Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-26T19:59:49.710Z Has data issue: false hasContentIssue false
  • English
  • Français

Modelling waving crops using large-eddy simulation: comparison with experiments and a linear stability analysis

Published online by Cambridge University Press:  15 April 2010

S. DUPONT ,
F. GOSSELIN ,
C. PY ,
E. DE LANGRE ,
P. HEMON  and
Y. BRUNET
S. DUPONT*
Affiliation:
INRA, UR1263 EPHYSE, 71 avenue Edouard Bourlaux, F-33140 Villenave d'Ornon, France
F. GOSSELIN
Affiliation:
Département de Mécanique, LadHyX, CNRS-Ecole Polytechnique, F-91128 Palaiseau, France
C. PY
Affiliation:
MSC, UMR 7057 CNRS-Université Paris-Diderot, F-75205 Paris cedex 13, France
E. DE LANGRE
Affiliation:
Département de Mécanique, LadHyX, CNRS-Ecole Polytechnique, F-91128 Palaiseau, France
P. HEMON
Affiliation:
Département de Mécanique, LadHyX, CNRS-Ecole Polytechnique, F-91128 Palaiseau, France
Y. BRUNET
Affiliation:
INRA, UR1263 EPHYSE, 71 avenue Edouard Bourlaux, F-33140 Villenave d'Ornon, France
*
†Email address for correspondence: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

In order to investigate the possibility of modelling plant motion at the landscape scale, an equation for crop plant motion, forced by an instantaneous velocity field, is introduced in a large-eddy simulation (LES) airflow model, previously validated over homogeneous and heterogeneous canopies. The canopy is simply represented as a poroelastic continuous medium, which is similar in its discrete form to an infinite row of identical oscillating stems. Only one linear mode of plant vibration is considered. Two-way coupling between plant motion and the wind flow is insured through the drag force term. The coupled model is validated on the basis of a comparison with measured movements of an alfalfa crop canopy. It is also compared with the outputs of a linear stability analysis. The model is shown to reproduce the well-known phenomenon of ‘honami’ which is typical of wave-like crop motions on windy days. The wavelength of the main coherent waving patches, extracted using a bi-orthogonal decomposition (BOD) of the crop velocity fields, is in agreement with that deduced from video recordings. The main spatial and temporal characteristics of these waving patches exhibit the same variation with mean wind velocity as that observed with the measurements. However they differ from the coherent eddy structures of the wind flow at canopy top, so that coherent waving patches cannot be seen as direct signatures of coherent eddy structures. Finally, it is shown that the impact of crop motion on the wind dynamics is negligible for current wind speed values. No lock-in mechanism of coherent eddy structures on plant motion is observed, in contradiction with the linear stability analysis. This discrepancy may be attributed to the presence of a nonlinear saturation mechanism in LES.

Type
Papers
Information
Journal of Fluid Mechanics , Volume 652 , 10 June 2010 , pp. 5 - 44
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Adrian, R. J., Meinhart, C. D. & Tomkins, C. D. 2000 Vortex organization in the outer region of the turbulent boundary layer. J. Fluid Mech. 422, 1–54.CrossRefGoogle Scholar
Amiro, B. D. 1990 Drag coefficients and turbulence spectra within 3 boreal forest canopies. Bound.-Layer Meteorol. 52 (3), 227–246.Google Scholar
Ancelin, P., Courbaud, B. & Fourcaud, T. Y. 2004 Development of an individual tree-based mechanical model to predict wind damage within forest stands. For. Ecol. Manag. 203 (1–3), 101–121.Google Scholar
Aubry, N., Guyonnet, R. & Lima, R. 1991 Spatiotemporal analysis of complex signals: theory and applications. J. Stat. Phys. 64 (3–4), 683–739.Google Scholar
Carlotti, P. 2002 Two-point properties of atmospheric turbulence very close to the ground: comparison of a high resolution les with theoretical models. Bound.-Layer Meteorol. 104 (3), 381–410.Google Scholar
Cassiani, M., Katul, G. G. & Albertson, J. D. 2008 The effects of canopy leaf area index on airflow across forest edges: large-eddy simulation and analytical results. Bound.-Layer Meteorol. 126 (3), 433–460.Google Scholar
Chow, F. K., Weigel, A. P., Street, R. L., Rotach, M. W. & Xue, M. 2006 High resolution large-eddy simulations of flow in a steep alpine valey. Part I. Meteorology, verification and sensitivity experiments. J. Appl. Meteorol. Climatol. 45, 63–86.Google Scholar
Deardorff, J. W. 1980 Stratocumulus-capped mixed layers derived from a 3-dimensional model. Bound.-Layer Meteorol. 18 (4), 495–527.Google Scholar
Doaré, O., Moulia, B. & de Langre, E. 2004 Effect of plant interaction on wind-induced crop motion. Trans. ASME: J. Biomech. Engng 126 (2), 146–151.Google ScholarPubMed
Drobinski, P., Carlotti, P., Newson, R. K., Banta, R. M., Foster, R. C. & Redelsperger, J. L. 2004 The structure of the near-neutral atmospheric surface layer. J. Atmos. Sci. 61 (6), 699–714.Google Scholar
Drobinski, P., Carlotti, P., Redelsberger, J.-L., Banta, R. M., Masson, V. & Newsom, R. K. 2007 Numerical and experimental investigation of the neutral atmospheric surface layer. J. Atmos. Sci. 64, 137–156.CrossRefGoogle Scholar
Dupont, S. & Brunet, Y. 2006 Simulation of turbulent flow in an urban forested park damaged by a windstorm. Bound.-Layer Meteorol. 120 (1), 133–161.CrossRefGoogle Scholar
Dupont, S. & Brunet, Y. 2008 a Edge flow and canopy structure: a large-eddy simulation study. Bound.-Layer Meteorol. 126, 51–71.Google Scholar
Dupont, S. & Brunet, Y. 2008 b Impact of forest edge shape on tree stability: A large-eddy simulation study. Forestry 81, 299–315.Google Scholar
Dupont, S. & Brunet, Y. 2008 c Influence of foliar density profile on canopy flow: a large-eddy simulation study. Agric. For. Meteorol. 148, 976–990.Google Scholar
Dupont, S. & Brunet, Y. 2009 Coherent structures in canopy edge flow: a large-eddy simulation study. J. Fluid Mech. 630, 93–128.Google Scholar
Dupont, S., Brunet, Y. & Finnigan, J. J. 2008 Large-eddy simulation of turbulent flow over a forested hill: validation and coherent structure identification. Q. J. R. Meteorol. Soc. 134, 1911–1929.CrossRefGoogle Scholar
Dwyer, M. J., Patton, E. G. & Shaw, R. H. 1997 Turbulent kinetic energy budgets from a large-eddy simulation of airflow above and within a forest canopy. Bound.-Layer Meteorol. 84 (1), 23–43.CrossRefGoogle Scholar
Farge, M., Schneider, K., Pellegrino, G., Wray, A. A. & Rogallo, R. S. 2003 Coherent vortex extraction in three-dimensional homogeneous turbulence: Comparison between cvs-wavelet and pod-Fourier decompositions. Phys. Fluids 15 (10), 2886–2896.CrossRefGoogle Scholar
Farquhar, T., Wood, J. Z. & van Beem, J. 2000 The kinematics of wheat struck by a wind gust. J. Appl. Mech. 67, 496–502.Google Scholar
Fesquet, C., Dupont, S., Drobinski, P, Dubos, T. & Barthlott, C. 2009 Impact of terrain heterogeneity on coherent structure properties: numerical approach. Bound.-Layer Meteorol. 133, 71–92.CrossRefGoogle Scholar
Finnigan, J. 2000 Turbulence in plant canopies. Annu. Rev. Fluid Mech. 32, 519–571.Google Scholar
Finnigan, J. J. 1979 Turbulence in waving wheat. Part 1. Mean statistics and honami. Bound.-Layer Meteorol. 16 (2), 181–211.Google Scholar
Finnigan, J. J. & Mulhearn, P. J. 1978 a Modelling waving crops in a wind tunnel. Bound.-Layer Meteorol. 14, 253–277.Google Scholar
Finnigan, J. J. & Mulhearn, P. J. 1978 b A simple mathematical model of airflow in waving plant canopies. Bound.-Layer Meteorol. 14, 415–431.Google Scholar
Flesch, T. K. & Grant, R. H. 1991 The translation of turbulent wind energy to individual corn plant motion during senescense. Bound.-Layer Meteorol. 55 (1–2), 161–176.Google Scholar
Flesch, T. K. & Grant, R. H. 1992 Corn motion in the wind during senescence. Part 2. Effect of dynamic-plant characteristics. Agronomy J. 84 (4), 748–751.Google Scholar
Flesch, T. K. & Wilson, J. D. 1999 Wind and remnant tree sway in forest cutblocks. ii. relating measured tree sway to wind statistics. Agric. For. Meteorol. 93 (4), 243–258.Google Scholar
Foster, R. C., Vianey, F., Drobinski, P & Carlotti, P. 2006 Near-surface coherent structures and the vertical momentum flux in a large-eddy simulation of the neutrally-stratified boundary layer. Bound.-Layer Meteorol. 120, 229–255.CrossRefGoogle Scholar
Foudhil, H., Brunet, Y. & Caltagirone, J. 2005 A fine-scale k-epsilon model for atmospheric flow over heterogeneous landscapes. Environ. Fluid Mech. 5 (3), 247–265.CrossRefGoogle Scholar
Gardiner, B. A. 1995 The Interactions of Wind and Tree Movement in Forest Canopies. Cambridge University Press, p. 485.Google Scholar
Gardiner, B., Peltola, H. & Kellomaki, S. 2000 Comparison of two models for predicting the critical wind speeds required to damage coniferous trees. Ecol. Model. 129 (1), 1–23.Google Scholar
Ghisalberti, M. & Nepf, H. 2006 The structure of the shear layer in flows over rigid and flexible canopies. Environ. Fluid Mech. 6 (3), 277–301.Google Scholar
Gosselin, F. & de Langre, E. 2009 Destabilising effects of plant flexibility in air and aquatic vegetation canopy flows. Eur. J. Mech. B-Fluids 28, 271–282.Google Scholar
Green, S. R. 1992 Modelling turbulence air flow in a stand of widely-spaced trees. PHOENICS, J. Comput. Fluid Dyn. 5, 294–312.Google Scholar
Hémon, P. & Santi, F. 2003 Applications of biorthogonal decompositions in fluid-structure interactions. J. Fluids Struct. 17 (8), 1123–1143.CrossRefGoogle Scholar
Hommema, S. E. & Adrian, R. J. 2003 Packet structure of surface eddies in the atmospheric boundary layer. Bound.-Layer Meteorol. 106 (1), 147–170.Google Scholar
Hunt, J. C. R. & Carlotti, P. 2001 Statistical structure at the wall of the high reynolds number turbulent boundary layer. Flow Turbul. Combust. 66 (4), 453–475.CrossRefGoogle Scholar
Hunt, J. C. R. & Morrison, J. F. 2000 Eddy structure in turbulent boundary layers. Eur. J. Mech. B-Fluids 19, 673–694.Google Scholar
Hutchins, N. & Marusic, I. 2007 Evidence of very long meandering features in the logarithmic region of turbulent boundary layers. J. Fluid Mech. 579, 1–28.CrossRefGoogle Scholar
Ikeda, S., Yamada, T. & Toda, Y. 2001 Numerical study on turbulent flow and honami in and above flexible plant canopy. Intl J. Heat Fluid Flow 22 (3), 252–258.Google Scholar
Inoue, R. 1955 Studies of the phenomena of waving plant (‘honami’) caused by wind. part 1: Mechanism and characteristics of waving plant phenomena. J. Agric. Meteorol. (Japan) 11, 71–82.Google Scholar
Jaffe, M. 1973 Thigmomorphogenesis: the response of plant growth and development to mechanical dioica. Planta 114, 143–157.Google Scholar
James, K. R., Haritos, N. & Ades, P. K. 2006 Mechanical stability of trees under dynamic loads. Am. J. Bot. 93 (10), 1522–1530.Google Scholar
Kaimal, J. C. & Finnigan, J. J. 1994 Atmospheric Boundary Layer Flows: Their Structure and Measurements. Oxford University Press, p. 289.Google Scholar
Kanda, M. & Hino, M. 1994 Organized structures in developing turbulent-flow within and above a plant canopy using a large-eddy simulation. Bound.-Layer Meteorol. 68 (3), 237–257.CrossRefGoogle Scholar
Kerzenmacher, T. & Gardiner, B. A. 1998 A mathematical model to describe the dynamic response of a spurce tree to the wind. Trees 12, 385–394.CrossRefGoogle Scholar
Kim, K. C. & Adrian, R. J. 1999 Very large-scale motion in the outer layer. Phys. Fluids 11 (2), 417–422.Google Scholar
Kravchenko, A. G., Moin, P. & Moser, R. 1996 Zonal embedded grids for numerical simulations of wall-bounded turbulent flows. J. Comput. Phys. 127 (2), 412–423.CrossRefGoogle Scholar
de Langre, E. 2008 Effects of wind on plant. Annu. Rev. Fluid Mech. 40, 141–168.Google Scholar
Li, Z. & Lin, J. D. 1990 Air flow over and through a forest edge: a steady-state numerical simulation. Bound.-Layer Meteorol. 51, 179–197.CrossRefGoogle Scholar
Lin, C. L., Moeng, C. H., Sullivan, P. P. & McWilliams, J. C. 1997 The effect of surface roughness on flow structures in a neutrally stratified planetary boundary layer flow. Phys. Fluids 9 (11), 3235–3249.CrossRefGoogle Scholar
Liu, J., Chen, J. M., Black, T. A. & Novak, M. D. 1996 E-epsilon modelling of turbulent air flow downwind of a model forest edge. Bound.-Layer Meteorol. 77 (1), 21–44.Google Scholar
Mahrer, Y. 1984 An improved numerical approximation of the horizontal gradients in a terrain-following coordinate system. Mon. Weather Rev. 112, 918–922.2.0.CO;2>CrossRefGoogle Scholar
Mayer, H. 1987 Wind-induced tree sways. Trees 1, 195–206.CrossRefGoogle Scholar
Moeng, C. H. 1984 A large-eddy-simulation model for the study of planetary boundary-layer turbulence. J. Atmos. Sci. 41 (13), 2052–2062.2.0.CO;2>CrossRefGoogle Scholar
Moeng, C.-H. & Sullivan, P. P. 1994 A comparison of shear-driven and buoyancy-driven planetary boundary-layer flows. J. Atmos. Sci. 51 (7), 999–1022.2.0.CO;2>CrossRefGoogle Scholar
Moulia, B. & Combes, D. 2004 Thigmomorphogenesis acclimation of plant to moderate winds greatly affects height structure in field-grown alfalfa (medicago sativa l.), an indeterminate herb. Comput. Biochem. Physiol. A: Molec. Integrative Physiol. 137 (3-S1), S77, A10.2.Google Scholar
Peltola, H. 1996 Swaying of trees in response to wind and thinning in a stand of scots pine. Bound.-Layer Meteorol. 77 (3–4), 285–304.Google Scholar
Peltola, H., Kellomaki, S., Vaisanen, H. & Ikonen, V. P. 1999 A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine, Norway spruce, and birch. Can. J. For. Res.-Rev. Can. Rech. For. 29 (6), 647–661.CrossRefGoogle Scholar
Pénelon, T., Calmet, I. & Mironov, D. V. 2001 Micrometeorological simulations over a complex terrain with submeso: a model study using a novel pre-processor. Intl J. Environ. Pollut. 16 (1–6), 583–602.Google Scholar
Py, C., de Langre, E. & Moulia, B. 2004 The mixing layer instability of wind over a flexible crop canopy. C. R. Méc. 332 (8), 613–618.Google Scholar
Py, C., de Langre, E. & Moulia, B. 2006 A frequency lock-in mechanism in the interaction between wind and crop canopies. J. Fluid Mech. 568, 425–449.Google Scholar
Py, C., de Langre, E., Moulia, B. & Hemon, P. 2005 Measurement of wind-induced motion of crop canopies from digital video images. Agric. For. Meteorol. 130 (3–4), 223–236.Google Scholar
Raupach, M. R., Finnigan, J. J. & Brunet, Y. 1996 Coherent eddies and turbulence in vegetation canopies: the mixing-layer analogy. Bound.-Layer Meteorol. 78 (3–4), 351–382.Google Scholar
Rodriguez, M., de Langre, E. & Moulia, B. 2008 A scaling law for the effects of architecture and allometry on tree vibration modes suggests a biological tuning to modal compartmentalization. Am. J. Bot. 95 (12), 1523–1537.Google Scholar
Ross, A. N. 2008 Large-eddy simulations of flow over forested ridges. Bound.-Layer Meteorol. 128, 59–76.Google Scholar
Russell, G., Marshall, B. & Jarvis, P. G. 1990 Plant Canopies: Their Growth, Form and Function. Cambridge University Press, p. 192.Google Scholar
Sellier, D., Brunet, Y. & Fourcaud, T. 2008 A numerical model of tree aerodynamic response to a turbulent airflow. Forestry 81 (3), 279–297.Google Scholar
Sellier, D., Fourcaud, T. & Lac, P. 2006 A finite element model for investigating effects of aerial architecture on tree oscillations. Tree Physiol. 26 (6), 799–806.Google Scholar
Shaw, R. H., Brunet, Y., Finnigan, J. J. & Raupach, M. R. 1995 A wind tunnel study of air flow in waving wheat: two-point velocity statistics. Bound.-Layer Meteorol. 76 (4), 349–376.Google Scholar
Shaw, R. H. & Schumann, U. 1992 Large-eddy simulation of turbulent-flow above and within a forest. Bound.-Layer Meteorol. 61 (1–2), 47–64.CrossRefGoogle Scholar
Shen, S. H. & Leclerc, M. Y. 1997 Modelling the turbulence structure in the canopy layer. Agric. For. Meteorol. 87 (1), 3–25.Google Scholar
Su, H. B., Shaw, R. H. & PawU, K. T. U, K. T. 2000 Two-point correlation analysis of neutrally stratified flow within and above a forest from large-eddy simulation. Bound.-Layer Meteorol. 94 (3), 423–460.Google Scholar
Su, H.-B., Shaw, R. H., PawU, K. T. U, K. T., Moeng, C.-H. & Sullivan, P. P. 1998 Turbulent statistics of neutrally stratified flow within and above a sparse forest from large-eddy simulation and field observations. Bound.-Layer Meteorol. 88, 363–397.Google Scholar
Watanabe, T. 2004 Large-eddy simulation of coherent turbulence structures associated with scalar ramps over plant canopies. Bound.-Layer Meteorol. 112 (2), 307–341.Google Scholar
Weigel, A. P., Chow, F. K. & Rotach, M. W. 2007 On the nature of turbulent kinetic energy in a steep and narrow alpine valley. Bound.-Layer Meteorol. 123 (1), 177–199.Google Scholar
Weigel, A. P., Chow, F. K., Rotach, M. W., Street, R. L. & Xue, M. 2006 High-resolution large-eddy simulations of flow in a steep alpine valley. Part II. Flow structure and heat budgets. J. Appl. Meteorol. Climatol. 45 (1), 87–107.Google Scholar
Xue, M., Droegemeier, K. K. & Wong, V. 2000 The advanced regional prediction system (arps) – a multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I. Model dynamics and verification. Meteorol. Atmos. Phys. 75 (3–4), 161–193.CrossRefGoogle Scholar
Xue, M., Droegemeier, K. K., Wong, V., Shapiro, A. & Brewster, K. 1995 ARPS version 4.0 User's Guide. Center for Analysis and Prediction of Storms, p. 380.Google Scholar
Xue, M., Droegemeier, K. K., Wong, V., Shapiro, A., Brewster, K., Carr, F., Weber, D., Liu, Y. & Wang, D. 2001 The advanced regional prediction system (arps) – a multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part II. Model physics and applications. Meteorol. Atmos. Phys. 76 (3–4), 143–165.CrossRefGoogle Scholar
Yang, B., Morse, A. P., Shaw, R. H. & PawU, K. T. U, K. T. 2006 a Large-eddy simulation of turbulent flow across a forest edge. Part II. Momentum and turbulent kinetic energy budgets. Bound.-Layer Meteorol. 121 (3), 433–457.CrossRefGoogle Scholar
Yang, B., Raupach, M. R., Shaw, R. H., Tha, K., Paw, U. & Morse, A. P. 2006 b Large-eddy simulation of turbulent flow across a forest edge. Part I. Flow statistics. Bound.-Layer Meteorol. 120 (3), 377–412.CrossRefGoogle Scholar