer Meteorol. 78, 351 (1996).
  25. R. H. Shaw and I. Seginer, Calculation of velocity skewness in real and artificial plant canopies, Bound. Layer Meteorol. 39, 315 (1987).
  26. H. M. Nepf, Drag, turbulence, and diffusion in flow through emergent vegetation, Water Res. Res. 35, 479 (1999).
  27. S. B. Pope and Y. L. Chen, The velocity-dissipation probability density function model for turbulent flows, Phys. Fluids A: Fluid Dynam. 2, 1437 (1990).
  28. G. A. Voth, K. Satyanarayan, and E. Bodenschatz, Lagrangian acceleration measurements at large Reynolds numbers, Phys. Fluids 10, 2268 (1998).
  29. S. Ott and J. Mann, An experimental investigation of the relative diffusion of particle pairs in three-dimensional turbulent flow, J. Fluid Mech. 422, 207 (2000).
  30. N. Mordant, J. Delour, E. Léveque, A. Arnéodo, and J.-F. Pinton, Long-Time Correlations in Lagrangian Dynamics: A Key to Intermittency in Turbulence, Phys. Rev. Lett. 89, 254502 (2002).
  31. L. Biferale, G. Boffetta, A. Celani, B. J. Devenish, A. Lanotte, and F. Toschi, Lagrangian statistics of particle pairs in homogeneous isotropic turbulence, Phys. Fluids 17, 115101 (2005).
  32. M. Bourgoin, N. T. Ouellette, H. Xu, J. Berg, and E. Bodenschatz, The role of pair dispersion in turbulent flow, Science 311, 835 (2006).
  33. P. K. Yeung, S. B. Pope, and B. L. Sawford, Reynolds number dependence of Lagrangian statistics in large numerical simulations of isotropic turbulence, J. Turbul. 7, N58 (2006).
  34. N. Ouellette, H. Xu, M. Bourgoin, and E. Bodenschatz, Small-scale anisotropy in Lagrangian turbulence, New J. Phys. 8, 102 (2006).
  35. J. Berg, B. Lüthi, J. Mann, and S. Ott, Backwards and forwards relative dispersion in turbulent flow: an experimental investigation, Phys. Rev. E 74, 016304 (2006).
  36. J. Bec, L. Biferale, M. Cencini, A. S. Lanotte, and F. Toschi, Effects of vortex filaments on the velocity of tracers and heavy particles in turbulence, Phys. Fluids 18, 081702 (2006).
  37. M. Guala, A. Liberzon, A. Tsinober, and W. Kinzelbach, An experimental investigation on Lagrangian correlations of small-scale turbulence at low Reynolds number, J. Fluid Mech. 574, 405 (2007).
  38. R. J. E. Walpot, C. W. M. van der Geld, and J. G. M. Kuerten, Determination of the coefficients of langevin models for inhomogeneous turbulent flows by three-dimensional particle tracking velocimetry and direct numerical simulation, Phys. Fluids 19, 045102 (2007).
  39. A. Arnèodo, R. Benzi, J. Berg, L. Biferale, E. Bodenschatz, A. Busse, E. Calzavarini, B. Castaing, M. Cencini, L. Chevillard, R. T. Fisher, R. Grauer, H. Homann, D. Lamb, A. S. Lanotte, E. Lévèque, B. Lüthi, J. Mann, N. Mordant, W.-C. Müller, S. Ott, N. T. Ouellette, J.-F. Pinton, S. B. Pope, S. G. Roux, F. Toschi, H. Xu, and P. K. Yeung, Universal Intermittent Properties of Particle Trajectories in Highly Turbulent Flows, Phys. Rev. Lett. 100, 254504 (2008).
  40. F. Toschi and E. Bodenschatz, Lagrangian properties of particles in turbulence, Ann. Rev. Fluid Mech. 41, 375 (2009).
  41. A. Liberzon, B. Lüthi, M. Holzner, S. Ott, J. Berg, and J. Mann, On the structure of acceleration in turbulence, Physica D: Nonlin. Phenom. 241, 208 (2012).
  42. R. Scatamacchia, L. Biferale, and F. Toschi, Extreme Events in the Dispersions of Two Neighboring Particles Under the Influence of Fluid Turbulence, Phys. Rev. Lett. 109, 144501 (2012).
  43. A. Di Bernardino, P. Monti, G. Leuzzi, and G. Querzoli, Water-channel estimation of Eulerian and Lagrangian timescales of the turbulence in idealized two-dimensional urban canopies, Bound. Layer Meteorol. 165, 251 (2017).
  44. N. Stelzenmuller, J. I. Polanco, L. Vignal, I. Vinkovic, and N. Mordant, Lagrangian acceleration statistics in a turbulent channel flow, Phys. Rev. Fluids 2, 054602 (2017).
  45. J. I. Polanco, I. Vinkovic, N. Stelzenmuller, N. Mordant, and M. Bourgoin, Relative dispersion of particle pairs in turbulent channel flow, Inte. J. Heat Fluid Flow 71, 231 (2018).
  46. R. Shnapp and A. Liberzon, Generalization of turbulent pair dispersion to large initial separations, Phys. Rev. Lett. 120, 244502 (2018).
  47. A. Celani, M. Cencini, M. Vergassola, E. Villermaux, and D. Vincenzi, Shear effects on passive scalar spectra, J. Fluid Mech. 523, 99 (2005).
  48. E. Pitton, C. Marchioli, V. Lavezzo, A. Soldati, and F. Toschi, Anisotropy in pair dispersion of inertial particles in turbulent channel flow, Phys. Fluids 24, 073305 (2012).
  49. R. Shnapp, E. Shapira, D. Peri, Y. Bohbot-Raviv, E. Fattal, and A. Liberzon, Extended 3D-PTV for direct measurements of Lagrangian statistics of canopy turbulence in a wind tunnel, Sci. Rep. 9, 7405 (2019).
  50. Y. Bohbot-Raviv, R. Shnapp, A. Liberzon, V. Babin, M. Hotoveli, A. Shick, and E. Fattal, Turbulence statistics of canopy-flows using novel Lagrangian measurements within an environmental wind tunnel, in Physmod 2017: International Workshop on Physical Modelling of Flow and Dispersion Phenomena Dynamics of Urban and Coastal Atmosphere, LHEEA École Centrale de Nantes, France (2017), pp. 162–169, https://physmod2017.sciencesconf.org/data/pages/book_physmod2017_en.pdf.
  51. C. W. Gardiner, Handbook of Stochastic Methods for Physics, Chemistry, and the Natural Sciences (Springer, Berlin, 1997).
  52. J. L. Doob, The Brownian movement and stochastic equations, Ann. Math. 43, 351 (1942).
  53. M. Obukhov, A description of turbulence in terms of Lagrangian variables, Vol. 6 of Advances in Geophysics (Elsevier, Amsterdam, 1959), pp. 113–116.
  54. A. S. Monin and A. M. Yaglom, Statistical Fluid Mechanics (Dover Publications, Mineola, NY, 1972).
  55. M. S. Borgas and B. L. Sawford, Stochastic equations with multifractal random increments for modeling turbulent dispersion, Phys. Fluids 6, 618 (1994).
  56. J. D. Wilson, E. Yee, N. Ek, and R. d'Amours, Lagrangian simulation of wind transport in the urban environment, Quart. J. R. Meteorol. Soc. 135, 1586 (2009).
  57. T. Duman, G. G. Katul, M. B. Siqueira, and M. Cassiani, A velocity-dissipation Lagrangian stochastic model for turbulent dispersion in atmospheric boundary-layer and canopy flows, Bound. Layer Meteorol. 152, 1 (2014).
  58. B. L. Sawford, Reynolds number effects in Lagrangian stochastic models of turbulent dispersion, Phys. Fluids A: Fluid Dynam. 3, 1577 (1991).
  59. S. Du, B. L. Sawford, J. D. Wilson, and D. J. Wilson, Estimation of the Kolmogorov constant (c0) for the Lagrangian structure function, using a second-order Lagrangian model of grid turbulence, Phys. Fluids 7, 3083 (1995).
  60. Th. Dracos, Three-Dimensional Velocity and Vorticity Measuring and Image Analysis Technique: Lecture Notes from the short course held in Zurich, Switzerland (Kluwer Academic Publisher, Dordrecht, 1996).
  61. OpenPTV consortium, Open source particle tracking velocimetry (2014), http://www.openptv.net.
  62. Y. Meller and A. Liberzon, Particle data management software for 3D particle tracking velocimetry and related applications—The flowtracks package, J. Open Res. Softw. 4, e23 (2016).
  63. R. Shnapp, Wind tunnel canopy flow 3D-PTV, YouTube (2018), https://www.youtube.com/watch?v=NMPCWiWUqrY.
  64. A. N. Kolmogorov, The local structure of turbulence in incompressible viscous fluid for very large Reynolds numbers, Cr Acad. Sci. URSS 30, 301 (1941).
  65. K. R. Sreenivasan, On the universality of the Kolmogorov constant, Phys. Fluids 7, 2778 (1995).
  66. M. Chamecki and N. L. Dias, The local isotropy hypothesis and the turbulent kinetic energy dissipation rate in the atmospheric surface layer, Quart. J. Roy. Meteor. Soc. 130, 2733 (2752).
  67. D. Poggi and G. G. Katul, Evaluation of the turbulent kinetic energy dissipation rate inside canopies by zero- and level-crossing density methods, Bound. Layer Meteorol. 136, 219 (2010).
  68. S. B. Pope, Turbulent Flows (Cambridge University Press, Cambridge, 2000).
  69. H. Tennekes and J. L. Lumley, A First Course in Turbulence (The MIT Press, Cambridge, MA, 1972).
  70. N. Mordant, E. Lévêque, and J.-F. Pinton, Experimental and numerical study of the Lagrangian dynamics of high Reynolds turbulence, New J. Phys. 6, 116 (2004).
  71. L. Biferale, E. Bodenschatz, M. Cencini, A. S. Lanotte, N. T. Ouellette, F. Toschi, and H. Xu, Lagrangian structure functions in turbulence: A quantitative comparison between experiment and direct numerical simulation, Phys. Fluids 20, 065103 (2008).
  72. W. K. George, P. D. Beuther, and J. L. Lumley, Processing of random signals, in Proceedings of the Dynamic Flow Conference 1978 on Dynamic Measurements in Unsteady Flows (Springer, Dordrecht, 1978).
  73. G. I. Taylor, Diffusion by continuous movements, Proc. London Math. Soc. s2-20, 196 (1921).
  74. C. Vanderwel and B. Ganapathisubramani, Turbulent boundary layers over multiscale rough patches, Bound. Layer Meteorol. 172, 1 (2019).
  75. R. H. Shaw, Y. Brunet, J. J. Finnigan, and M. R. Raupach, A wind tunnel study of air flow in waving wheat: Two-point velocity statistics, Bound. Layer Meteorol. 76, 349 (1995).
  76. P. K. Yeung and S. B. Pope, Lagrangian statistics from direct numerical simulations of isotropic turbulence, J. Fluid Mech. 207, 531 (1989).
  77. N. Mordant, P. Metz, O. Michel, and J. F. Pinton, Measurement of Lagrangian Velocity in Fully Developed Turbulence, Phys. Rev. Lett. 87, 214501 (2001).
  78. B. L. Sawford and P. K. Yeung, Kolmogorov similarity scaling for one-particle Lagrangian statistics, Phys. Fluids 23, 091704 (2011).
  79. H. Yu, K. Kanov, E. Perlman, J. Graham, E. Frederix, R. Burns, A. Szalay, G. Eyink, and C. Meneveau, Studying Lagrangian dynamics of turbulence using on-demand fluid particle tracking in a public turbulence database, J. Turbul. 13, N12 (2012).
  80. R.-C. Lien and E. A. D'Asaro, The Kolmogorov constant for the Lagrangian velocity spectrum and structure function, Phys. Fluids 14, 4456 (2002).
  81. B. L. Sawford, P. K. Yeung, and J. F. Hackl, Reynolds number dependence of relative dispersion statistics in isotropic turbulence, Phys. Fluids 20, 065111 (2008).
  82. Y. Li, E. Perlman, M. Wan, Y. Yang, R. Burns, 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. Turbul. 9, N31 (2008).
  83. D. Poggi, A. Porporato, L. Ridolfi, J. D. Albertson, and G. G. Katul, The effect of vegetation density on canopy sublayer turbulence, Bound. Layer Meteorol. 111, 565 (2004).
  84. H. Xia, N. Francois, H. Punzmann, and M. Shats, Lagrangian scale of particle dispersion in turbulence, Nature Commun. 4, 2013 (2013).

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