Advertisement

On the Use of Surface PIV for the Characterization of Wake Area in Flows Through Emergent Vegetation

  • J. Leonardo Corredor-GarciaEmail author
  • Alexandre Delalande
  • Virginia Stovin
  • Ian Guymer
Conference paper
  • 51 Downloads
Part of the GeoPlanet: Earth and Planetary Sciences book series (GEPS)

Abstract

New results from surface PIV (Particle Image Velocimetry) measurements are presented. Surface PIV can potentially provide researchers with a cheap and versatile method for mapping 2D flow fields. This technique was evaluated in a laboratory flume with a random distribution of rigid plastic straws, to simulate flows through emergent vegetation. Velocities were computed via an open-source tool for conventional PIV, and a sensitivity analysis conducted, in which the factors seeding particle size, particle image density, size of interrogation window, number of passes and contrast were evaluated. Results show that, with the appropriate settings, 98.7\(\%\) of data points were considered to be reliable. It was found that the best quality velocity maps were obtained with small seeding particles and intermediate window resolutions (16\(\,\times \,\)16 pixels). The practical use of this technique is illustrated by using the data to identify the portion of flow through vegetation occupied by wakes. For this, a straightforward criterion, related to the incident flow conditions and generated vorticity, is proposed. Further refinements of this research can lead to applications in several branches of fluid mechanics, such as in situ measurements of the flow field and analysis of scalar dispersion processes in ecohydraulics.

Keywords

Surface PIV Vegetated flow Vorticity Wake area Ecohydraulics PIV Large scale PIV 

References

  1. Dobson DW, Holland KT, Calantoni J (2014) Fast, large-scale, particle image velocimetry-based estimations of river surface velocity. Comput Geosci 70:35–43ADSCrossRefGoogle Scholar
  2. Fujita I, Muste M, Kruger A (1998) Large-scale particle image velocimetry for flow analysis in hydraulic engineering applications. J Hydraul Res 36(3):397–414CrossRefGoogle Scholar
  3. Gharahjeh S, Aydin I (2016) Application of video imagery techniques for low cost measurement of water surface velocity in open channels. Flow Meas Intrum 51:79–994CrossRefGoogle Scholar
  4. Higham J (2017) The application of modal decomposition techniques for the analysis of environmental flows. Ph.D. thesis, University of SheffieldGoogle Scholar
  5. Higham JE, Brevis W, Keylock CJ (2016) A rapid non-iterative proper orthogonal decomposition based outlier detection and correction for PIV data. Meas Sci Technol 27:1–16CrossRefGoogle Scholar
  6. Jadhav R, Buchberger S (1995) Effects of vegetation on flow through free water surface wetlands. Ecol Eng 4:481–496CrossRefGoogle Scholar
  7. Lohrmann A, Cabrera R, Kraus NC (1994) Acoustic doppler velocimeter (adv) for laboratory use. In: Pugh CA (ed) Proceedings of symposium on fundamentals and advancements in hydraulic measurements and experimentation. ASCE, pp 351–365Google Scholar
  8. Muste M, Hauet A, Fujita I, Legout C, Ho H-C (2014) Capabilities of large-scale particle image velocimetry to characterize shallow free-surface flows. Adv Water Resour 70:160–171ADSCrossRefGoogle Scholar
  9. Nepf H (1999) Drag, turbulence and diffusion in flow through emergent vegetation. Water Resour Res 35(2):479–489ADSCrossRefGoogle Scholar
  10. Nepf H (2012) Flow and transport in regions with aquatic vegetation. Annu Rev Fluid Mech 44:123–142ADSMathSciNetCrossRefGoogle Scholar
  11. Novak G, Rak G, Preseren T, Bajcar T (2017) Non-intrusive measurements of shallow water discharge. Flow Meas Intrum 56:14–17CrossRefGoogle Scholar
  12. Osorio-Cano JD, Osorio AF, Medina R (2013) A method for extracting surface flow velocities and discharge volumes from video images in laboratory. Flow Meas Intrum 33:188–196CrossRefGoogle Scholar
  13. Patalano A, Garcia CM, Rodriguez A (2017) Rectification of image velocity results (river): a simple and user-friendly toolbox for large scale water surface particle image velocimetry (piv) and particle tracking velocimetry (ptv). Comput Geosci 109:323–330ADSCrossRefGoogle Scholar
  14. Raffel M, Willert CE, Scarano F, Kahler CJ, Wereley ST, Kompenhans J (2018) Particle image velocimetry: a practical guide, 3rd edn. Springer, BerlinCrossRefGoogle Scholar
  15. Ricardo AM, Franca M, Ferreira RML (2016a) Turbulent flows within random arrays of rigid and emergent cylinders with varying distributions. J Hydraul Eng 142(9):1–6CrossRefGoogle Scholar
  16. Ricardo AM, Sanches P, Ferreira RML (2016b) Vortex shedding and vorticity fluxes in the wake of cylinders within a random array. J Turbulence 17(11):999–1014ADSCrossRefGoogle Scholar
  17. Sonnenwald F, Stovin VR, Guymer I (2018) A stem spacing-based non-dimensional model for predicting longitudinal dispersion in low-density emergent vegetation. Acta Geophys pp 1–18. https://doi.org/10.1007/s11600-018-0217-zADSCrossRefGoogle Scholar
  18. Stanislas M, Okamoto K, Kahler CJ, Westerweel J, Scarano F (2008) Main results of the third international PIV challenge. Exp Fluids 45:27–71CrossRefGoogle Scholar
  19. Sumner D (2010) Two circular cylinders in cross-flow: a review. J Fluid Struct 26:849–899CrossRefGoogle Scholar
  20. Thielicke W, Stamhuis EJ (2014) Pivlab - towards user-friendly, affordable and accurate digital particle image velocimetry in matlab. J Open Res Software 2(1). http://dx.doi.org/10.5334/jors.bl
  21. Wang S, Tian F, Jia L, Lu X, Yin X (2010) Secondary vortex street in the wake of two tandem circular cylinders in cross-flow. Physics Rev E 81:1–9Google Scholar
  22. White BL, Nepf HM (2003) Scalar transport in random cylinder arrays at moderate reynods number. J Fluid Mech 487:43–79ADSCrossRefGoogle Scholar
  23. Zhou Y, Mahbud MA (2016) Wake of two interacting cylinders: a review. J Heat Fluid Flow 62:510–537CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • J. Leonardo Corredor-Garcia
    • 1
    Email author
  • Alexandre Delalande
    • 2
  • Virginia Stovin
    • 1
  • Ian Guymer
    • 1
  1. 1.University of SheffieldSheffieldUK
  2. 2.INSA (Institut National des Sciences Appliquées) LyonLyonFrance

Personalised recommendations