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Evidence of preferential sweeping during snow settling in atmospheric turbulence

Published online by Cambridge University Press:  04 October 2021

Jiaqi Li Open the ORCID record for Jiaqi Li [Opens in a new window] ,
Aliza Abraham Open the ORCID record for Aliza Abraham [Opens in a new window] ,
Michele Guala Open the ORCID record for Michele Guala [Opens in a new window]  and
Jiarong Hong Open the ORCID record for Jiarong Hong [Opens in a new window]
Jiaqi Li
Affiliation:
Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN 55455, USA Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
Aliza Abraham
Affiliation:
Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN 55455, USA Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
Michele Guala
Affiliation:
Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN 55455, USA Department of Civil, Environmental and Geo- Engineering, University of Minnesota, Minneapolis, MN 55455, USA
Jiarong Hong*
Affiliation:
Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN 55455, USA Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN 55455, USA
*
†Email address for correspondence: [email protected]
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Abstract

We present a field study of snow settling dynamics based on simultaneous measurements of the atmospheric flow field and snow particle trajectories. Specifically, a super-large-scale particle image velocimetry (SLPIV) system using natural snow particles as tracers is deployed to quantify the velocity field and identify vortex structures in a 22 m $\times$ 39 m field of view centred 18 m above the ground. Simultaneously, we track individual snow particles in a 3 m $\times$ 5 m sample area within the SLPIV using particle tracking velocimetry. The results reveal the direct linkage among vortex structures in atmospheric turbulence, the spatial distribution of snow particle concentration and their settling dynamics. In particular, with snow turbulence interaction at near-critical Stokes number, the settling velocity enhancement of snow particles is multifold, and larger than what has been observed in previous field studies. Super-large-scale particle image velocimetry measurements show a higher concentration of snow particles preferentially located on the downward side of the vortices identified in the atmospheric flow field. Particle tracking velocimetry, performed on high resolution images around the reconstructed vortices, confirms the latter trend and provides statistical evidence of the acceleration of snow particles, as they move toward the downward side of vortices. Overall, the simultaneous multi-scale particle imaging presented here enables us to directly quantify the salient features of preferential sweeping, supporting it as an underlying mechanism of snow settling enhancement in the atmospheric surface layer.

JFM classification

Geophysical and Geological Flows: Atmospheric flows Multiphase and Particle-laden Flows: Particle/fluid flow Turbulent Flows: Turbulent boundary layers
Type
JFM Papers
Information
Journal of Fluid Mechanics , Volume 928 , 10 December 2021 , A8
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Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

REFERENCES

Abraham, A. & Hong, J. 2020 Dynamic wake modulation induced by utility-scale wind turbine operation. Appl. Energy 257, 114003.CrossRefGoogle Scholar
Adrian, R.J., Christensen, K.T. & Liu, Z.C. 2000 Analysis and interpretation of instantaneous turbulent velocity fields. Exp. Fluids 29 (3), 275–290.CrossRefGoogle Scholar
Aliseda, A., Cartellier, A., Hainaux, F. & Lasheras, J.C. 2002 Effect of preferential concentration on the settling velocity of heavy particles in homogeneous isotropic turbulence. J. Fluid Mech. 468, 77–105.CrossRefGoogle Scholar
Ayyalasomayajula, S., Gylfason, A., Collins, L.R., Bodenschatz, E. & Warhaft, Z. 2006 Lagrangian measurements of inertial particle accelerations in grid generated wind tunnel turbulence. Phys. Rev. Lett. 97 (14), 144507.CrossRefGoogle ScholarPubMed
Baker, L., Frankel, A., Mani, A. & Coletti, F. 2017 Coherent clusters of inertial particles in homogeneous turbulence. J. Fluid Mech. 833, 364–398.CrossRefGoogle Scholar
Balachandar, S. & Eaton, J.K. 2010 Turbulent dispersed multiphase flow. Annu. Rev. Fluid Mech. 42, 111–133.CrossRefGoogle Scholar
Banko, A.J., Villafañe, L., Kim, J.H., Esmaily, M. & Eaton, J.K. 2019 Stochastic modeling of direct radiation transmission in particle-laden turbulent flow. J. Quant. Spectrosc. Radiat. Transfer 226, 1–18.CrossRefGoogle Scholar
Bec, J., Biferale, L., Boffetta, G., Celani, A., Cencini, M., Lanotte, A., Musacchio, S. & Toschi, F. 2006 Acceleration statistics of heavy particles in turbulence. J. Fluid Mech. 550, 349–358.CrossRefGoogle Scholar
Böhm, H.P. 1989 A general equation for the terminal fall speed of solid hydrometeors. J. Atmos. Sci. 46 (15), 2419–2427.2.0.CO;2>CrossRefGoogle Scholar
Christensen, K.T. & Adrian, R.J. 2001 Statistical evidence of hairpin vortex packets in wall turbulence. J. Fluid Mech. 431, 433–443.CrossRefGoogle Scholar
Crocker, J.C. & Grier, D.G. 1996 Methods of digital video microscopy for colloidal studies. J. Colloid Interface Sci. 179 (1), 298–310.CrossRefGoogle Scholar
Dasari, T., Wu, Y., Liu, Y. & Hong, J. 2019 Near-wake behaviour of a utility-scale wind turbine. J. Fluid Mech. 859, 204–246.CrossRefGoogle Scholar
Dunnavan, E.L., Jiang, Z., Harrington, J.Y., Verlinde, J., Fitch, K. & Garrett, T.J. 2019 The shape and density evolution of snow aggregates. J. Atmos. Sci. 76 (12), 3919–3940.CrossRefGoogle Scholar
Durán, O., Claudin, P. & Andreotti, B. 2011 On aeolian transport: grain-scale interactions, dynamical mechanisms and scaling laws. Aeolian Res. 3 (3), 243–270.CrossRefGoogle Scholar
Falkinhoff, F., Obligado, M., Bourgoin, M. & Mininni, P.D. 2020 Preferential concentration of free-falling heavy particles in turbulence. Phys. Rev. Lett. 125 (6), 064504.CrossRefGoogle ScholarPubMed
Ferrante, A. & Elghobashi, S. 2003 On the physical mechanisms of two-way coupling in particle-laden isotropic turbulence. Phys. Fluids 15 (2), 315–329.CrossRefGoogle Scholar
Garrett, T.J., Yuter, S.E., Fallgatter, C., Shkurko, K., Rhodes, S.R. & Endries, J.L. 2015 Orientations and aspect ratios of falling snow. Geophys. Res. Lett. 42 (11), 4617–4622.CrossRefGoogle Scholar
Good, G.H., Ireland, P.J., Bewley, G.P., Bodenschatz, E., Collins, L.R. & Warhaft, Z. 2014 Settling regimes of inertial particles in isotropic turbulence. J. Fluid Mech. 759, R3.CrossRefGoogle Scholar
Heisel, M., Dasari, T., Liu, Y., Hong, J., Coletti, F. & Guala, M. 2018 The spatial structure of the logarithmic region in very-high-Reynolds-number rough wall turbulent boundary layers. J. Fluid Mech. 857, 704–747.CrossRefGoogle Scholar
Heymsfield, A.J. & Westbrook, C.D. 2010 Advances in the estimation of ice particle fall speeds using laboratory and field measurements. J. Atmos. Sci. 67 (8), 2469–2482.CrossRefGoogle Scholar
Högström, U., Hunt, J.C.R. & Smedman, A.S. 2002 Theory and measurements for turbulence spectra and variances in the atmospheric neutral surface layer. Boundary-Layer Meteorol. 103 (1), 101–124.CrossRefGoogle Scholar
Hong, J., Toloui, M., Chamorro, L.P., Guala, M., Howard, K., Riley, S., Tucker, J. & Sotiropoulos, F. 2014 Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine. Nat. Commun. 5, 4216.CrossRefGoogle ScholarPubMed
Ireland, P.J., Bragg, A.D. & Collins, L.R. 2016 The effect of Reynolds number on inertial particle dynamics in isotropic turbulence. Part 1. Simulations without gravitational effects. J. Fluid Mech. 796, 617–658.CrossRefGoogle Scholar
Kalt, P.A., Birzer, C.H. & Nathan, G.J. 2007 Corrections to facilitate planar imaging of particle concentration in particle-laden flows using Mie scattering, Part 1: collimated laser sheets. Appl. Opt. 46 (23), 5823–5834.CrossRefGoogle ScholarPubMed
Li, C., Lim, K., Berk, T., Abraham, A., Heisel, M., Guala, M., Coletti, F. & Hong, J. 2021 Settling and clustering of snow particles in atmospheric turbulence. J. Fluid Mech. 912, A49.CrossRefGoogle Scholar
Mallery, K., Shao, S. & Hong, J. 2020 Dense particle tracking using a learned predictive model. Exp. Fluids 61 (10), 223.CrossRefGoogle Scholar
Maxey, M.R. 1987 The gravitational settling of aerosol particles in homogeneous turbulence and random flow fields. J. Fluid Mech. 174, 441–465.CrossRefGoogle Scholar
Maxey, M.R. & Riley, J.J. 1983 Equation of motion for a small rigid sphere in a nonuniform flow. Phys. Fluids 26 (4), 883–889.CrossRefGoogle Scholar
Mordant, N., Crawford, A.M. & Bodenschatz, E. 2004 Experimental Lagrangian acceleration probability density function measurement. Physica D 193 (1–4), 245–251.CrossRefGoogle Scholar
Nemes, A., Dasari, T., Hong, J., Guala, M. & Coletti, F. 2017 Snowflakes in the atmospheric surface layer: observation of particle–turbulence dynamics. J. Fluid Mech. 814, 592–613.CrossRefGoogle Scholar
Nielsen, P. 1993 Turbulence effects on the settling of suspended particles. J. Sedim. Res. 63 (5), 835–838.Google Scholar
Ouellette, N.T., Xu, H. & Bodenschatz, E. 2006 A quantitative study of three-dimensional Lagrangian particle tracking algorithms. Exp. Fluids 40 (2), 301–313.CrossRefGoogle Scholar
Petersen, A.J., Baker, L. & Coletti, F. 2019 Experimental study of inertial particles clustering and settling in homogeneous turbulence. J. Fluid Mech. 864, 925–970.CrossRefGoogle Scholar
Raffel, M., Willert, C.E., Scarano, F., Kähler, C.J., Wereley, S.T. & Kompenhans, J. 2018 Particle Image Velocimetry: A Practical Guide. Springer.CrossRefGoogle Scholar
Rosa, B., Parishani, H., Ayala, O. & Wang, L.P. 2016 Settling velocity of small inertial particles in homogeneous isotropic turbulence from high-resolution DNS. Intl J. Multiphase Flow 83, 217–231.CrossRefGoogle Scholar
Saddoughi, S.G. & Veeravalli, S.V. 1994 Local isotropy in turbulent boundary layers at high Reynolds number. J. Fluid Mech. 268, 333–372.CrossRefGoogle Scholar
Shaw, R.A. 2003 Particle-turbulence interactions in atmospheric clouds. Annu. Rev. Fluid Mech. 35 (1), 183–227.CrossRefGoogle Scholar
Stull, R.B. 1988 An Introduction to Boundary Layer Meteorology. Kluwer Academic Publishers.CrossRefGoogle Scholar
Toloui, M., Riley, S., Hong, J., Howard, K., Chamorro, L.P., Guala, M. & Tucker, J. 2014 Measurement of atmospheric boundary layer based on super-large-scale particle image velocimetry using natural snowfall. Exp. Fluids 55 (5), 1737.CrossRefGoogle Scholar
Tooby, P.F., Wick, G.L. & Isaacs, J.D. 1977 The motion of a small sphere in a rotating velocity field: a possible mechanism for suspending particles in turbulence. J. Geophys. Res. 82 (15), 2096–2100.CrossRefGoogle Scholar
Tropea, C., Yarin, A.L. & Foss, J.F. 2007 Springer Handbook of Experimental Fluid Mechanics. Springer.CrossRefGoogle Scholar
Vaillancourt, P.A. & Yau, M.K. 2000 Review of particle-turbulence interactions and consequences for cloud physics. Bull. Am. Meteorol. Soc. 81 (2), 285–298.2.3.CO;2>CrossRefGoogle Scholar
Wang, L.P. & Maxey, M.R. 1993 Settling velocity and concentration distribution of heavy particles in homogeneous isotropic turbulence. J. Fluid Mech. 256, 27–68.CrossRefGoogle Scholar
Westbrook, C.D. & Sephton, E.K. 2017 Using 3-D-printed analogues to investigate the fall speeds and orientations of complex ice particles. Geophys. Res. Lett. 44 (15), 7994–8001.CrossRefGoogle Scholar
Yang, C.Y. & Lei, U. 1998 The role of the turbulent scales in the settling velocity of heavy particles in homogeneous isotropic turbulence. J. Fluid Mech. 371, 179–205.CrossRefGoogle Scholar
Zeugin, T., Krol, Q., Fouxon, I. & Holzner, M. 2020 Sedimentation of snow particles in still air in stokes regime. Geophys. Res. Lett. 47 (15), e2020GL087832.CrossRefGoogle Scholar
Zhou, J., Adrian, R.J., Balachandar, S. & Kendall, T.M. 1999 Mechanisms for generating coherent packets of hairpin vortices in channel flow. J. Fluid Mech. 387, 353–396.CrossRefGoogle Scholar

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