WIND PREDICTION IN URBAN AREA. Zhenqing Liu. Department of Civil Engineering University of Tokyo

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Transcription:

LES MODELING OF CANOPY FLOWS FOR WIND PREDICTION IN URBAN AREA Zhenqing Liu Takeshi Ishihara Bridge & Structure Lab Bridge & Structure Lab Department of Civil Engineering University of Tokyo

Background Single building Street City km Tens of Kilometers Hundreds of kilometers Generate the real building model Using ground roughness length Wide area : Wide area : High resolution : High resolution : Eg. Wind environment around buildings Eg. Long bridge, wind energy prediction 2

Objectives Propose a method to simulated the flow over urban area Validate the method by comparing the simulated results with experiments. Check if the method could give good results for Two different types of canopy exists in urban area, i.e. buildingsand d forest. 3

Fundamental equation Continuity equation u x i i = Momentum equation In fluid In roughness canopy u uu æ ö i u p t r + r = m - - t x x çè x ø x x i j i ij j j j i j u i uu i j u i p t ij r r æ m ö + = - - + t xj x j çè xj ø xi xj Smagorinsky Lilly SGS model 1 1æ ui u ö j t ij =- 2 mt Sij + tkkdij ; S ij = 3 2 ç + ç è xj xi ø 1 m 2 t = rls S = rls 2 S ijs ij; Ls = min æ kd, CV ö s 3 çèç ø f ui, C s =.32 s 4

Flow pattern V.S. density of roughness Ishihara et al. (1997) Isolated roughness flow Frontal density<1% Wake interference flow Skimming i flow (cavity flow) Frontal density>3% 5

Roughness canopy model V grid F Drag i V u A o u fu, i Velocity in cell Occupancy rate F Drag 1 = rc DAo u u i = -fui, Vg rid 2 FDrag 1 1 =- rc 2 l F Drag C D g : Drag force : Drag force coefficient =-f ui, V grid uu f o i l o Equivalent CD = force coefficient (1 - g ) ui = (1 - g o ) u i C f 2 g = o V grid V u Representative length l o g o V o gov = = A A o grid o 6

Drag force coefficient V u f u, i Drag force 1 1 =- rc 2 l g uu f o i o V grid F Drag 4 4. u i A o C Equivalent force coefficient C D f = - g o (1 ) 2 3. Exp. 風洞実験 Fitting 式 line Force coefficient C D,u 2. 1....2.4.6.8 1. g u C D æ 1.53 ö = min,2.75(1 - gu) è ç (1 - g ) ø u 7

Verification of street model Wind tunnel experiment Outline of simulation Roughness 2. 粗度ブロック P1 P2 P3 19.9 z [m] x [m] 6.8 8.11 1.51 12.95 Case 21. Layout of blocks Inflow Inflow Inflow.18 [m].3 [m].3 [m].6 [m].3 [m].3 [m].18 [m].12 [m].6 [m].3 [m].3 [m] g o=5.6% g o=12.5% g o=25.% 8

Numerical model Y Z Bird s view X Outlet 2 Side view 2 1 z 1.5 Inflow velocity Profile y Inlet 5 1 x 15 2 z 1 Roughness Canopy 5 1 15 2 x 5.5.4 z(m.3 m)growing g rate: 1.1.2.1.2.4.6.8 1 1.2 u(m/s) Canopy top grid size:.2m h Roughness Canopy First grid size:.2m Horizontal resolution: h 1 grids 9

Instantaneous flow fields over modeled roughness canopy Instantaneous flow fields visualized by vorticity Occupancy 5.6% Horizontal Slice z=1h Horizontal ontal Slice z=2h Occupancy 12.5% Horizontal Slice z=1h Horizontal Slice z=2h Occupancy 25.% Horizontal Slice z=1h Horizontal Slice z=2h Instantaneous turbulent flow fields are successfully captured 1

Comparison with experiments Occupancy 56% 5.6% 1m s 1 Simulation Experiment.25m 2 s 2 Simulation Experiment Mean Wind Speed Turbulent Kinetic Energy Occupancy 12.5% Occupancy 25.% Mean wind speed and kinetic energy are well reproduced. 11

Limitation of horizontal resolution In order to examine the effects of the horizontal grid resolution, threemeshsystems systems arechecked. h 2h 4h h h h Horizontal grid size h Horizontal grid size 2h Horizontal grid size 4h Vertical grid distributions are same for each case. Only the horizontal grid sizes are changed. 12

Effects of horizontal grid size to the mean wind speed Mean wind speed profile at x=12.96 (P3) h 2h 4h Occupancy 5.6%.5.5.5.4.4.4 Occupancy 12.5%.3.2 1.1.2.4.6.8 1 1.2.5.4.3 U(m/s).3.2 1.1.2.4.6.8 1 1.2 U(m/s).5.4.3.3.2 1.1.2.4.6.8 1 1.2 U(m/s).5.4.3 Horizontal grid size h Horizontal grid size 2hh Occupancy 25.%.2.1.2.4.6.8 1 1.2 U(m/s).5.4.2.1.2.4.6.8 1 1.2 U(m/s).5.4.2 Horizontal.1.2.4.6.8 1 1.2 grid size 4h U(m/s).5 Experiment.4.3.3.3.2.2.2.1.1.1.2.4.6.8 1 1.2 U(m/s) 2.2 4.4 6.6 8.8 1 12 1.2 U(m/s) 2.2 4.4 6.6 8.8 1 12 1.2 U(m/s) Accurate Acceptable Large error 13

Effects of horizontal grid size to the kinetic energy Kinetic energy profile at x=12.96 (P3) h 2h 4h Occupancy 5.6%.5.5.5.4.4.4 Occupancy 12.5%.3.2 1.1.5.1.15.2 k(m 2 /s 2 ).5.4.3.3.2 1.1.5.1.15.2 k(m 2 /s 2 ).5.4.3.3.2 1.1.5.1.15.2 k(m 2 /s 2 ).5.4.3 Horizontal grid size h Horizontal grid size 2hh.2.2.2 Horizontal.1.1.1.5.1.15.2.25.5.1.15.2.25.5.1.15.2.25 grid size 4h 25.%.5 k(m 2 /s 2 ) k(m 2 /s 2 ) k(m 2 /s 2 ).5.5 Experiment Occupancy.4.4.4.3.2.3.2.3.2.1.1.1 5.5 1.1 15.15 2.2 k(m 2 /s 2 ) 5.5 1.1 15.15 2.2 k(m 2 /s 2 ).55 1.1 15.15 2.2 k(m 2 /s 2 ) Accurate Acceptable Large error 14

Verification of forest model If the ground is covered by forest like canopy Momentum equation in canopy u i uu i j ui p tij r r æ m ö + = - - + f t x j x j èç x j ø x i x j 1 go f ui, =- rc f uu 2 i lo C ' o f ui u g, d = C f This value will be adjusted. d i lo ui, In the wind tunnel the ground is covered by artificial grass whose drag force coefficient, occupancy rate and the representative length thhave not been measured. 15

Numerical model Grid No. 7.5million 1mm f u, i 1 1 =- rc g 2 l go C = C = l ' d uu f o i 2 o f o 8. Roughness canopy 1mm Mean wind speed Fluctuations σ i /U ref Simulated results for the flow fields over forest are accurate. 16

Mean and fluctuating components Grid No. 7.5million h Exp. Ishihara (21) LES simulation U W σ u σv σ w Both mean and fluctuations of 3 D hill could be reproduced well. 17

Conclusions A method simulating the roughness canopy by adding a source term in the momentum equation are proposed. The flow fields over the roughness blocks are successfully reproduced by using this method. Simulated results show good agreement with experiment. The same method are applied for the flow over the artificial grass, and with adjusting the equivalent force coefficients the flow fields are well reproduced. 18

Thanks for your attention!