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Experiments in Fluids

, 55:1736 | Cite as

Characterizing the lower log region of the atmospheric surface layer via large-scale particle tracking velocimetry

  • Giuseppe A. Rosi
  • Michael Sherry
  • Matthias Kinzel
  • David E. Rival
Research Article

Abstract

As a first step toward characterizing coherent structures within the atmospheric surface layer (ASL), measurements obtained via a large-scale particle tracking velocimetry (LS-PTV) system were validated against wind-measurement station data as well as canonical turbulent boundary layer studies. The LS-PTV system resolves three-dimensional, Lagrangian tracks over a 16 m3 volume. Mean-velocity measurements, as well as vertical and shear Reynolds-stress measurements, generally agreed with wind-measurement station data and Reynolds-stress profiles referenced from literature. The probability distributions for streamwise, spanwise and vertical velocity-fluctuation components appear normally distributed about zero. Furthermore, the probability distributions for all three components of Lagrangian acceleration were exponential and followed the parametrization curve from LaPorta et al. (Lett Nat 409:1017–1019, 2001). Lastly, the vorticity probability distributions were exponential and symmetric about zero, which matches findings from Balint et al. (Fluid Mech 228:53–86, 1991). The vorticity intensity measured by the LS-PTV system was less than values from Priyadarshana et al. (Fluid Mech 570:307–346, 2007), which is attributed to the low spatial resolution. However, the average spacing of 0.5 m between tracer particles is deemed sufficient for the future characterization of vortical structures within the ASL.

Keywords

Vorticity Coherent Structure Tracer Particle Atmospheric Surface Layer Tomographic Particle Image Velocimetry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors wish to thank Alberta Innovates Technology Futures for their financial backing. Thanks also go to Genivar Wind for their generous support in the development and operation of the wind mast. The authors also wish to thank Tyler Christensen and Mohamed Arif Mohamed for their assistance during data acquisition, and Dr. Masaki Hayashi for providing access to his eddy-covariance system.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Giuseppe A. Rosi
    • 1
  • Michael Sherry
    • 1
  • Matthias Kinzel
    • 2
  • David E. Rival
    • 1
  1. 1.Department of Mechanical EngineeringUniversity of CalgaryCalgaryCanada
  2. 2.Graduate Aerospace Laboratories of the California Institute of TechnologyPasadenaUSA

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