Turbulent flow over groups of urban-like obstacles O. Coceal 1, T.G. Thomas 2, I.P. Castro 2 and...
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Transcript of Turbulent flow over groups of urban-like obstacles O. Coceal 1, T.G. Thomas 2, I.P. Castro 2 and...
![Page 1: Turbulent flow over groups of urban-like obstacles O. Coceal 1, T.G. Thomas 2, I.P. Castro 2 and S.E. Belcher 1 1 Department of Meteorology, University.](https://reader035.fdocuments.us/reader035/viewer/2022062619/55160d55550346d46f8b609d/html5/thumbnails/1.jpg)
Turbulent flow over groups of urban-like obstacles
O. Coceal1, T.G. Thomas2, I.P. Castro2 and S.E. Belcher1
1Department of Meteorology, University of Reading, U.K.
2School of Engineering Sciences, University of Southampton, U.K.
1Email: [email protected]
www.met.rdg.ac.uk/bl_met
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Motivation and Aims
• Modelling flow and dispersion in urban areas
• Wider application, e.g. in engineering
Aims
• To perform high resolution simulations – no turbulence modelling, no tuning
• To validate simulations against a high quality dataset
• To compute 1-d momentum balance for canopy of cubical roughness, and compare with vegetation canopies
compare with rough walls in general
• To compare flow within canopy with that above & understand their coupling
• To investigate effect of layout of the obstacles
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Spatial averaging
'~ uuUu Uuu ~
uUuu ~'
spatial fluctuation from mean
turbulent wind speed
Compute from LES/DNS data
Dwuz
wuzx
P
Dt
DU
~~''1
Spatial average of Reynolds-averaged momentum equation
uU
''wu is spatial average of Reynolds stress
is dispersive stress
is distributed drag term
wu ~~
S i dSnp
VD
1
is spatially averaged mean wind speed
See e.g. Raupach & Shaw (1982), Finnigan (2000)
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Numerical method• Multiblock LES/DNS code developed by T.G. Thomas
• Resolutions:
DNS at 64 x 64 x 64 grid points per cube (256 x 256 x 256 grid points)
32 x 32 x 32 grid points per cube (128 x 128 x 128 grid points)
16 x 16 x 16 grid points per cube (64 x 64 x64 grid points)
•Boundary conditions:
free slip at top
no slip at bottom and cube surfaces
periodic in streamwise and lateral directions
• Reynolds number = 5000 (based on Utop and h)
• Flow driven by constant body force
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Domain set-up
Repeating unit
Staggered Aligned Square
Obstacle density 0.25
Domain sizes: 4h x 4h x 4h, 8h x 8h x 4h, 4h x 4h x 6h
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Grid resolution tests
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Domain size tests (I)
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Domain size tests (II)
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Unsteady flow viz - windvectors
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Unsteady flow viz - windvectors
Unsteady flow very different from mean flow
Streamwise vortex structures
Streamwise-vertical plane Lateral-vertical plane
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Unsteady flow viz - vorticity
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Unsteady flow viz - vorticity
Strong, continuous shear layer Interacting shear layers
Enhanced lateral mixing Decoupling of flow ?
Streamwise-vertical plane Horizontal plane
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Time-mean flow - windvectorsRobust recirculation upstream of cube
Staggered array
Square array
No recirculation bubble behind cube
Divergence point near ground
Steady vortex in canyon
More two-dimensional in nature
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Time-mean flow – pressure
Pressure on back face more uniform
Front face Back face
Side face Top face
Negative pressure on top face
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Pressure drag profile
Compared with data from Cheng and Castro (2003)
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Mean velocity profiles
Compared with data from Cheng and Castro (2003)
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Spatially-averaged stress budget
Dispersive stress negligible above canopycf Finnigan (1985) Cheng and Castro (2003)
Dispersive stress significant within canopy
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Spatially-averaged stress budget
Very large averaging times needed to average out effects of slow-evolving vortex structures (~ 400 T)
Characteristic timescale T = h / u*
50 T 400 T
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Stress budget – effect of layout
Dispersive stress changes sign for aligned/square arrays
Due to recirculation (cf Poggi et al., 2004)
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Reynolds and dispersive stresses
Dispersive stresses of order 1% of total stress above array
Stress measurements above array Cheng and Castro (2003)
Aligned array
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Mean velocity and drag profiles
Spatially-averaged mean velocity profile
Well predicted with few sampling points
Sectional drag coefficient
Much lower for aligned/square arrays - sheltering
Much lower for staggered array
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Mixing length profile
Velocity profile not exponential in canopy
Velocity profile logarithmic above canopy
Mixing length minimum at top of canopy
Blocking of eddies by shear layer
dzdU
wu
ml /
''
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Conclusions• High resolution DNS of flow over cubes – excellent agreement with data
• Vortex structures both above and within array
unsteady flow very different from mean flow
• Strong shear layer at top of array
decouples flow within array from that within
• Time-mean flow structure depends on layout
vortex in canyon for aligned/square arrays
no recirculation bubble for staggered array
• Dispersive stress small above array, large within
• Log profile above arrays
• Mean flow and turbulence structure is different from plant canopies