Adaptive wind tunnel model tests for a large cooling tower considering the realistic wind environment

*X.X. Cheng1), L. Zhao2), Y.J. Ge3) and J. Dong4)

1), 4) College of Civil Engineering, Nanjing Tech University, Nanjing 211816, China; 1), 2), 3) State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University,

Shanghai 200092, China 1) cxx_njut@njtech.edu.cn

ABSTRACT

The traditional wind tunnel model tests consider the theoretical atmospheric boundary layer (ABL) wind characteristics presented in Codes of Practice and publications as

targets in simulating ABL flow fields. However, the theoretical knowledge might be inapplicable to a specific engineering case, since it is obtained by generalizing large

quantities of measured data with simplifications and conservatism. To this end, adaptive wind tunnel model tests considering the realistic wind environment are proposed in this paper. According to the new simulation concept, field measurements for realistic ABL

flow characteristics at the engineering sites should be undertaken before wind tunnel model tests, and wind tunnel model tests should then be formulated and conducted

guided by field measurement results. Using a large cooling tower located in Xu-zhou, China as the engineering background, this paper proves that the adaptive wind tunnel model tests can lead to more reliable wind effects compared with those of the traditional

simulation concept.

1. INTRODUCTION

As a mature technique applied in aviation industry, the wind tunnel model test was introduced into wind engineering research and design in 1960s. After Jensen (1958)

proposed that the flow field simulated in the wind tunnel should be similar to the actual atmospheric boundary layer (ABL) flow field for wind engineering model tests, simulating ABL has become an indispensable test procedure. According to Cermak

(1987), physical modeling to quantify wind effects for either wind-engineering design or research requires simultaneous similarity for two distinct physical phenomena. The

initial consideration is similarity of the desired natural wind characteristics. When this requirement is satisfied, similarity of specific wind effects must then be considered. According to Eurocode 1 (1995), if wind tunnel model tests are carried out to evaluate

1)

Post-Doc Fellow 2),3),4)

Professor

the wind action on buildings, the following conditions should be considered: (1) the wind

model must reproduce the mean wind velocity variation with height, corresponding to the aerodynamic roughness of the site location and (2) the flow in the wind tunnel should

also be modeled to reproduce the turbulence adjusted to the local condition. To fulfill the task of simulating realistic ABL flow fields, passive simulation devices,

including spires, roughness elements, grids and baffles, can jointly be used in wind

tunnel model tests. It has been found that idealized flow fields can be obtained by adjusting the position and the number of some devices placed in the wind tunnel.

According to Lopes, Gomes et al. (2008), the generation of the ABL was achieved in a short wind tunnel considering the mean velocity profile, the turbulence profile and spectra of the velocity fluctuations by means of a combination between triangular spires

in the beginning of the tunnel’s working section and roughness elements distributed along the tunnel floor. According to Table 1 (Huang, Shi et al. 2001), different kinds of

ABL flow fields are successfully simulated using passive devices in wind tunnels of Tongji Univeristy in China. Even in an open-jet 12-fan testing facility, spires and roughness elements are proven to be effective in simulating the suburban exposure

wind flow (Fu, Chowdhury et al. 2014).

Table 1 Specifics for ABL flow field simulations in wind tunnels in Tongji University

Wind tunnel name

Size (m)

Wind speed range (m/s)

Built time

Simulated flow field

type*

Successfully simulated wind characteristics

Devices Representative engineering

services

TJ-1 1.2 ×1.8

×18

0.5~32.5

1991 Type B and C ABL flow

fields

Mean wind speed profile, turbulence

intensity profile, power spectral

density for

along-wind and vertical wind

speed fluctuations

Gird and spires

Oriental pearl TV tower in

Shanghai

TJ-2 3×2.5×15

0.5~68 1996 Type A, B, C and D ABL flow

fields

Mean wind speed profile, turbulence intensity profile,

power spectral density and turbulence

integral scale

Baffle, spires and roughness

elements

Jinmao tower in Shanghai

TJ-3 15×2 ×14

0.2~17.8

1994 Type A, B, C ABL flow

fields and typhoon flow field

Mean wind speed profile, turbulence

intensity profile and power

spectral density

Baffle, spires,

roughness elements and grid

Jiangyin bridge, Humen bridge,

many stadiums and highrise

buildings

* Note: ABL flow field types are defined by GB 50009-2001 (2002).

The passive method of simulating the ABL flow field in the wind tunnel is proven to

be effective. However, the simulation targets are not necessarily the realistic natural wind characteristics of the specific engineering site. According to GB 50009-2001

(2002), Simiu and Scanlan (1996) and Holmes (2001), ABL flow fields are simply divided into four types according to the roughness length of the ground surface. Empirical formulae for the mean wind velocity profile are given for each flow field type based on

on-site observations, but the turbulence intensity profiles are not definitively described. This is because that the roughness length varies in an interval for each terrain type

which causes uncertainties to the turbulence intensity (Holmes 2001), and the turbulence intensity also depends on the mean wind speed which changes over time (Kozmar 2011). The practice of regarding a representative turbulence intensity profile as

the simulation target for a type of ABL flow field in model tests (see, e.g., Xu, Yu et al. 2014, Lou, Zhang et al. 2015) is less reasonable. Besides, the practice of considering

theoretical wind characteristics presented in Codes of Practice and publications as simulation targets is unreliable. The theoretical knowledge is obtained by generalizing large quantities of measured data with simplifications and conservatism, so they might

be inapplicable to specific engineering cases. If it is possible, realistic turbulence intensity profile of the specific engineering site should be taken into account for wind

tunnel model tests. In this paper, a large cooling tower located in Peng-cheng electric power station in Xu-zhou, China is taken as the engineering background. Before its construction,

anemometers were installed on the site for obtaining the actual wind environment information. Guided by field measurement results, adaptive wind tunnel model tests were formulated and conducted. After the construction of the large cooling tower, the

realistic wind effects were obtained on the structure and compared with the model test results. The comparison demonstrates the usefulness of obtaining the realistic wind

environment parameters for guiding the wind tunnel model test. 2. WIND ENVIRONMENT AT THE ENGINEERING SITE

2.1 Theoretical turbulence intensity profile A 167-meter smooth-walled cooling tower was to be built in Peng-cheng power

station, Xu-zhou, China. To its south, an adjacent cooling tower of the same size would be built, and there was an industrial complex to its west (see Fig. 1). To its north and

east, there is no large interfering building, but a few mounds. According to the descriptions of terrain types given in Table 2 (Holmes 2001), the flow field at Peng-cheng electric power station is open terrain type, for which the roughness length is

in between 0.01 and 0.05 m (see Table 2).

Fig. 1 Site plan of Peng-cheng electric power station (unit: m)

Table 2 Terrain types and roughness length

Terrain type Description Roughness length (m)

Very flat terrain Snow, desert 0.001~0.005

Open terrain Grassland, few trees 0.01~0.05 Suburban terrain Buildings 3-5m 0.1~0.5

Dense urban Buildings 10-30m 1~5

According to Simiu and Scanlan (1996) and Holmes (2001), the following equation exists:

*

0

1( ) ln

zU z u

k z (1)

where z is the height above the surface, z0 is the roughness length, u* is the friction

velocity, U(z) is the mean wind speed at z height, and k=0.4. The friction velocity u* calculated for the site of Peng-cheng electric power station is 1.35~1.76 m/s. According to Simiu and Scanlan (1996), the longitudinal turbulence intensity is

defined as:

( )( )

uI zU z

(2)

where U(z) is mean wind velocity at elevation z, and σu is root mean square value of u.

The longitudinal turbulence fluctuations can be written as: 2 2

*u u (3)

where it is commonly assumed that β does not vary with height. Values of β suggested

for structural design purposes on the basis of a large number of measurements are listed in Table 3 (Simiu and Scanlan 1996).

Table 3 Value of β corresponding to various roughness lengths

Z0 (m) 0.005 0.07 0.3 1 2.5

β 6.5 6 5.25 4.85 4

By using the first-order exponential decay equation to fit data presented in Table 3,

the following relation between z0 and β can be obtained:

02.27exp( ) 4.050.68

z (4)

According to Eqn. (4), the value β for open terrain type is 6.29~6.16. Then, according to Eqn. (3), σu for open terrain type is 3.39~4.37 m/s. Thus, the theoretical turbulence

intensity profile for the site of Peng-cheng electric power station can be calculated using Eqn. (2). As is shown in Fig. 2, the theoretical turbulence intensity profile varies in the

interval between the lower and upper envelopes due to the uncertainty of the roughness length.

10 12 14 16 18 20 22

0

20

40

60

80

100

120

140

160

Lower Envelope

Upper Envelope

Hei

ght

(m)

Turbulence Intensity (%) Fig. 2 Upper and lower envelopes of the theoretical turbulence intensity profile in open

terrain

2.2 Actual turbulence intensity profile

Before the construction of the two-grouped cooling towers, a two-dimensional (2D)

propeller anemometer, a three-dimensional (3D) ultrasonic anemometer and a vane are arranged at the engineering site at 20-meter height in 2007 (see Fig. 3). For the 2D propeller anemometer, measured data are the wind speed and the wind direction in the

horizontal plane. The 3D ultrasonic anemometer can record full oncoming flow information, including wind speed, azimuth angle and elevation angle, which is more

preferable in use under normal weather conditions. However, the performance of the 3D anemometer is likely to be adversely affected by rainwater, and 2D anemometer is used as 3D anemometer’s substitute on rainy days.

Fig. 3 Anemometers and vane

The field measurements for the realistic flow field information last for over one year. A huge amount of wind speed samples has been obtained, from which records with constant strong winds are selected and processed. They are divided into 10-min data

segments, and the turbulence intensities and the corresponding mean wind speeds are calculated for each segment. Fig. 4 illustrates some representative results, which

suggests that turbulence intensity tends to decrease as the mean wind speed increases, which accords with Quan, Wang et al. (2013). The longitudinal turbulence intensity measured at 20-meter height is in [0.006, 0.25], and the mean value is 0.027 which is

much smaller than the theoretical turbulence intensity calculated at the same height.

6 8 10 12 14 16 18 20

0

2

4

6

8

10

12

14

16

Turb

ule

nce

Inte

nsi

ty (

%)

10-min Mean Wind Speed (m/s) Fig. 4 Measured turbulence intensities at 20-meter height

Using Eqn. (2), the turbulence profiles are calculated based on measured data. A

comparison between measured and theoretical turbulence intensity profile envelopes made in Fig. 5 suggests that the upper envelope for measured turbulence intensity

profiles is close to the theoretical value, but the lower envelope for measured turbulence intensity profiles is close to the vertical axis, which is significantly smaller than the theoretical value. Thus, it can be concluded that the oncoming flow at Peng-cheng

electric power station is highly uncertain, as the measured flow characteristic varies in an extremely wide interval. The flow with negligible free-stream turbulence and the

theoretical open terrain ABL turbulent flow can be approximately regarded as the two extremes of the realistic oncoming flow in terms of the turbulence intensity.

0 2 4 6 8 10 12 14 16 18 20 22

0

20

40

60

80

100

120

140

160

Hei

ght

(m)

Turbulence Intensity (%)

Measured Lower Envelope

Measured Upper Envelope

Theoretical Lower Envelope

Theoretical Upper Envelope

Fig. 5 Measured and theoretical turbulence intensity profile envelopes

3. ADAPTIVE WIND TUNNEL MODEL TESTS

Without the realistic oncoming flow information, traditional wind tunnel model tests rely solely on the theoretical knowledge, which might lead to unrealistic results.

Considering the field measurement findings (see Sec. 2.2) , the model tests for Peng-cheng cooling tower are adaptively formulated and presented in this section, which include the following steps: First, the uniform flow field with negligible free-stream

turbulence is simulated in the wind tunnel, and the corresponding wind effects are regarded as the lower limit value; Second, the traditional ABL turbulent flow field for

open terrain is also used, and the wind effects obtained in the flow field are regarded as the upper limit value; Third, the final result is obtained by averaging the upper and the lower limits.

3.1 Model test in uniform flow field with negligible free-stream turbulence

The wind tunnel model test is carried out in TJ-3 atmospheric boundary layer (ABL) wind tunnel at Tongji University, Shanghai. It is a closed circuit rectangular cross-section wind tunnel, wherein the size of the test zone is 15m in width, 2m in height and 14m in

length. The test wind speed can be continuously controlled in a range from 1 to 17.6m/s. In uniform flow field, the non-uniformity of wind speed in test zone is less than 1%, the

turbulence is less than 0.5% and the average flow deviation angle is less than 0.5°. The wind speed at the model top height is regarded as the reference wind speed,

which is measured by a system composed of a pitot tube and a micromanometer. The wind pressures on the tower model are obtained using a pressure measurement system

composed of a DSM3000 electronic pressure scanning valve, a PC machine and a self-programming signal acquisition system, whose sampling frequency is 312.5Hz. The data length at each pressure measurement point in each run is 6000. The 1:200 scaled

pressure measurement model is made of synthetic glass, which ensures its strength and rigidity. Its prototype is the 167-meter high Peng-cheng cooling tower. 12×36

measurement points are arranged along the meridian and circumferential directions, respectively. The model in uniform flow field is shown in Fig. 6, and the distribution of the measurement points is presented in Fig. 7.

Fig. 6 Tower model in uniform flow field

(a) Prototype heights (unit: m) (b) Measurement sections

Fig. 7 Measurement point distribution on model surface

To simulate the high Reynolds number (Re) effects, 8 types of surface roughness are set up on the model. For each surface roughness condition, pressure measurement tests are conducted under 4 wind speeds (6m/s, 8m/s, 10m/s and 12m/s). Thus, the

data for a total of 32 (8×4) cases are obtained. To avoid the end effects, the 8th circumferential section which is closest to the throat of the tower model is chosen as the

characteristic section. By processing data obtained on the 8th section, it can be found that only 5 within the 32 cases can successfully re-simulate the actual static characteristics of the prototype cooling tower in the reduced-scale model with lower Re.

This can be proved from a good fitting of the two mean wind pressure distributions based on the model test and the full-scale measurement (Niemann 1971), respectively

(see Fig. 8 (a)). The five cases are regarded as valid simulation cases, and the dynamic wind effects for the valid simulation cases are presented in Fig. 8 (b).

0 20 40 60 80 100 120 140 160 180

-1.6

-1.4

-1.2

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Pre

ssure

coef

fici

ent

Cp

Angle (Degree)

Niemann (1971)

Two-layer paper tape 10m/s

Two-layer paper tape 12m/s

Three-layer paper tape 6m/s

Four-layer paper tape 6m/s

Four-layer paper tape 8m/s

0 20 40 60 80 100 120 140 160 180

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

0.22

RM

S o

f pre

ssure

coeff

icie

nt

(Cp)

Angle (Degree)

Two-layer paper tape 10m/s

Two-layer paper tape 12m/s

Three-layer paper tape 6m/s

Four-layer paper tape 6m/s

Four-layer paper tape 8m/s

(a) Mean wind pressure distribution (b) Fluctuating wind pressure distribution

Fig. 8 Wind effects for valid simulation cases obtained in uniform flow field

3.2 Model test in traditional open terrain ABL turbulent flow field

Using triangular spires and roughness elements, the traditional ABL turbulent flow

field for open terrain is simulated for the test. Fig. 9 suggests that all simulated flow field characteristics are close to the targets (Simiu and Scanlan 1996, Holmes 2001). In Fig. 9, the power spectral density is measured at 1 m height, and the simulated turbulence

integral scale at that height is around 0.3 m.

1 10

0.01

0.1

1

10

nS

u(n

)/u

*2

nZ/U

Measured PSD

Von Karman spectrum

0 2 4 6 8 10 12 14 16 18

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Measured Value

Average of Theoretical Profiles

(Simiu and Scanlan 1996)Z

/HG

Iu (%)

0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Z/H

G

U/UG

Measured Value

Theoretical Profile U/UG=(Z/HG)0.16

(Simiu and Scanlan 1996)

(a) Power spectral function for along-wind

component of wind speed

(b) Turbulence intensity

profile

(c) Average wind velocity

profile

Fig. 9 Characteristics of traditional ABL turbulent flow field simulated in the TJ-3 (HG and

UG refer to the gradient height and the geostrophic velocity, respectively)

The model in traditional ABL turbulent flow field is shown in Fig. 10, and the wind

tunnel model test and the data processing are undertaken in the same way as those conducted in uniform flow field. The obtained results presented in Fig. 11 suggest that 5

valid simulation cases exist. The static wind effects for the 5 cases are all close to the full-scale measurement result (see Fig. 11 (a)), but the fluctuating wind pressure distributions are different (see Fig. 11 (b)).

Fig. 10 Tower model in traditional ABL turbulent flow field

0 20 40 60 80 100 120 140 160 180

-1.8

-1.6

-1.4

-1.2

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Pre

ssure

coef

fici

ent

Cp

Angle (Degree)

Niemann (1971)

Three-layer paper tape 12m/s

Four-layer paper tape 6m/s

Four-layer paper tape 8m/s

Four-layer paper tape 10m/s

Four-layer paper tape 12m/s

0 20 40 60 80 100 120 140 160 180

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0.12

0.13

0.14

0.15

0.16

0.17

0.18

0.19

0.20

0.21

0.22

0.23

RM

S o

f pre

ssure

coeff

icie

nt

(Cp)

Angle (Degree)

Three-layer paper tape 12m/s

Four-layer paper tape 6m/s

Four-layer paper tape 8m/s

Four-layer paper tape 10m/s

Four-layer paper tape 12m/s

(a) Mean wind pressure distribution (b) Fluctuating wind pressure distribution

Fig. 11 Wind effects for valid simulation cases obtained in traditional ABL turbulent flow field

4. FULL-SCALE MEASUREMENTS FOR WIND EFFECTS ON PENG-CHENG

COOLING TOWER

After the model tests, the full-scale wind effects are further measured on

Peng-cheng cooling tower, which are employed to see whether the underlying problem with the traditional wind tunnel model test is mitigated.

4.1 Setup for full-scale measurements

During Peng-cheng cooling tower’s construction in 2009, 36 transducers are evenly installed around the tower’s throat section at 130-meter high (see Figs. 12 and

13). Besides, another transducer is arranged inside a cabin, which provides static reference pressure for measurements presented in this paper.

θ

Fig. 12 Plan of pressure measurement points

Fig. 13 Projection of measuring tower (unit: m)

The wind pressure transducers used are piezoresistive ones, whose dimensions

are: 13cm in length, 5cm in width and 3cm in depth (see Fig. 14). The transducers’

maximum measured value is ±2.5kPa (corresponding to 63m/s wind speed). Their maximum sampling frequency and precision are 100Hz and 1/1000 maximum range,

respectively.

(a) an actual transducer (b) Dimension (unit: mm)

Fig. 14 Wind pressure transducer

Before installed on the prototype tower, the transducer is tested in TJ-2 wind tunnel of Tongji University for its performances. It is found that when oncoming flow

speed is greater than 15m/s, the noise to signal ratio for the transducer is kept below 5% (see Fig. 15 (a)). Besides, it is shown that the signal produced by the transducer agrees with those obtained using high-precision electronic pressure scanivalve in 0 -6Hz

frequency domain (see Fig. 15 (b)). These prove that both static and dynamic performances of the transducer are agreeable.

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

RMS of Wind Pressure

Noise to Signal Ratio

Wind Speed (m/s)

RM

S o

f W

ind

Pre

ss

ure

(P

a)

0.01

0.1

1

15m/s11m/s

No

ise

to S

ign

al R

atio

0.05

1 10

0.1

1

10

100

1000

Win

d P

res

su

re P

ow

er

Sp

ec

tra

l D

en

sit

y (P

a2*s)

Frequency (Hz)

Wind Pressure Transducer

Electronic Pressure Scanivalve

6.0Hz

(a) Static performance (b) Dynamic performance

Fig. 15 Wind tunnel tests for transducer’s performances

The whole full-scale measurement campaign lasts from 2010 to 2015 on a 2-3

times of intensive test per year basis. In each time, we predict the occurrence of the strong wind scenario based on a local meteorological center’s weather -forecast.

Equipments are set up before the arrival of the strong wind, and 24-hours simultaneous recordings for wind and wind-induced pressures are then conducted which usually continue for 1 to 2 weeks long. In the huge amount of data measured, those obtained

from Nov. 28, 2011 to Dec. 12, 2011 are found to be most representative.

The daily predominate wind direction and the daily representative 10-min mean wind velocity obtained from Nov. 28 to Dec. 12 in 2011 are shown by Fig. 16 and Fig. 17, respectively (the mean wind velocities are obtained at 20-meter high and converted to

the corresponding values at 130-meter high using the power law formula of mean wind profile). As can be seen from Fig. 17, only wind speeds for Nov. 29 and Dec. 8 exceed

12m/s, which represent valid strong wind scenarios. However, the wind directions on the two days are quite different. On Nov. 29, the oncoming flow is from due east, but it is from due north on Dec. 8 (see Fig. 16). Since some transducers installed on the tower’s

north surface are found ineffective, complete fluctuating wind pressure distribution can only be obtained on Nov. 29. Besides, the upstream terrain is smooth, and there are no

obvious interference effects caused by neighboring cooling towers or buildings with respect to the specific wind direction of Nov. 29. As a result, the wind-induced pressures recorded on Nov. 29 in 2011 should be used.

0

45

90

135

180

225

270

315

360

Nov.28 Nov.29 Nov.30 Dec.1 Dec.2 Dec.3 Dec.4 Dec.5 Dec.6 Dec.8 Dec.9 Dec.11 Dec.12

Time

Wind Direction θ

(Degree)

Fig. 16 Daily predominant wind direction (see Fig. 12 for definition of wind direction)

3.9

12.06

7.8

1.95

3.77

6.836.03

9.178.39

13.65

10.53

8.78

4.29

0

2

4

6

8

10

12

14

16

Nov.28 Nov.29 Nov.30 Dec.1 Dec.2 Dec.3 Dec.4 Dec.5 Dec.6 Dec.8 Dec.9 Dec.11 Dec.12

Time

Wind Speed at 130m (m/s)

Fig. 17 Daily representative 10-min mean wind speed at 130-meter height

4.2 Validation of model test results using full-scale wind effects

On Nov. 29 in 2011, six groups of 10-min wind pressure samples with mean wind speed in between 11.3 and 16.4m/s (at 130-meter high) are produced by transducers installed on Peng-cheng cooling tower. After data processing, the fluctuating wind

pressure distributions obtained are compared with those of two early field measurement campaigns in history (Ruscheweyh 1976, Sageau 1979) and one model test study

(Davenport and Isyumov 1996) in Fig. 18. It is obvious that the basic tendencies of those distributions are the same. All of the curves in Fig. 18 can be divided into three regions: windward region (0-40 degree), side region (40-120 degree) and wake region (120-180

degree). In windward region, the fluctuating wind pressure coefficients decrease with the increase of angle. In side region, the fluctuating wind pressure coefficients first increase

and then decrease with the increase of angle, reaching the peaks at the angles between 80 and 100 degrees. In wake region, the fluctuating wind pressure coefficients decrease and then remain stable at a certain value. However, it is obvious that the results on

Peng-cheng cooling tower are smaller than those on cooling towers of smaller sizes over the full half-circle. It is suspected that the differences have resulted from the

discrepancy of the turbulence intensity of the oncoming flow. In addition, Fig. 18 compares the fluctuating wind pressure distributions measured

on Peng-cheng cooling tower with the results obtained by wind tunnel model tests under uniform flow. It can be found that the model test results are approximately the lower

envelopes of the full-scale measurement results, which supports the practice of regarding wind effects obtained in uniform flow field as the lower limit value (see Sec. 3).

Fig. 18 Fluctuating wind pressure distributions obtained by full-scale measurements and

wind tunnel model tests under uniform flow

Fig. 19 equally compares the fluctuating wind pressure distributions measured on

Peng-cheng cooling tower with the results obtained by wind tunnel model tests under traditional ABL turbulent flow. It can be found that the model test results are approximately the upper envelopes of the full-scale measurement results, which also

supports the practice of regarding wind effects obtained in ABL turbulent flow field as the upper limit value (also see Sec. 3).

Fig. 19 Fluctuating wind pressure distributions obtained by full-scale measurements and

wind tunnel model tests under turbulent flow

By using a mathematical conversion method (Zhao, Cheng et al. 2012), the model test results obtained under uniform and turbulent flows are averaged. A comparison made in Fig. 20 indicates that the averaged model test result is very close to the

full-scale measurement results. Due to discretization errors, the averaged model test result might vary in a range, which is shown in Fig. 20. Coincidentally, most realistic

fluctuating wind pressure coefficients fall into the variation range. These prove that the

average value of the two wind tunnel model test results is the reasonable final result, and it can be applied to the full-scale condition.

Fig. 20 Fluctuating wind pressure distributions obtained by full-scale measurements and

the average value of the two wind tunnel model test results 5. CONCLUSIONS

(1) Theoretical knowledge and field measurement results both indicate that the turbulence intensity profile cannot be definitively described for each terrain type. This is because the turbulence intensity depends on the roughness length and the mean wind

speed, which both vary in intervals. (2) The turbulence intensity measured at Peng-cheng power station varies in a

wider range than the theoretical value, and the lower envelope for measured turbulence intensity profiles is extremely low compared with the theoretical one. These suggest that there exist possibilities that theoretical ABL flow characteristics presented in Codes of

Practice and publications might not be applicable to a specific engineering case. A reasonable explanation is that theoretical results are obtained by generalizing large

quantities of measured data, and simplifications and conservatism are usually included in generalization.

(3) With measured wind environment information at hand, wind tunnel model tests

can be adaptively formulated considering the realistic ABL flow characteristics. By comparing wind effects obtained from model tests and full-scale measurements, this

paper proves that the adaptive model tests lead to more reliable results. Thus, it is suggested that if possible, field measurements for wind environments at specific engineering sites should be undertaken before wind tunnel model tests.

(4) The fluctuating wind pressure distributions obtained by wind tunnel model tests under traditional open terrain ABL turbulent flow are approximately the upper envelopes

of the full-scale measurement results. This suggests the conservativeness of the

traditional model tests.

(5) The fluctuating wind pressure coefficients on Peng-cheng cooling tower are found to be much smaller than those measured on other cooling towers over the full

half-circle. It is assumed that the differences have resulted from the discrepancy of the turbulence intensity of the oncoming flow. So, occasionally, wind effects obtained from one engineering case cannot be simply generalized to another without knowing the

oncoming flow information.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the support of the National Natural Science Foundation of China (51178353 and 50978203) and the National Key Basic Research

Program of China (i.e. 973 Program) (2013CB036300), and the support of China Postdoctoral Science Foundation.

REFERENCES

Center for European Standardization, Brussels, Belgium (1995), Eurocode 1: Basis of

Design and Actions on Structures Part 2-4: Actions on Structures Wind Actions.

Cermak, J.E. (1987), “Advances in physical modeling for wind engineering”, Journal of Engineering Mechanics, ASCE, 113(5), 737-756.

Davenport, A.G. and Isyumov, N. (1966), The Dynamic and Static Action of Wind on

Hyperbolic Cooling Tower, University of Western Ontario, London, Canada. Fu, T.C., Chowdhury, A.G., Bitsuamlak, G. and Baheru, T. (2014), “Partial turbulence

simulation and aerodynamic pressures validation for an open-jet testing facility”, Wind and Structures, 19(1), 15-33.

Holmes, J.D. (2001), Wind Loading of Structures, London: Spon Press.

Huang, P., Shi, Z., Chen, W. and Gu, M. (2001), “Simulation method and measuring technology of atmospheric boundary layer”, Journal of Tongji University, 29(1), 40-44.

Jensen, M. (1958), “The model-law for phenomena in natural wind”, Ingenioren (Int. Ed.), 2, 121-128.

Kozmar, H. (2011), “Wind-tunnel simulations of the suburban ABL and comparison with international standards”, Wind and Structures, 14(1), 15-34.

Lopes, M.F.P., Gomes, M.G. and Ferreira J.G. (2008), “Simulation of the atmospheric

boundary layer for model testing in a short wind tunnel”, Experimental Techniques, 32(4), 36-43.

Lou, W., Zhang, L., Huang, M.F. and Li, Q.S. (2015), “Multiobjective equivalent static

wind loads on complex tall buildings using non-Gaussian peak factors”, Journal of Structural Engineering, ASCE, Article ID: 04015033 (12 pages).

Ministry of Construction, P.R.C. (2002), GB 50009-2001: Load Code for the Design of building Structures.

Niemann, H.J. (1971), Zur stationaren windbelastung rotations-symmetrischer

Bauwerke im Bereich transkritischer Reynoldszahlen. Mitt. Nr. 71-2, Tech.-wissensch. Mitt., Institut fur Konstr. Ing.-ban, Ruhr-Universitat Bochum, West Germany.

Quan, Y., Wang, S., Gu, M. and Kuang, J. (2013), “Field measurement of wind speeds

and wind-induced responses atop the Shanghai world financial center under normal climate conditions”, Mathematical Problems in Engineering, Article ID: 902643 (14

pages). Ruscheweyh, H. (1976), “Wind loadings on hyperbolic natural draft cooling towers”,

Journal of Industrial Aerodynamics, 1, 335–340.

Sageau, J.F. (1979) Caracterisation des champs de pression moyens et fluctuants a la surface des grands aerorefrigerants, Electricite de France, Direction des Etudes et

Recherches, 6 quai Watier, Chatou, France. Simiu, E. and Scanlan, R.H. (1996), Wind Effects on Structures, New York: John Wiley & Sons.

Xu, H., Yu, S. and Lou, W. (2014), “The inertial coefficient for fluctuating flow through a dominant opening in a building”, Wind and Structures, 18(1), 57-67.

Zhao, L., Cheng, X., Dong, R. and Ge, Y. (2012), “Investigation of surface roughness and its influence to flow dynamic characteristics of hyperbolic cooling tower”, Proceedings of the 6th International Symposium on Cooling Towers , Cologne,

Germany.