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Research Papers

Microscale Computational Fluid Dynamics Simulation for Wind Mapping Over Complex Topographic Terrains

[+] Author and Article Information
Ashkan Rasouli

e-mail: arasouli@alumni.uwo.ca

Horia Hangan

e-mail: hmh@blwtl.uwo.ca
Wind Engineering, Energy and Environment
(WindEEE) Research Institute,
Western University,
1151 Richmond Street,
London, ON N6A 5B9, Canada

Contributed by the Solar Energy Division of ASME for publication in the Journal Of Solar Energy ENGINEERING. Manuscript received June 26, 2012; final manuscript received March 13, 2013; published online June 25, 2013. Assoc. Editor: Christian Masson.

J. Sol. Energy Eng 135(4), 041005 (Jun 25, 2013) (18 pages) Paper No: SOL-12-1165; doi: 10.1115/1.4024124 History: Received June 26, 2012; Revised March 13, 2013

Wind mapping is of utmost importance in various wind energy and wind engineering applications. The available wind atlases usually provide wind data with low spatial resolution relative to the wind turbine height and usually neglect the effect of topographic features with relatively large or sudden changes in elevation. Two benchmark cases are studied for computational fluid dynamics (CFD) model evaluation on smooth two-dimensional (2D) and three-dimensional (3D) hills. Thereafter, a procedure is introduced to build CFD model of a complex terrain with high terrain roughness heights (dense urban area with skyscrapers) starting from existing topography maps in order to properly extend the wind atlas data over complex terrains. CFD simulations are carried out on a 1:3000 scale model of complex topographic area using Reynolds averaged Navier–Stokes (RANS) equations along with shear stress transport (SST) k-ω turbulence model and the results are compared with the wind tunnel measurements on the same model. The study shows that CFD simulations can be successfully used in qualifying and quantifying the flow over complex topography consisting of a wide range of roughness heights, enabling to map the flow structure with very high spatial resolution.

Copyright © 2013 by ASME
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Figures

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Fig. 1

NASA hump model. (a) Schematic of the hump (from Ref. [24]), (b) hump profile.

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Fig. 2

Solution domain and boundary conditions for NASA hump test case

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Fig. 3

Structured grid over NASA hump model. View of the entire solution domain and magnified view of the grid around hump model.

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Fig. 4

Pressure (a) and skin friction (b) coefficients on the hump surface obtained by SST k-ω and RSM turbulence model

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Fig. 5

Velocity profiles in four sections over the hump for SST k-ω and RSM turbulence model. C3 and C4 are also compared with measurements.

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Fig. 6

Middle section profile of the three-dimensional hill

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Fig. 7

Solution domain and boundary conditions for three-dimensional hill

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Fig. 8

Hybrid grid over three-dimensional hill model. View of the entire solution domain and zoomed sectional view of the grid around hill model.

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Fig. 9

Speed-up ratios (S) for three locations over the hill (hill foot, midslope, and summit)

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Fig. 10

Streamwise velocity profiles on four locations on the midsection of the hill (y/L = 0) at (a) x/L = 0, (b) x/L = 0.45, (c) x/L = 1.0, and (d) x/L = 1.5. The experimental values are from Ref. [28].

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Fig. 11

Google Earth satellite images of Hong Kong: (a) extent of the topographic model, (b) Southeast Hong Kong. The marked area represents the extents of the wind tunnel and CFD model.

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Fig. 12

Modeling procedure for complex topographic terrains

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Fig. 13

Southeastern Hong Kong model. (a) Digital elevation model and (b) NURBS surface.

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Fig. 14

Streamwise velocity and turbulence intensity profiles upstream of the topography model from hot-wire measurements

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Fig. 15

Solution domain and boundary conditions for topography models

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Fig. 16

Hybrid grid over topography model. View of the entire solution domain and magnified view of the grid near topography surface.

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Fig. 17

Roughness simulation in hill configuration: (a) roughness blocks in wind tunnel model, (b) roughness elements implemented in the numerical model, (c) the elements are staggered in an angle to produce maximum frontal area—the camera axis is in direction of free stream. Flow direction is from bottom-left corner to the top-right corner in isometric views ((a) and (b)).

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Fig. 18

(a) Boundary layer profile shape with respect to the change of roughness in upstream (reprinted from Ref. [36], with permission from Elsevier). (b) Boundary layer profiles at the upstream and downstream of the bell-shaped roughness elements. The dashed line represents the inner boundary layer thickness (the height g2 as shown in (a)) calculated from theoretical relations proposed in Ref. [36].

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Fig. 19

Topographic contours and side view of the valley configuration with horizontal and vertical measurement area locations, size and reference coordinates. The rectangles show the extent of the PIV measurements in horizontal and vertical planes. The thick solid lines in side view correspond to the horizontal measurement planes demonstrated as a rectangle in top view.

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Fig. 20

Mean vorticity contour plots for the valley flow in a vertical plane at y = 0. (a) PIV measurements, and (b) CFD simulation. Mean vorticity contours (1/s), flow direction is from right to left.

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Fig. 21

Comparison of CFD predicted mean velocity profiles by PIV and hot-wire measurements for the valley flow

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Fig. 22

Comparison of CFD predicted turbulent intensity profiles by PIV and hot-wire measurements for the valley flow

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Fig. 23

Topographic contours and side view of the hill configuration with horizontal and vertical measurement area locations, size and reference coordinates. The rectangles show the extent of the PIV measurements in horizontal and vertical planes. The thick solid lines in side view correspond to the horizontal measurement planes demonstrated as a rectangle in top view.

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Fig. 24

Mean contour plots at hub height (z=50 m) for the hill flow. (a) Velocity magnitude contours (m/s) and (b) mean wind power per unit area (W/m2). Flow direction is aligned with x-axis. The plots cover an area of 12 km × 14 km.

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Fig. 25

Comparison of CFD predicted mean velocity profiles by PIV and hot-wire measurements for the hill flow

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Fig. 26

Topographic contours and side view of the ridge configuration with horizontal measurement area locations, size, and reference coordinates. The rectangle shows the extent of the PIV measurement in the horizontal plane. The thick solid lines in side view correspond to the horizontal measurement planes demonstrated as a rectangle in top view.

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Fig. 27

Velocity vectors for the ridge flow in a horizontal plane at z = 200 m (6 cm model scale). (a) PIV measurements and (b) CFD simulation. The velocity vectors are superimposed on the topography image. Flow direction is from left to right.

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Fig. 28

Velocity vectors for the ridge flow in a horizontal plane at z = 225 m (7.5 cm model scale). (a) PIV measurements and (b) CFD simulation. The velocity vectors are superimposed on the topography image. Flow direction is from left to right.

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Fig. 29

Comparison of CFD predicted mean velocity profiles by PIV and hot-wire measurements for the ridge flow

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