PIV analysis on the shelter effect of a bank of real fir trees

Lee, Jin Pyung; Lee, Sang Joon

doi:10.1016/j.jweia.2012.07.003

Cited by 23 publications

(13 citation statements)

References 20 publications

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“…These include blocks of foam rubber (Rodrigo et al, 2007), Lego™ bricks, Meccano™ wheels (Stacey et al, 1994), wooden pegs, wire mesh (Aubrun and Leitl, 2004), miniature fir trees (Lee and Lee, 2012), bottle brushes (Liang et al, 2005), 3D printed fractal models (Bai et al, 2012), automotive bulbs (Bohm et al, 2013) and architectural model trees (Meroney, 1968;Endalew et al, 2009b;Ruck et al, 2012). Each of these materials have their own merits and allow various aspects of canopy flows to be investigated faster, cheaper and in greater detail than a full-scale experimental campaign.…”

Section: Model Treesmentioning

confidence: 99%

“…In the case of Liang et al (2005), the shadow of an individual brush was examined as a proxy for the vertical structure of the tree canopy. In Bai et al (2012), the actual geometry file used for the 3D printing was utilised whilst in Endalew et al (2009b) and Lee and Lee (2012), photographic techniques were used to capture the required canopy structural data.…”

Section: Model Treesmentioning

confidence: 99%

“…Also, as discussed in Bohm et al (2013), the use of scale models of vegetation in wind tunnels may result in the flow being dominated by viscous drag which will not be representative of full-scale flows. However, the use of non-bluff bodies to represent forest canopies in wind tunnels is not without precedent (Meroney, 1968;Liang et al, 2005;Endalew et al, 2009b;Lee and Lee, 2012;Ruck et al, 2012). These limitations aside and given that the focus of this study is the role that detailed canopy morphology can play in improving simulations, these model trees were deemed to be the best candidate for experimentation.…”

Section: Model Treesmentioning

confidence: 99%

“…In a recent experimental campaign presented in Lee and Lee (2012), the flow around a bank of three fir trees of H c =150 mm was investigated in a wind tunnel study using stereo-PIV. Although the presented blockage was far below the relevant canopy adjustment length, the effect of the wake on the velocity profile was found to persist until 10H C in the lee of the blockage.…”

Section: Re-equilibrium Zonementioning

confidence: 99%

“…In Dupont et al (2012), a number of LES simulations were conducted based on forested site data and in Lee and Lee (2012), the flow around a bank of real fir trees was investigated by use of Stereoscopic Particle Image Velocimetry (stereo-PIV) in a wind tunnel. Again, both Dupont et al (2012) and Lee and Lee (2012) concluded that an understanding of the actual morphology is vital when modelling canopy flows.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A study on the inclusion of forest canopy morphology data in numerical simulations for the purpose of wind resource assessment

Desmond

Watson

Aubrun

et al. 2014

Journal of Wind Engineering and Industrial Aerodynamics

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A series of numerical simulations of the flow over a forest stand have been conducted using two different turbulence closure models along with various levels of canopy morphology data. Simulations have been validated against Stereoscopic Particle Image Velocimetry measurements from a wind tunnel study using one hundred architectural model trees, the porosities of which have been assessed using a photographic technique.It has been found that an accurate assessment of the porosity of the canopy, and specifically the variability with height, improves simulation quality regardless of the turbulence closure model used or the level of canopy geometry included. The observed flow field and recovery of the wake is in line with characteristic canopy flows published in the literature and it was found that the shear stress transport turbulence model was best able to capture this detail numerically.

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Section: Model Treesmentioning

confidence: 99%

Section: Model Treesmentioning

confidence: 99%

Section: Model Treesmentioning

confidence: 99%

Section: Re-equilibrium Zonementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A study on the inclusion of forest canopy morphology data in numerical simulations for the purpose of wind resource assessment

Desmond

Watson

Aubrun

et al. 2014

Journal of Wind Engineering and Industrial Aerodynamics

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Modeling complex flow structures and drag around a submerged plant of varied posture

Boothroyd

Hardy

Warburton

et al. 2017

Water Resources Research

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Although vegetation is present in many rivers, the bulk of past work concerned with modeling the influence of vegetation on flow has considered vegetation to be morphologically simple and has generally neglected the complexity of natural plants. Here we report on a combined flume and numerical model experiment which incorporates time‐averaged plant posture, collected through terrestrial laser scanning, into a computational fluid dynamics model to predict flow around a submerged riparian plant. For three depth‐limited flow conditions (Reynolds number = 65,000–110,000), plant dynamics were recorded through high‐definition video imagery, and the numerical model was validated against flow velocities collected with an acoustic Doppler velocimeter. The plant morphology shows an 18% reduction in plant height and a 14% increase in plant length, compressing and reducing the volumetric canopy morphology as the Reynolds number increases. Plant shear layer turbulence is dominated by Kelvin‐Helmholtz type vortices generated through shear instability, the frequency of which is estimated to be between 0.20 and 0.30 Hz, increasing with Reynolds number. These results demonstrate the significant effect that the complex morphology of natural plants has on in‐stream drag, and allow a physically determined, species‐dependent drag coefficient to be calculated. Given the importance of vegetation in river corridor management, the approach developed here demonstrates the necessity to account for plant motion when calculating vegetative resistance.

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