vol. 9 no. 1 january 2012 - iswe : indian society for wind ... · journal of wind and engineering,...

JOURNAL OF WIND & ENGINEERING

Vol. 9 No. 1 January 2012

CONTENTS

1. Along - Wind Response of A Tall Rectangular Building : A Comparative 1-19

Study of International Codes/Standards with Wind Tunnel Data

Nikhil Agrawal, Achal Mittal, Amit Gupta, V. K. Gupta

2. Tracer Gas dispersion in an Urban Environment: 20-32

Scaling Considerations in Wind Tunnel Testing

Amit Gupta, Ted Stathopoulos

3. Comparison of Codal Values and Experimental Data 33-53

Pertaining to Dynamic Wind Characteristics

Nikhil Agrawal, V. K. Gupta, Amit Gupta, Achal Mittal

Journal of Wind and Engineering, Vol. 9, No. 1, January 2012, pp 1-19.

1 Research Scholar, Department of Civil Engineering, IIT Roorkee ([email protected])

2 Principal Scientist, Structural Engineering Group, CSIR-CBRI Roorkee ([email protected])

3 Structural and Wind Engineering Consultant, Roorkee ([email protected])

4 Professor, Department of Civil Engineering, IIT Roorkee ([email protected])

Along - Wind Response of A Tall Rectangular Building:

A Comparative Study of International Codes/Standards with

Wind Tunnel Data

Nikhil Agrawal1, Achal Mittal2, Amit Gupta3, V. K. Gupta4

ABSTRACT

This paper presents a comparison of along wind load and its effect on tall rectangular buildings obtained from

different international wind codes/standards for three different terrain categories namely: suburban, heavy

suburban and urban. The codes/standards studied are those for Japan, Australia/New-Zealand, United States,

British/European, Canada, Hong-Kong and India [existing (1987) as well as proposed (2011)].

Different parameters like gust factor, shear force, base bending moment and peak acceleration in along wind

direction have been compared for two different plan orientations of a building. The results of wind tunnel

test on an aero-elastic model have also been presented along with values by different codes/standards. The

similarities and differences of different codes/standards are also discussed.

Key words : Along wind, Wind codes/standards, Terrain categories, Building orientation, Gust loading

factor, Tall building.

NOTATION

b Width of building (m) S Size reduction factor

H Height of building (m) E Gust energy ratio

d Depth/length of building (m) r Roughness factor

B Background component mo

Average mass per unit height (kg/m)

R Resonant component Vo

Basic wind velocity (m/s)

ρbldg

. Density of building . Lz

Turbulent length scale at any height Z (m)

ρair

Density of air LH

Turbulent length scale at building height (m)

β Critical damping ratio na

First mode frequency of building (Hz)

CD, C

fDrag/force coefficient N Effective reduced frequency

G Gust factor φ Factor to account for second order turbulent

intensity

Z , Ze

Reference height (m) CeH

Exposure factor

zo

Roughness length (m) VD

/ Va

Up-crossing frequency (Hz)

T Averaging time K A factor related to surface roughness

coefficient of the terrain

IZ Turbulent intensity at height Z φ(z) Along wind mode shape function

g, gf,g

vPeak factor ξ Mode exponent

gR

RL, R

H, R

DAerodynamic K Non dimensional coefficient

admittance functions

α Power law index . V Z Hourly mean wind velocity (m/s)

Usual meaning of notation unless/otherwise mentioned in the text

2 Along - Wind Response of a Tall Rectangular Building: A Comparative Study of International Codes/Standards With Wind Tunnel Data

INTRODUCTION

Under the influence of dynamic wind loads, typical high-rise buildings may oscillate in the along-wind, across-

wind, and torsional directions. The along-wind motion primarily results from pressure fluctuations on the

windward and leeward faces, which generally follow the fluctuations in the approach flow, at least in the low

frequency range. Therefore, along-wind aerodynamic loads may be quantified analytically, utilizing quasi-

steady and strip theories, with dynamic effects customarily represented by a random vibration based "Gust

Factor Approach" (Davenport 1967, Vellozzi & Cohen 1968, Vickery 1970, Simiu 1976, Solari

1982, ESDU 1989).

Many researchers found it of interest to compare the prevalent international codes/standards, their treatment

of dynamic effects, and how well the estimated values compare with measured data. Such comparisons of

the suggested procedures given by codes/standards with wind tunnel data (for large collections of actual

buildings tested under both isolated conditions and in their actual surroundings) and comparisons with

full-scale data have been reported by Loh & Isyumov (1985), Ferraro et. al. (1989) and Lee & Ng (1988).

Holmes (2007) summarized a comparison of wind loading provisions among the following standards:

International Standards ISO 4354 (1997), Australian Standards AS/NZS 1170.2-2002, Euro code pre-

Standard EN 1991-1-4.6 (CEN, 2004), American ASCE 7-05, Japanese AIJ (2004) and British BS 6399:

Part 2 (1997), and highlighted their similarities and differences. Other comparisons between major wind

loading codes/standards have been made by Cook (1990), Mehta (1998), Kijewski and Kareem (1998),

Hajra and Godbole (2006) and Tamura et. al. (2009) for dynamic wind effects on buildings. A Special Issue

of the journal Wind and Structures in 2005 included five papers in which all aspects of codification for wind

loads were reviewed (Holmes et. al., 2005a,b; Letchford et. al., 2005; Kasperski and Geurts, 2005;

Tamura et. al., 2005).

Holmes et. al. (2009) described a comparison of wind load calculations on three buildings (low-rise H=6.2m,

medium-rise H=48m and high-rise H=183m) using fifteen different wind loading codes/standards from the

Asia-Pacific Region. Authors discussed reasons for differences in the results and also presented the extent of

variations in numerical terms.

Although sufficient work has been conducted on codes/standards, a comprehensive review of the provisions

particularly for different terrain categories has not been conducted so far.

The Codes/Standards considered herein are:

Architectural Institute of Japan (AIJ-2004) Recommendations for Loads on Buildings.

Australian Standard: Minimum Design Loads on Structures (AN/NZS 1172.2:2002).

British/European Standard: Euro-code 1: Actions on Structures (BS EN 1991-1-4:2005).

Code of Practice on Wind Effects in Hong-Kong (CPWEHK-2004).

Code of Practice for Design Loads for Buildings and Structures IS: 875(Part-3)-1987.

Code of Practice for Design Loads for Buildings and Structures IS: 875(Part-3)-2011 (Proposed).

Minimum Design Loads for Buildings and Other Structures (ASCE 7-05).

National Building Code of Canada (NBCC-1995).

A brief discussion of the treatment of dynamic wind loads and corresponding responses by these codes/

standards, in along wind direction has been given for a sample building. The results calculated from these

codes/standards in the along-wind direction for shear force, base bending moment, and accelerations at the

top of a building are compared to responses estimated from wind tunnel data. In total, this paper provides

critical evaluation of the codes treatment of dynamic effects in along wind direction by these codes/standards.

Journal of Wind and Engineering, Vol. 9, No. 1, January 2012, pp 1-19. 3

In the following text, details about the wind tunnel study have been presented first, followed by a discussion

of the comparison of various wind codes/standards for along wind response.

WIND TUNNEL STUDY

The wind tunnel tests were conducted in the Boundary Layer Wind Tunnel of civil engineering department at

Indian Institute of Technology Roorkee. This is an open circuit, continuous flow, suction type tunnel using

single blower fan (125 HP) having a test section of 2.1 m x 2.0 m size. The length of test section is 15m.

Turbulent boundary layer flows are developed over the fetches of upwind terrain, where vortex generators,

barrier wall and roughness blocks are set on the floor. In such a case, when the airflow approaches the

testing body, it develops characteristics similar to the natural wind attaining the desired wind velocity profile

(Asawa et. al.-1985).

Aeroelastic Model

In the present study, a single rigid lumped mass model, pivoted at the base, having two degrees of freedom,

described by Isyumov (1982) is adopted. This is a rectangular building model with cross-section 0.05x0.15x0.60

m. Tests were conducted for two different orientations, namely, long afterbody (LAB) and short afterbody

(SAB). Orientation of building in which shorter dimension of building faces the wind with longer dimension

along the wind corresponds to LAB orientation and when longer dimension of building faces the wind with

shorter dimension along the wind corresponds to SAB orientation. The first mode

frequency of the model is 19.0 Hz in LAB orientation and 16.0 Hz in SAB orientation. The structural density

of model is 183.4 kg/m3 and the assumed critical structural damping ratio is 0.015 in both the directions (IS

875: Part 3-1987, Gupta 1996). The length scale, velocity scale and frequency scale are also set as 1/400, 1/

4 and 100 respectively. Data are recorded for a sampling duration of 20 seconds (corresponding to 33.34 min.

at full scale) at a sampling rate of 250 Hz per channel, i.e., 3000 data points are taken for each channel. Two

acceleration sensors are placed at the top of the model to measure the along-wind and acrosswind

acceleration responses.

In all the roughness conditions considered, suburban (α=0.19), heavy suburban (α=0.25) and urban (α=0.33),

bending moment at the base and acceleration at the top of the building model were recorded simultaneously,

for a fan speed of 300rpm to 700rpm, which corresponds to mean wind speeds of 4 m/s to 12 m/s in along-

wind direction for both long as well as short afterbody orientations. Statistical parameters of the responses,

i.e., mean, standard deviation and peak moment, rms and peak acceleration in along-wind and across-wind

direction have been calculated for all the cases. Measured longitudinal mean wind velocity profile, turbulent

intensity profile, and turbulence spectrum of the wind simulation are shown in Figures 1 (a-c).

Figure 1 Wind model properties: (a) Mean wind velocity profiles (á=0.19, 0.25, 0.33); (b)

Turbulent intensity profiles; (c) Longitudinal turbulence spectrums for given terrains

The schematic drawing of the wind tunnel at Civil Engineering Department, IIT Roorkee is shown in the

Figure 2 (a). Figure 2 (b) shows a schematic figure of Aero-elastic model and Figure 2 (c) gives a

photographs of aero-elastic model used in this study


Table 2 Conversion Factors for 1-hour Averaging Time

The gust loading factor, G, may be defined as the ratio of the expected maximum response (e.g. deflection or

stress) of the structure in a defined period (e.g. 10-minutes or 1-h) to the mean or time-averaged response in

the same period. The expected maximum wind response, during an interval T may then be expressed as the

summation of the mean value and the RMS value multiplied by a statistically-derived peak factor

(Davenport 1967), For example, the expected maximum mean value of random, X, related to loading or

response is given by:

(1)

(2)

where g is the peak factor, σx is the RMS value of X, G is the gust factor, B is background factor and R is the

resonant factor. σx represents the area under the power spectral density of X which can be described in terms

of background component (B) and resonant component (R). For example, in the case of response, the back-

ground component (B) would represent the response due to the quasi-steady effects, while the resonant

component (R) would denote the response resulting from dynamic amplification. Typically, a stiffer building

would have major contributions from the background component, whereas for more flexible structure, the

resonant part would dominate.

Equation (2) or variations of it are used in many codes/standards for wind loading, for simple estimations of

the along-wind dynamic loading of structures. The usual approach is to calculate G for the modal coordinate

in the first mode of vibration, and then to apply it to a mean load distribution on the structure from which all

responses such as shear force/ bending moments are calculated (Holmes 2007).

For a quick reference, the procedure for gust loading factor and peak acceleration in the major codes/

standards are summarized in Table 3.

A Tall rectangular building is used as an example to compare the estimates of wind load effects based on

codes/standards. The building particulars are H=240m, b=20m, d=60m; natural frequency in SAB is 0.16 Hz

and in LAB orientation is 0.19 Hz, linear mode shape in two translation directions; critical damping ratio

β=0.015; drag force coefficient (as per IS: 875 (3)-1987) CD=1.27 in SAB orientation and 1.18 in LAB

orientation and building density ρ=183.4 kg/m3. The building is assumed to be located at Bombay (India) far

from sea. The basic 3-second gust wind velocity=44m/s (as per IS: 875(3)-1987). Comparison is made for

two different orientations (SAB, LAB) for three different terrains, namely, suburban, heavy suburban and

urban. For simplicity, the effects of wind direction, topography, shielding, importance and return period are

ignored in the following discussion.

Terrain Categories/Averaging Time 3 Seconds 10 Minutes

Suburban (Zo=0.2m) 1.40 1.05

Heavy Suburban (Zo=0.7m) 1.47 1.06

Urban (Zo=2m) 1.54 1.07

xgXX σ.max +=

RBg

Xg

X

XG x ++=+== .1.1max σ


Tab

le 3

(C

on

tin

ued

)

a-4.

Br

gf

=φ

; b-

2

BI

gh

v=

φ; c-

z

za V

Ln

N=

; d

- )

21(

221

1η

ηη

−−

−=

eL

R f

or η>

0:

and R

L=

1 f

or η=

0. R

H,

zV

Ha

n6.

4=

η,

Rb,

zV

ban

6.4=

η,

and R

D,

zV

dan

4.15

=η

; e-

)1ˆ

/(ˆ

)6

5.

1(+

+=

ξα

αK

and

ξφ

)/

()

(H

zz=

wh

ere ξ

is t

he

mode

expon

ent;

f-

R

Rn

a+

=1

.υ

;

g -

6/

52

.71

1

.4

+

=

H

Ha

H

Ha V

Ln

V

Ln

F; h

-2

2

2

RB

Rn

a+

=υ

h

za

.0

8.0≥

ν; i-

)

ln(

.2 )1

(

15.

0)

ln(

).1(

).12(

ozezozez

K

+

−

+

++

=ξξ

ξ

and

ξφ

)/

()

(H

zz=

wher

e ξ

is

the

mode

exponen

t, a

nd

(

)(

)

+

−=

′

07

.0

56

.0

/

/63

.0

1

14

.0

49

.0

2

bH

LbH

IC

H

zg

α, λ=

1;

j-as

fo

rmula

for

acce

lera

tion i

s n

ot

giv

en s

o g

ener

al e

quat

ion h

as b

een u

sed,

and K

=0.1

4,

72

.0

30

.4.

0

=

HC

eH

fo

r urb

an t

erra

in;

k

- K

=0.1

,

5.0

7.12

.5.

0

=

HC

eHfo

r hea

vy

sub

urb

an t

erra

in;

l-.

)1(

2

11

2

2

η

ηη

−−

−=

eR

H f

or η>

0:

and R

H=

1 f

or η=

0.

RH,

za

L

Hn

6.4

=η

, R

H=

Rb f

or

za

L

bn

6.4

=η

.

wh

ere:


Numerical values of different parameters contributing to GLF estimated from different codes/standards are

listed in Table 4.

Table 4 shows the Gust Factor (G) for two different building orientations in suburban, heavy suburban and

urban terrain. Typical values of different parameters used for estimation of GLF in different codes/standards

as observed in Table 4, are discussed below.

The mean hourly design wind velocity (after applying conversion factor) in Indian (1987/2011), Australian/

New-Zealand and American standards (which are based on 3s gust) are lower than those by other codes/

standards which are based on longer averaging time (10min or 1-hour). The effect of averaging time on

forces and accelerations can be seen in Figure 3.

American and British/European calculate the GLF at 0.6H, while others at building height H. Similarly,

value of r is taken 1.7Iz for ASCE, instead of 2I

z as in other codes/standards. Consequently result in higher

values of B and E.

Any parameter used in calculating GLF that has a higher value than those with other codes/standards are

generally compensated by other parameter in respective code at the end, and all codes provide comparative

values of GLF in the end. For example, value of resonant response factor (R) for AIJ code is much higher

than any other code, but at the same time the value of peak factor (gf) is lower, resulting in a comparable

value of GLF. Similarly, the value of turbulent length scale in Indian (1987) and Hong-Kong Standards is

much-much higher than any other code/standard, although its effect on GLF has been taken care of in

their background component (B).

Indian Standards show higher gust loading factor (2-15%) in spite of lower value of background (B) and

resonant factor (R) due to higher value of peak factor for suburban terrain.

Although, heavy suburban category is not defined in Indian standards and Australian/New-Zealand code,

values shown in Table 4 are computed from linear interpolation between the terrains suburban and urban.

Similarly, urban terrain (city centre) is not defined in American and British/European standards. The value for

GLF parameters for American code is computed from its earlier version (ASCE 7-98).

From Table 4, it is also noted that as roughness increases, the value of design wind velocity decreases and

turbulent intensity increases. Subsequently, background and resonant factors decrease but the peak factor

value for resonant factor increases, thus there is an increase in GLF.

It is interesting to note that the background factor is independent of terrain roughness for AS/NZS Code as

well as Hong-Kong code and almost constant for Indian (2011) and BS EN Standards although AIJ and

Indian Standards (1987) show variation of Background factors with terrain roughness.

Size reduction factor (S) depends on the natural frequency of building, height of building, width of building

facing the wind and design wind speed according to all codes/standards. For BS EN Standard, S depends on

length scale instead of design wind speed as in other codes/standards. In addition to the above parameters, S

is also dependent upon lateral dimension of the building as per American Standard. Graphical

representations of the GLF and responses: forces and accelerations for three terrains and two different

orientations of building are shown in Figure 3. The experimental results are also presented in the same

figure.

For simplicity in the comparison among codes/standards, the risk coefficient (1.07) is ignored, but it is anyway

included during wind tunnel experiment, so the experimental values presented in Figure 3 are higher that what


Tab

le 4

.Res

ult

of C

om

pu

tati

on

for

Su

bu

rban

(S

), H

eavy S

ub

urb

an

(H

) an

d U

rban

(U

) Ter

rain

Sy

mb

ols

/Co

des

T

erra

in

Ca

teg

ory

IS-1

987

IS-2

01

1

AS

/NZ

S

AS

CE

*

SA

B

LA

B

SA

B

LA

B

SA

B

LA

B

SA

B

LA

B

)/

.(s

mV

o

S,H

,U

(sa

me

va

lue)

44

44

44

44

31

.42

31

.42

44

44

).(

mZ

2

40

24

0

24

0

24

0

24

0

24

0

14

4

14

4

)/

.(s

mV

z

S

H

U

40

36

31

40

36

31

40

35

31

40

35

31

40

37

34

40

37

34

41

39

32

41

39

32

zI

S

H

U

0.1

03

0.1

22

0.1

45

0.1

03

0.1

22

0.1

45

0.1

24

0.1

54

0.1

84

0.1

29

0.1

54

0.1

84

0.1

31

0.1

58

0.1

86

0.1

31

0.1

58

0.1

86

0.1

60

0.1

92

0.2

88

0.1

60

0.1

92

0.2

88

r

S

H

U

0.2

06

0.2

44

0.2

90

0.2

06

0.2

44

0.2

90

0.2

48

0.3

07

0.3

68

0.2

48

0.3

07

0.3

68

0.2

62

0.3

16

0.3

72

0.2

62

0.3

16

0.3

72

0.2

72

0.3

27

0.4

90

0.2

72

0.3

27

0.4

90

).(

mL

z

S

H

U

19

56

.0

18

57

.7

17

59

.0

19

56

.0

18

57

.7

17

59

.0

18

8.1

17

0.0

15

4.9

18

8.1

17

0.0

15

4.9

18

8.1

18

8.1

25

2.1

23

7.3

20

8.2

252

.1

237

.3

208

.2

B

S

H

U

0.5

6

0.5

4

0.5

4

0.5

7

0.5

5

0.5

4

0.5

9

0.5

7

0.5

5

0.6

0

0.5

8

0.5

6

0.5

9

0.6

0

0.7

7

0.7

6

0.7

5

0.7

8

0.7

7

0.7

6

E

S

H

U

0.1

32

0.1

28

0.1

17

0.1

16

0.1

11

0.1

07

0.1

08

0.1

05

0.1

03

0.0

96

0.0

94

0.0

92

0.1

07

0.1

02

0.0

96

0.0

96

0.0

91

0.0

86

0.1

32

0.1

33

0.1

28

0.1

21

0.1

22

0.1

17

S

S

H

U

0.1

48

0.1

28

0.1

08

0.1

64

0.1

48

0.1

32

0.1

17

0.0

98

0.0

84

0.1

45

0.1

25

0.1

09

0.1

17

0.1

06

0.0

95

0.1

45

0.1

33

0.1

21

0.0

87

0.0

80

0.0

58

0.0

85

0.0

79

0.0

61

R

S

H

U

1.3

0

1.0

9

0.8

4

1.2

7

1.0

9

0.9

4

0.8

4

0.6

9

0.5

8

0.9

3

0.7

0.6

7

0.8

3

0.7

2

0.6

9

0.9

3

0.8

1

0.7

0

0.8

0.8

4

0.7

1

0.8

3

0.8

0

0.6

9

g

g

f =4

.0

gf =

4.0

g

R=

3.5

6

gR=

3.6

1

gR=

3.0

2

gR=

3.0

8

gR=

3.7

27

gR=

3.7

7

gv=

4.0

g

v=

4.0

g

v=

3.7

g

v=

4.0

g

v=

3.4

0

gv=

3.4

0

G

S

H

U

2.1

2

2.2

5

2.3

6

2.1

1

2.2

2

2.4

1

2.2

2

2.4

6

2.7

0

2.2

6

2.5

2

2.7

7

2.0

4

2.2

1

2.3

7

2.0

8

2.2

6

2.4

3

1.9

7

2.1

5

2.5

8

1.9

6

2.1

4

2.5

9

G(C

om

pa

rin

g

wit

h I

S-8

75

-

19

87)

S

H

U

10

0%

10

0%

10

0%

10

0%

10

0%

10

0%

10

4.7

%

10

9.3

%

11

4.4

%

10

7.1

%

11

3.5

%

11

4.9

%

96

.2%

98

.2%

10

0%

98.6

%

101

.8%

10

0%

92

.9%

95

.6%

10

9.3

%

92

.9%

96

.4%

10

7.5

%


Tab

le 4

(C

on

tin

ued

)

Sy

mb

ols

/Co

des

T

erra

in

Ca

teg

ory

AIJ

B

S E

N

HK

N

BC

C

SA

B

LA

B

SA

B

LA

B

SA

B

LA

B

SA

B

LA

B

)/

.(s

mV

o

S,H

,U

(sa

me

valu

e)

31.5

3

1.5

3

1.5

31.5

2

9.93

29

.93

29.

93

29.

93

).(

mZ

2

40

240

144

144

2

40

240

2

40

24

0

)/

.(s

mV

z

S

H

U

47

41

34

47

41

34

41

34 -

41

34 -

43

43

- 44

38

- 44

38

zI

S

H

U

0.1

17

0.1

30

0.1

49

0.1

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it should be if we would have neglected risk coefficient during the experimental study. Further, this

represents the worst case for the study presented in this paper.

Although, the trend of values computed from different codes/standards are similar for both orientations in

different terrains but values vary due to different wind characteristics particularly their distinct wind velocity

profiles. For heavy suburban terrain, wind tunnel results show a different trend for GLF and peak

acceleration, when compared with other codes /standards.

From Figure 3, it is observed that the structural response for SAB orientation is around 3 times than LAB

orientation. Indian Standard (2011) gives a higher value of GLF than any other code/standard for all terrains

and both the orientations. The value of GLF in different codes/standards varies by -14% to+7% compared to

Indian Standard (1987) for suburban terrain, -18% to +14% for heavy suburban and -22% to +16% for urban

terrain. Least variation comes out for Indian Standard (2011) and the maximum variation for Hong-Kong

Code.

Value of peak acceleration according to Indian Standard (2011) is almost the same in heavy suburban and

urban terrain for SAB orientation. Higher value of turbulent intensity in urban terrain becomes the critical

factor instead of higher value of wind speed and resonant component of heavy suburban terrain.

It is interesting to note that the value of peak acceleration from the ASCE Standard for heavy suburban

terrain is higher than suburban for both the building orientations, which is not the trend followed by other

codes/standards. This is because resonant peak factor in ASCE Standard does not depend on terrain

roughness and there is lesser difference in design wind speed of suburban and heavy suburban terrain for this

standard.

BS EN, AIJ and ASCE Standards considered the effect of mode exponent, while computing the peak

acceleration. The value of non-dimensional coefficient Kx (depends on mode exponent, type of terrain and

effective height of building) in BS EN Standard is three times more than in ASCE Standard. The higher value

Kx in BS EN Standard appears the reason of greater value of acceleration in BS EN Standard than other

codes/standards except NBCC, for both the building orientations in different terrains.

Factor of 3.9 considered by NBCC (refer Table 3) while calculating the peak acceleration should be the

reason responsible for its highest value of peak acceleration as this factor for AIJ, ASCE and BS EN

Standards are 1, (0.85*3) and 3.0 respectively.

Base forces (shear and bending moment) increase with a decrease in the terrain roughness due to increase

in design wind speed (refer Table 4). For example, Japanese Code shows highest value of forces for both

building orientations in suburban terrain as the highest value of wind speed is used by this code (refer Table

3). Similarly, Canadian and Hong-Kong codes estimate higher value of forces for both orientations of

building in heavy suburban and urban terrains respectively.

Base bending moments vary within ±11% from average value for all codes/standards considered, for

suburban terrain and the variation is ±22.5% and ±18% for heavy suburban and urban terrain respectively,

for SAB orientation of building. These variations for respective terrains in LAB orientation of building are

±13.6%, ±27.75% and ±24.5%.

It may be seen that Hong-Kong Code gives the same value of GLF, forces and acceleration for all terrain

because of single general terrain category adopted by this code.


Figure 3.Varition of GLF, Peak Accelerations, Base Bending Moments and Shear Forces for Different Orientation

of Building in Different Terrain Roughness with Different Codes/Standards and

Wind Tunnel Data

Symboles : Urban Terrain Heavy Sub Urban Terrain Sub Urban Terrain

AS

CE

Exp

.

BS E

N

Peak Accelerations for LAB Oritentation

WindIS

198

7

IS 2

011

AS/N

ZS

AIJ

HK

NB

CC

Pe

ak

Acc

era

tio

ns

(% o

f g

)

7

6.5

6

5.5

5

4.5

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3.5

3

2.5

2

1.5

1

0.5

0

AS

CE

Exp

.

BS E

N

IS 1

987

IS 2

011

AS/N

ZS

AIJ

HK

NB

CC

Shear Forces for LAB Oritentation

Wind

Sh

ea

r F

orc

es

(KN

-m *

10

00

)

40

35

3

25

20

15

10

5

0

AS

CE

Exp

.

BS E

N

IS 1

987

IS 2

011

AS/N

ZS

AIJ

HK

NB

CC

Base Moments for LAB Oritentation

Wind

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

Ba

se M

om

en

ts (

KN

-m *

10

00

00

0)

AS

CE

Exp

.

Gust Factors for LAB Orientation

BS E

N

3

2.5

2

1.5

1

0.5

0

IS 1

987

IS 2

011

AS/N

ZS

AIJ

HK

NB

CC

Wind

AS

CE

Exp

.

Gust Factors for SAB Orientation

3

2.5

2

1.5

1

0.5

0

IS 1

987

IS 2

011

AS/N

ZS

AIJ

HK

NB

CC

BS E

N

Wind

Wind

7

6.5

6

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

AS

CE

Exp

.

IS 1

987

IS 2

011

AS/N

ZS

AIJ

HK

NB

CC

BS E

N

Pe

ak

Acc

era

tio

ns

(% o

f g

)

Peak Accelerations for SAB Oritentation

AS

CE

BS E

N

IS 1

987

IS 2

011

AS/N

ZS

NB

CC

5.5

5

4.5

4

3.5

3

2.5

2

1.5

1

0.5

0

Ba

se M

om

en

ts (

KN

-m *

10

00

00

0)

Base Moments for SAB Oritentation

Wind

Exp

.

AIJ

HK

Wind

AS

CE

Exp

.

BS E

N

IS 1

987

IS 2

011

AS/N

ZS

AIJ

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NB

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ea

r F

orc

es

(KN

-m *

10

00

)

40

35

3

25

20

15

10

5

0

Shear Forces for SAB Oritentation


The experimental results are showing more or less similar trend as by other codes/standards for all the

terrains and both the orientations of building for GLF, peak acceleration, shear force and base bending

moment. However, there is deviation in the trend for LAB orientation in heavy suburban terrain. The

experimental values for particular wind velocity are shown in Figure 3, although the experimental data are

collected for range of reduced velocities.

CONCLUSIONS

This paper presents a comparative study of parameters affecting along-wind response of a tall building

namely: gust loading factor, shear force, base bending moment and peak acceleration in major country

codes/standards. Two different building orientations: short after body and long after body for three different

terrain categories: suburban, heavy suburban and urban have been studied. Wind tunnel tests on an

aero-elastic model have also been conducted and the experimental results are presented along with values

from these codes/standards.

Main conclusions from this study are:

1) For a 3-second basic gust wind speed, mean wind loads estimated from each code/standard varied

significantly due to their distinct wind characteristics (V , IZ , r and LZ ). For example, value of

gust loading factor in different codes/standards varies up-to ±10% from Indian Standard (1987) for

suburban terrain, ±16% for heavy suburban and ±19% for urban terrain. Consequently there is

difference in shear forces and base bending moments

2) Heavy suburban terrain does not exist in Indian Standards [existing (1987) as well as proposed

(2011)] causing a large difference between forces and accelerations estimated for terrain category III

(α=0.18) and category IV (α=0.36). Thus, there appears to be a need for more refined terrain

category classification for Indian Standards.

3) Any parameter used in calculating gust factor that has a higher value than those with other codes

standards is generally compensated by other parameter in respective code at the end, resulting in

comparable values. For example, value of resonant response factor (R) for AIJ code is much higher

than any other code, but at the same time the value of peak factor (gf) is lower, resulting in a

comparable value of GLF.

4) In general, proposed Indian Standard (2011) is more accurate and refined than the earlier version i.e

1987 and is more direct than other codes/standards for estimating response parameters such as

acceleration and forces.

5) It is observed that with an increase in roughness the value of design wind velocity decreases and

turbulent intensity increases. Consequently, background and resonant factors decrease

but the peak factor value for resonant component increases, thus there is an increase in gust

loading factor.

6) Base forces (shear and bending moment) increase with decrease in the terrain roughness due to

increase in design wind velocity. Base bending moments vary ±11% from average value from all

codes/standards considered, for suburban terrain, and the variation is ±22.5% and ±18% for heavy

suburban and urban terrain respectively, for SAB orientation of building. These variations for

respective terrains in LAB orientation of building are ±13.6%, ±27.75% and ±24.5%.


7) The experimental results are showing more or less similar trend as by codes/standards for all

the terrains and both the orientations of building for GLF, peak acceleration, shear force and

base bending moment. However, there is deviation in the trend for LAB orientation in heavy

suburban terrain.

REFERENCES

1. Architectural Institute of Japan (AIJ-2004), “Recommendations for loads on buildings”, (in English

version).

2. ASCE, ‘’Minimum design loads for buildings and other structures’’, ASCE 7-98.

3. ASCE, ‘’Minimum design loads for buildings and other structures’’, ASCE 7-05.

4. AS/NZS: 1170.2:2002, Australian / New Zealand “Standard structural design actions”, Part 2- Wind

action.

5. AS/NZS: 1170.2 Supplement 1:2002, “Structural design actions”, Part 2-Wind action-Commentary

(Supplement to AS/NZS: 1170.2:2002).

6. Asawa, G. L., Pathak, S. K. and Ahuja, A. K. (1985), “Industrial wind tunnel at University of Roorkee”,

1st Asia-Pacific Symposium on Wind Engineering, Roorkee, India, 95-102.

7. BS EN 1991-1-4:2005, Euro code 1: ‘’Actions on structures-Part 1-4: Wind actions’’.

8. Bietry J., Sacre C. and Simiu E. (1978), “Mean wind profiles and changes of terrain roughness”,

Journal of Structural Division, ASCE, 104, (Oct. 1978), 665-673.

9. Cook, N.J. (1990) The Designer’s Guide to Wind Loading of Building Structures. Part 2 Static

Structures, London.

10. Davenport, A.G. (1967), “Gust loading factors,” Journal of Structure Division, ASCE

93(ST3) 11-34.

11. Durst C. S. (1960), “Wind speeds over short periods of time”, Meteor. Mag., 89, (1960), 181-186.

12. ESDU (1989), “Calculation methods for along-wind loading. Part 3: Response of buildings and

plate-like structures to atmospheric turbulence”, Item No. 88019, with amendments A & B, ESDU

International, London, March.

13. Ferraro, V., Irwin, P. A., and Stone, G. K. (1989). “Wind-induced building accelerations” Proceedings

of 6th U.S. National Conference on Wind Engineering, A. Kareem, ed., Univ. of Houston, Houston.

14. Gupta, A. (1996), “Wind tunnel studies on aerodynamic interference in tall rectangular buildings”,

Ph.D. Thesis, University of Roorkee, Roorkee, India.

15. Hajra, B. and Godbole, P. N. (2006). “Along wind load on tall buildings Indian codal provisions”

Proceedings of 3rd .National Conference on Wind Engineering, Jadavpur University, Kolkata, India,

January 5-7, 2006.

16. Holmes, J. D., Baker, C. J., English, E. C. and Choi, E. C. C. (2005), ‘’Wind structure and codification’’,

Wind & Structures, 8 (4), 235-250.

17. Holmes, J. D., Kasperski, M., Miller, C. A., Zuranski, J. A. and Choi, E. C. C. (2005), ‘’Extreme Wind

Prediction and Zoning’’, Wind & Structures, 8 (4), 269-281.

18. Holmes, J. D. (2007), “Wind Loading Structures”, 2nd Ed., Taylor and Francis, London and

New York.


19. Holmes, J. D., Tamura, Y. and Krishna, P. (2009), “Comparison of wind loads calculated by fifteen

different codes and standards, for low, medium and high-rise buildings”, Proceedings of 11th

American Conference on Wind Engineering, San-Juan, Puerto Rico, June 22-26, 2009.

20. Hong Kong (2004),”Code of practice on wind effects in Hong Kong”.

21. Indian Standards IS: 875-Part 3 (1987), “Code of practice for design wind loads (other than earthquake)

for buildings and structures”, Bureau of Indian Standards, New Delhi.

22. Indian Standards IS: 875-Part 3 (2011), “Code of practice for design wind loads (other than earthquake)

for buildings and structures”, Bureau of Indian Standards, New Delhi.

23. Isyumov, N. (1982), “The Aero-elastic Modelling of Tall Buildings”, Proceeding of International

Wind Symposium on Wind Tunnel Modelling, USA, pp 373-407.

24. Kasperski, M. (2006), “The new ISO-Approach for codification of wind loads”, Journal of Wind and

Engineering, Vol. 3, No. 1, pp 38-47.

25. Kasperski, M. and Geurts, Chris. (2005), ‘’Reliability and Code Level’’, Wind & Structures, 8 (4),

295-307.

26. Kijewski, T., and Kareem, A. (1998), ‘’Dynamic wind effects: A comparative study of provisions in

codes and standards with wind tunnel data’’, Wind & Structures, 1 (1), 77-109.

27. Kwok, K. C. S. (2007), “Codification of dynamic structural properties of buildings”, Journal of Wind

and Engineering, Vol. 4, No. 1, pp 1-5.

28. Lee, B. E., and Ng, W. K. (1988), ‘’Comparisons of estimated dynamic along-wind responses’’,

Journal of Wind. Engineering and Industrial Aerodynamics, Vol.30, pp 153-162.

29. Letchford, Chris, Holmes, J. D., Hoxey, Roger and Robertson, Adam (2005), ‘’Wind pressure

coefficients on low rise structures and codification’’, Wind & Structures, 8 (4), 283-294.

30. Loh, P., and Isyumov, N. (1985). “Overall wind loads on tall buildings and comparisons with code

values,” Proceedings of 5th U.S. National Conference on Wind Engineering, R. Dillingham and

K. Mehta, eds., Wind Engineering Research Council, Lubbock, Tex.

31. Mehta, K.C. (1998), “Wind load standards”. Proceedings, Jubileum Conference on Wind Effects on

Buildings and Structures, Porto Alegre, Brazil, 25–29 May.

32. Mendis, P., Ngo, T., Haritos, N., Hira, A., Samali, B. and Cheung, J. (2007), “Wind loading on tall

buildings”, EJSE especial issue: Loading on Structures, page 40-54.

33. NBCC. (1995), ‘’Commentary B-Wind Loads’’, User’s Guide-NBC 1995 Structural commentaries,

Canadian commission on building and fire codes, National Research Council of Canada, Ottawa, Part 4.

34. Niemann, H. J. (2008), “The European wind loading Standard: Provisions and their background”,

Journal of Wind and Engineering, Vol. 5, No. 2, pp 31-39.

35. Simiu, E. (1976), “Equivalent Static Wind Loads for Tall Building Design,” Journal of Structure

Division, ASCE, 102(4) 719-737.

36. Solari, G. (1982), “Along-wind response estimations, closed form solution,” Journal of Structure

Division, ASCE, 108(1) 225-244.

37. Solari, G. (1993a), “Gust buffeting. I: Peak wind velocity and equivalent pressure.” Journal of

Structure Engineering, 119 (2), 365–382.

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Wind. Engineering Industrial Aerodynamics, vol. 77 and 78, page 673–684.


39. Tamura, Y., Kareem, A., Solari, G., Kwok, C. S. K., Holmes, J. D. and Melbourne, W. H. (2005),

‘’Aspects of the dynamic wind-induced response of structures and codification’’, Wind & Structures,

8 (4), 251-268.

40. Tamura, Y., Holmes, J. D., Krishna, P. and Guo, L. (2009), “Comparison of wind loads on medium-rise

building by Asia-Pacific codes/standards”, Proceeding of APCWE VII, Taipei, Taiwan, Nov. 8-12,

2009.

41. Vellozzi, J. and Cohen, H. (1968), “Gust response factors,” Journal of Structure Division, ASCE,

97(6) 1295-1313.

42. Vickery, B. J. (1970), “On the reliability of gust loading factors”, Proceeding of Technical Meeting

Concerning Wind Loads on Buildings and Structures, Building Science Series 30, National Bureau of

Standards, Washington, D.C., 296–312.

43. Zhou, Y., Kijewski, T., ASCE, S. M. and Kareem, A. (2002), ‘’Along wind load effects on tall

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Journal of Wind and Engineering, Vol. 9, No. 1, January 2012, pp. 20-32

Tracer Gas dispersion in an Urban Environment:

Scaling Considerations in wind tunnel testing

Amit Gupta1, Ted Stathopoulos2

1Research Associate, 2Professor

Centre for Building Studies, Concordia University, Montreal, Quebec, Canada, H3G 1M8

ABSTRACT

Tracer gas experiments were carried out on a 3-storey building in the wake of a 12 storey building to

investigate the dispersion of emissions from rooftop stacks. The tests were later simulated in a wind tunnel

at two geometric scales. A 1:500 model correctly matched the boundary layer scale but had stack flows that

were laminar. A 1:200 model provided turbulent stack flows but was oversized with respect to the boundary

layer flow. The accuracy of the simulations varied with the location of the stack and the receptor. Concentration

values obtained with the 1:500 model generally showed better agreement with the field data than the 1:200

results.

Key words : Building wake, full-scale tests, wind tunnel, dispersion, tracer gas

INTRODUCTION

Prediction of the dispersion of plumes emitted from rooftop stacks is often necessary to avoid potential

contamination of fresh air intakes of the emitting building or adjacent buildings. Dispersion

models that predict nearfield concentrations are available for simple building geometries ASHRAE (2003).

Flow around buildings is complicated Ahuja (2005). Thus, these models are not applicable in many cases

such as a low emitting building in the near-wake of a taller building. Addition on rooftop structures such as

penthouses or skylights further complicated the flow on building roofs, Amit et al. (2012a, 2012b). In

complex flow situations, fluid modeling using a wind tunnel or water channel provides the only practical

method for simulating the dispersion of building exhaust.

In some cases, relaxation of simulation criteria may be necessary due to various constraints. For example,

correct simulation requires that the scale of building models match the scale of the boundary layer flow.

However, in some cases a reduction in model size may be required to reduce wind tunnel blockage. On the

other hand, situations involving small full-scale buildings may require oversized models in order to

satisfy Reynolds Number criteria.

The effect of mismatching the model and boundary layer scales has not been studied extensively with

respect to dispersion modeling. Wilson has suggested that model results obtained for a given model building

are applicable to a range of full-scale building heights from one-half to twice that of the model building as

indicated by Wilson et al (1998). This assumption implies that the dimensions of the building wake and other

separated flow regions are not significantly affected by changes in the properties of the approaching flow

(e.g. turbulence intensity, turbulence scale). However, wind engineering studies have shown that the mis-

match of model and boundary layer scales can significantly affect the wind loads on the model building. Roy

and Holmes (1988) showed that the force coefficients may be significantly underestimated

when measurements are obtained with a model that is twice the correct size.

Journal of Wind and Engineering, Vol. 9, No. 1, January 2012, pp. 20-32 21

In the present study, concentration measurements have been obtained with a 1:500 scale model correctly

matched to the wind tunnel boundary layer but with a stack exhaust that was not turbulent.

Measurements were also obtained using a 1:200 scale model that was too large with respect to the boundary

layer flow. The tests were performed for the case of a tall building upwind of a low emitting building.

MODELING CRITERIA

The following criteria are generally considered to be sufficient for wind tunnel modeling of

dispersion of non-buoyant exhaust in a neutral atmosphere [ASHRAE (2001)]:

Similarity of wind tunnel boundary layer with the atmospheric surface layer (mean velocity

profile, turbulence intensity, turbulence scale)

Geometric similarity between model and full-scale

Building Reynolds number (Reb = U

HW

b/ν) should exceed 11,000

Stack Reynolds number (Res = w

ed

s/ν ) should exceed 2000 to ensure turbulent exhaust flow,

Stack momentum ratio (M = we/U

H) of the model should be equivalent to the full-scale value.

where we is the exhaust velocity, U

H is the wind speed at building height, ν is the kinematic viscosity of

air, Wb is the nominal building dimension and d

s is the stack diameter.

The wind tunnel used in the present study has a boundary layer scale of approximately 1:500. Thus, building

models constructed at a scale of 1:500 provide the most accurate simulation of the separated flow regions

around the buildings, as long as the building Reynolds No. criterion is satisfied. It is very important to

achieve correct turbulence in simulated flows. Vortex generators play an important role in controlling the

turbulence in wind tunnel flows. Further information on vortex generators can be found in Rajan et al.

(2009).

However, a potential disadvantage of a 1:500 model is the difficulty in achieving turbulent flow in the model

stack due to its small diameter. In the present study, the 1:500 model stack had a diameter of only 0.8 mm.

Consequently, values of Res were well below the minimum specified value of 2000, indicating the exhaust

flow was laminar. Wilson et al. (1998) suggest that the effect of a laminar velocity profile on the exhaust

momentum can be compensated for by adjusting the model values of exhaust momentum ratio, M = we/U

H,

to obtain the full-scale equivalent value by using the expression shown in equation (1)

Mfull-scale

= 1.414Mmodel

(1)

where:

Mfull-scale

= Exhaust momentum ratio at full scale

Mmodel

= Exhaust momentum ratio at model scale

In order to avoid difficulties associated with Res, experiments were also performed at a scale of 1:200. For

these tests, Res varied from 1960 to 4480 and thus the exhaust flow was either fully turbulent or was

approaching turbulent flow. The disadvantage of the 1:200 model is that it was oversized with respect to

boundary layer flow. Consequently the turbulence intensity and scale of the approaching flow were less than

those for the 1:500 model.

EXPERIMENTAL PROCEDURE

Full-scale experiments

Full-scale experiments were performed on the roof of the 3-storey Building Engineering (BE) building

located in downtown Montreal on the campus of Concordia University. The building is surrounded by

buildings varying in height from 3 storeys to 15 storeys.

The purpose of the study was to investigate the dispersion of plumes from rooftop stacks for various stack

locations, stack heights and exhaust velocities. In the present study, results are presented for tests carried out

for nominally southwesterly winds. For this wind direction, the BE building was in the wake of the

12-storey Faubourg building (FB), as shown in Figure 1.

22 Tracer Gas dispersion in an Urban Environment:Scaling Considerations in wind tunnel testing

Figure 1: Location pf samples used in all field and wind tunnel experiments


Wind speed (UFB

), wind direction (θ) and turbulence parameters (σu, σθ) were obtained with a Young

anemometer placed on a 5 m mast on the roof of the FB building (height above ground was 55 m.). Wind

data and stack parameters for six field tests are shown in Table 1. Also shown are corresponding data for the

1:500 and 1:200 wind tunnel simulations. The reference wind speed varied between 4.1 m s-1 and 7.2 m s-1.

The details of the field test setup, location of samplers, location of anemometer and stacks are shown in

Figures 1 and 2 and detailed specifications of test parameters and atmospheric conditions are shown in Table 2.

Sulfur hexafluoride (SF6) was released from a 0.4 m diameter stack on the roof of the BE building. The stack

and the attached blower can be positioned at different locations. In the present study, locations near the

upwind building (SL3) and near the center of the roof (SL4) were chosen. The height of the stack was either

1m or 3m in the different tests. The influence of exhaust momentum on concentration profiles was

investigated by conducting tests at two exhaust speeds (we~7.5 m s-1, w

e~17.5 m s-1)

Air samples were collected using 15 automated samplers containing 10 sample bags. Twelve samplers were

placed on the roof of the BE building. The remaining three samplers were placed at the leeward edge of the

FB roof and collected samples at the top of the wall (approximately 2 m below the roof edge). The sampling

period for each bag was 5 minutes and thus, the total duration of a test was 50 minutes. Usually, two tests

were carried out per day.

In addition to the 10-bag samplers, a multi-syringe pump was used to obtain samples at different heights on

the leeward wall of the FB building. Using this method, only five 5-minute samples could be obtained

during each 50 minute test.

Figure 2: Elevation view of BE and Faubourg buildings

Faubourg Bldg. .

BE Bldg .

BE Bldg.

Anemometer

SL3 SL4

H= 50 m

U

51m

x

32m

Table 1 Exhaust and meteorological parameters for tests at full scale and different scales with taller building (FB)

present upstream of smaller (BE) emitting building

Full scale

Test date Stack

location

Wind dir.

(θ0)

Stack height

(m)

Wind speed at FB

bldg. ht. UFB(m/s)

Momentum

ratio (M)

Stack Reynolds

number (Re)

Aug-12 SL3 214 - 231 1 5.7 4.2 - 6.1 480000

Aug-12 SL3 208 - 231 1 5.9 1.9 -2.9 234667

Aug-26 SL3 204 - 229 3 7.2 1.4 - 2.3 205333

Aug-26 SL3 215 - 230 3 7.0 3.5 -5.3 472000

Oct-01 SL4 215 - 227 1 5.7 1.6 -2.6 194667

Oct-01 SL4 217- 236 1 6.8 3.1- 4.5 437333

1:200 model

Test date Stack

location

Wind dir.

(θ0)

Stack height

(m)

Wind speed at FB

bldg. ht. UFB(m/s)

Momentum

ratio (M)

Stack Reynolds

number (Re)

Aug-12 SL3 200 - 230 1 10.5 5.0 4480

Aug-12 SL3 200 - 230 1 10.5 2.2 1960

Aug-26 SL3 200 - 230 3 10.5 2.2 1960

Aug-26 SL3 200 - 230 3 10.5 4.5 4060

Oct-01 SL4 200 - 230 1 10.5 2.2 1960

Oct-01 SL4 200 - 230 1 10.5 3.5 2940

1:500 model

Test date Stack

location

Wind dir.

(θ0)

Stack height

(m)

Wind speed at FB

bldg. ht. UFB(m/s)

Momentum

ratio (M)*

Stack Reynolds

number (Re)

Aug-12 SL3 220 1 8.0 3.5 302

Aug-12 SL3 220 1 8.0 1.6 687

Aug-26 SL3 220 3 8.0 1.2 233

Aug-26 SL3 220 3 8.0 2.8 549

Oct-01 SL4 220 1 8.0 1.4 275

Oct-01 SL4 220 1 8.0 2.6 508

* Corrected for laminar flow, from [2]

Table 2 Experimental parameters for tests with Faubourg building upstream of BE building

Parameters Field Wind Tunnel

m

1:200 model scale

Wind Tunnelm

1:500 model scale

Zref (m) 120e , 300

e 0.6 0.6

Uref (m/s) 5.2 – 9e 12.5 13.0

UFB (m/s)b 4.1 - 7.0

m 10.5 8.0

Zo (m) 0.5 - 1.5c 0.66 1.65

Lx (m) 100e 0.4 0.4

σu/U(FB) 0.25 - 0.36m 0.12 - 0.13 0.19 - 0.20

Res 194500 – 480000m

1960 - 5000 233 - 508

ds (mm) 400 2.0 0.80

a UBE (m/s) is measured at 15 m (full scale height) from ground level using power law

b UFB (m/s) is measured at 55 m (full scale height) from ground level

c From Wieringa (1993)

e Estimated

m Measured


Wind tunnel experimental setup

Wind tunnel experiments were carried out in the boundary layer wind tunnel at Concordia University. The

wind tunnel working section is 1.8 m by 1.8 m and the length is 12.2 m. Models of the BE and FB buildings

and their surroundings were constructed at scales of 1:200 and 1:500. A certified mixture of nitrogen and

SF6 was emitted from the stack and the mean concentration of SF

6 was measured at various receptor

locations on the BE roof and the FB wall. A multi-syringe pump was used to obtain samples via plastic tubes.

A sampling time of 1 minute was used.

Figure 3 shows profiles of mean velocity and turbulence intensity (σu/U) measured in the wind tunnel

corresponding to the 1:500 and 1:200 models. Turbulence intensity data obtained by Engineering Sciences

Data Unit (ESDU 1985) and full-scale data from the present study are also shown. The mean velocity profile

had a power law exponent (α) of 0.3, indicating an urban or heavy suburban terrain. At the height of the

reference anemometer (55 m), the wind tunnel value of σu/U was only 0.13 - less than 50% of the mean

full-scale value. In contrast, σu/U at the reference height was 0.2 for the 1:500 model. Although this value

is below the ESDU and full-scale values, the 1:500 model more closely matched the boundary layer scale

than the 1:200 model.

An important parameter for modeling the dispersion of stack emissions is the exhaust momentum ratio,

M = we/U

h, where we is the exhaust velocity and U

h is the wind speed at the height of the BE building. In the

present study, Uh in the field and wind tunnel tests was determined using the power law with α = 0.3 to adjust

the wind speed obtained by the FB anemometer.

Concentration data are expressed in terms of the non-dimensional concentration coefficient, K, which is

defined as:

K = CUhH2(10-6)/Q

SF6(2)

Where:

C = Concentration in ppb

QSF6

= Emission rate of SF6 in m3s-1.


RESULTS AND DISCUSSION

Field data overview

Figure 4 shows the effect of M on mean values of K obtained on the BE roof and the top of the FB wall.

These results were obtained on Aug-26, 2002 with a 3 m stack at SL3. The exhaust velocity was 7.5 ms-1 in

the first test and approximately 17.5 ms-1 in the second test.

0

50

100

150

200

250

300

0 0.2 0.4 0.6 0.8 1

U/Uref

Zfu

ll s

ca

le

(m)

V elocity prof ile at 1:500 scale

BE anemometer ht .

FB anemometer ht .

0

50

100

150

200

250

300

0 0.1 0.2 0.3 0.4

Zfu

ll s

ca

le (

m)

Turbulence intensity at

1:500 scale: Zo = 1.6 m

TI ≈ 0.20

Field TI bound

≈ 0.25 - 0.36

0

50

100

150

200

250

300

0 0.2 0.4 0.6 0.8 1

U/Uref

Zfu

ll s

ca

le

(m)

V elocity prof ile at 1:200 scale

BE anemometer ht .

FB anemometer ht .

0

50

100

150

200

250

300

0 0.1 0.2 0.3 0.4

Zfu

ll s

cale

(m

)

Turbulence intensity at

1:200 scale: Zo = 0.66 m

TI ≈ 0.13Field TI bound

≈ 0.25 - 0.36

σu/U

α = 0.30 ESDU (1985)

bounds: (Z0 = 0.7m)

α = 0.30

σu/U

a)

b)

ESDU (1985)

bounds: (Z0 = 0.7m)

Figure 3 : Mean velocity and turbulence profit a) model scale - 1:500 and b) model scale - 1:200


54 21

The K values shown in Figure 4 are typical of all field tests performed when the FB building was directly

upwind of the BE building. For the low M case (M = 1.7) maximum K values were obtained at BE roof

samplers close to the stack and the next highest K values occurred at the top of the FB leeward wall.

Concentrations were relatively low at the remaining BE roof samplers. A larger M value for the second test

(M = 3.9) reduced K near the stack by more than a factor of three. At most of the remaining BE samplers, K

values for M = 3.9 were only 20% to 30% lower than the low M values. Similar reductions occurred at the

top of the FB wall.

Figure 5 shows the variation of K with time at the three FB wall samplers for the first Aug. 26-02 test

(M = 1.7) field test. High correlation between the samplers is evident. The time series also indicate K

increased significantly from the beginning of the test to the end. The average K value for the three samplers

at T = 5 min was 150. For the last 3 sample periods (40<T<50), the average value of K was approximately

500.

Figure 4 : Comparison of field K for Aug. 26-02 field tests for low and high exhaust momentum


The trend indicated in Figure 5 may be due to an increase in wind speed during the test. Figure 6 shows that

the 5 min wind speed measured by the FB anemometer increased from 5.2 ms-1 at T = 5 min to 8.5 ms-1 at

T = 50 min. Wind direction changes may have also affected the data. However, in this case, ? was relatively

constant at 219º ± 10º, see Figure 6.

Figure 7 shows time series of K obtained at 3 BE roof samplers located near the stack (R4), near the middle

of the roof (R18) and on the roof of the penthouse (P2) on the leeward side of the building. Like the FB data,

K values obtained at these samplers increased during the test.

Figure 7: Concentration K time series for near (R4), mid (R18) and far (P2) sampler on BE roof for

low M - [Aug. 26-02-field test: Stack location 3]

1

10

100

1000

10000

0 10 20 30 40 50 60

Sam pling tim e (m in)

k

S# R4_M=1.7

S# R18_M=1.7

S# P2_M=1.7

Hs = 3m

Figure 5 : Concentration K time series for samplers on FB wall, Aug. 26-20 field test : Stack location 3

Figure 6 : Wind direction and wind speed variation with time for Aug. 26-02 hour 1

10

100

1000

0 10 20 30 40 50

Sampling time (min)

k

S# FB1_M=1.7

S# FB2_M=1.7

S# FB3_M=1.7

Hr-1

hs = 3m

200

220

240

0 5 10 15 20 25 30 35 40 45 50

Time (min.)

Win

d d

ire

cti

on

4

6

8

10

0 5 10 15 20 25 30 35 40 45 50

Time (min.)

Win

d s

pe

ed

(m

/s)


Wind tunnel and field data comparsion

Figure 8a shows the variation of K with height on the FB wall for the first Aug 26 test (SL3, hs = 3 m, M

avg

= 1.7) and the corresponding wind tunnel tests performed using the 1:500 model and the 1:200 model. The

wind tunnel experiments were conducted using the average M-value for the field tests. As discussed

previously, the actual M value used for the 1:500 test was reduced from 1.7 to 1.2 to correct for the laminar

stack flow.

Regarding the field data, note that the range of 5-minute K values is shown along with the 50-minute mean

at each height. During each field test, 10 samples were generally obtained at the maximum height

(z = 0.85Hb) and 5 samples were obtained at the remaining heights.

The results clearly show that for this stack location, the 1:200 model, mismatched to the wind tunnel

boundary layer flow, produced significantly higher concentrations than the field values. The 1:200 K values

were at least a factor of 3 times the mean field value at each height. The 1:200 values are also well outside

the maximum K observed in the field test.

The 1:500 model, which approximately matches the scale of the wind tunnel boundary layer flow, produced

reasonable agreement with the field values on the upper part of the wall (z > 0.6Hb). However, at lower

heights, wind tunnel K values fall outside the band of field data. At the lowest measurement height

(z = 0.27Hb), the wind tunnel K value is less than 5% of the mean field value.

Figure 8b shows data for the SL3 stack obtained with a moderately high M (field Mavg

= 3.9). Comparison

with the low M data of Figure 8a shows that increasing M tends to reduce the maximum K values measured

on the wall. As with the low M test, the 1:200 model greatly overestimated the field data while the 1:500

model produced good agreement except at the lowest height.

The discrepancy between the 1:200 wall profile and field result may be due to the low turbulence intensity in

the wind tunnel compared to field value. As discussed in Hosker (1987), the level of turbulence in the

incident flow can have a significant effect on the size of the near wake. High turbulence causes shear layer

separating from the leading edges of a building to reattach to side walls, resulting in a reduction of wake size.

Thus, flow reattachment may have occurred on the FB side walls in the field tests but may have been absent

in the 1:200 wind tunnel tests.

Data obtained with a 1 m stack in the middle of the roof (SL4) for an average field M of 2.0 and 3.5 are

shown in Figures 8c and 8d respectively. For this stack location, the 1:200 model provides relatively good

agreement with the field data. Although the 1:200 data exceed the 50-min mean field values, the wind tunnel

data fall within the range of the 5-minute field samples at most heights. On the other hand, the 1:500 model

provides good agreement only at the sampler at the top of the FB wall. As z decreases, the wind tunnel K

decreases significantly while the field values show little variation with height. The reason for the large drop

in K as z decreases in the wind tunnel is not clear. Similar variation of concentration with height is evident

in the water channel results of Wilson et al. (1988) In that study, in which the upwind building height was

twice the height of the emitting building, maximum concentration near the top of the wall was

approximately five times the minimum value near the base for a wide range of M values. It is not clear why

the accuracy of the two wind tunnel simulations appear to vary with stack location. It may be associated with

the effect of incident turbulence on the flow in the near wake.

Figures 9a - 9b and 9c - 9d show K values obtained on the BE roof for stack locations SL3 and SL4,

respectively. The graphs show the variation of K with x/L, where x is the distance from the windward edge


and L is the length of the building. For each stack location, results are presented for low and moderate M

values. The stack height was 1 m in each case. Note that the field curves show the mean K values for each

50-minute test. The hatched region indicates the scatter of the 5-minute samples.

In general, the 1:500 model results compared well with the field data. At SL3, the wind tunnel K values were

within 25% of the mean field values. At SL4, larger discrepancies are evident. However, the data are

generally within a factor of two of the field values.

As with the FB wall results, roof concentrations obtained with the 1:200 model were less accurate than those

obtained with the 1:500 model when the stack was located at SL3. For this stack location, 1:200 model

significantly underestimated the maximum K value, which occurred near the stack. However reasonable

agreement with the field values was obtained at downwind locations ( x/L > 0.5). Results obtained with the

1:200 model for the centre roof stack (SL 4) were generally similar to the 1:500 data. For the low M case, the

maximum mean field concentration exceeded the 1:500 K value by a factor of two and the 1:200 K by a

factor of three. However, at the windward and leeward edges of the roof, both wind tunnel simulations

showed good agreement with the field data.

Figure 8 : Variation of K with height on FB wall for stack locations 3 and 4

L

U

L

Data plane

z H

L

X

U

X

L

Data plane

z H

0

0.25

0.5

0.75

1

0 200 400 600 800 1000 1200

k

Z/H

b

Field, M = 1.6-2.6

WT-1:200, M = 2.0

WT-1:500, M = 1.4

hs = 1m

0

0.25

0.5

0.75

1

0 200 400 600 800 1000 1200

k

Z/H

b

Field, M = 3.1-4.5

WT-1:200, M = 3.5

WT-1:500, M = 2.6

hs = 1m

0

0.25

0.5

0.75

1

0 200 400 600 800 1000 1200

k

Z/H

b

Field, M = 1.4-2.3

WT_1:200, M = 1.7

WT-1:500, M = 1.2

hs = 3m

0

0.25

0.5

0.75

1

0 200 400 600 800 1000 1200

k

Z/H

b

Field, M = 3.1-5.3

WT-1:200, M = 4

WT-1:500, M = 2.8

hs = 3m

Field maximum and

minimum bounds

a) c)

b) d)


For the moderate M case, (M = 3.5) shown in figure 9d, the 1:500 and 1:200 simulations produced generally

similar results. The wind tunnel K values were within the range of the 5-minute field values near the stack.

However, at the windward edge of the building, both simulations overestimated the mean field value by

approximately 70%.

CONCLUSIONS

The dispersion of emissions from a low-rise building downwind of a taller building was investigated using

field tests and wind tunnel experiments performed at model scales of 1:500 and 1:200. The 1:500 model

matched the scale of boundary layer flow but had laminar stack flows. The 1:200 model provided turbulent

stack flows but was oversized with respect to the boundary layer.

In both the field and wind tunnel tests, high concentrations were measured at the top of the leeward wall of

the upwind building and near the stack on the emitting building. The accuracy of the wind tunnel simulations

varied with stack and receptor location.

Concentration data obtained with 1:500 model generally showed better agreement with the field data than

the 1:200 data. This suggests that the turbulent properties of the approaching flow are important for proper

modelling of plume dispersion in the near wake of a building. On the other hand, the existence of laminar

flow in model stacks may not produce significant errors for emission sources located in building wakes.

Figure 9 : Variation of plume centerline K with distance on BE roof for Stack locations 3 and 4

0

1000

2000

3000

0 0.2 0.4 0.6 0.8 1

x/L

k

Field, M = 1.9-2.9

WT-1:200, M = 2.2

WT-1:500, M = 1.1

Stack

location

hs = 1m

0

300

600

900

1200

0 0.2 0.4 0.6 0.8 1

x/L

k

Field, M =4.2-6.1

WT-1:200, M = 5

WT-1:500, M = 3.5

Stack

location

hs = 1m

0

1000

2000

3000

4000

5000

0 0.2 0.4 0.6 0.8 1

x/L

k

Field, M = 1.6-2.6

WT-1:200, M = 2.2

WT-1:500, M = 1.5

Stack

location

hs = 1m

0

300

600

900

1200

0 0.2 0.4 0.6 0.8 1

x/L

kField, M = 3.1-4.5

WT-1:200, M = 3.5

WT-1:500, M = 2.5

Stack

locationhs = 1m

L

X

U

X

L

Data plane z

H

L

X

U

X

L

zH

Data plane Field maximum and

minimum bounds

g p

a) c)

b) d)


REFERENCES

1. Ahuja A K, Dalui S K, Ahuja R , Gupta V K (2005), Effect of interference on the wind environment

around high-rise buildings Journal of Wind & Engineering V2 - 1, pp 1-8.

2. ASHRAE Applications Handbook, Chapter 16, American Society of Heating, Refrig. and Air-Cond.

Eng., Inc., Atlanta, 2001.

3. ASHRAE Applications Handbook, Chapter 44, American Society of Heating Refrigerating and Air

conditioning Engineers, Atlanta, 2003.

4. Bahloul A., Stathopoulos T. Hajra B, Gupta A., (2008), "A Comparative study of ADMS, ASHRAE

and Wind Tunnel Simulation for Rooftop dispersion of airborne pollutants", Proceedings of 11th Inter

national Conference on Indoor Air Quality and Climate, Technical University of Denmark, Denmark,

August 17-22.

5. Engineering Sciences Data Unit: 1985; Data Item 85020, ESDU International Ltd., London.

6. Erwin W James, Chowdhury Arindam Gan, Bitsuamlak Girma (2011), Wind loads on rooftop

equipment mounted on a flat roof Journal of Wind & Engineering V 8-1, pp 23-42.

7. Gupta A., Saathoff P., Stathopoulos T. (2012A) - Evaluation of ASHRAE dispersion models for

building exhaust dispersion. ASHRAE Transactions.

8. Gupta A., Saathoff P., Stathopoulos T. (2012B) - Wind tunnel investigation of the downwash effect of

rooftop structure on plume dispersion Journal of Atmospheric Environment 2011.

9. Gupta A., Saathoff P., Stathopoulos T., (2005), "Effect of building orientation on downwash due to

rooftop structures", International Workshop on Physical Modeling of Flow and Dispersion

Phenomena, University of Western Ontario, London, Ontario, Canada, August 24-27.

10. Gupta A., Saathoff P., Stathopoulos T., (2007), "Downwash effect of rooftop structures", International

Workshop on Physical Modeling of Flow and Dispersion Phenomena, University of Orleans, France,

August 29-31.

11. Hosker; Atmospheric Science and Power Production. D. Randerson. Ed., U.S. Dept. of energy D.O.E.

TIC-27601, 1984, pp 241 - 326.

12. Leitl Bernd (2008), Quality assurance of urban flow and dispersion models - New challenges and data

requirements. Journal of Wind & Engineering V5-2 pp: 60-73.

13. Rajan S Selvi, Lakshmanan N , Arunachalam S , Babu G Ramesh (2009), Simulation studies on design

of vortex generators for boundary layer wind tunnel Journal of Wind & Engineering V 6-2, pp 19-29.

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pp-343-353.

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17. Wilson, D.J, Fabris, I., Chen, J., ckerman M. ASHRAE Research Report 897; American Society of

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Journal of Wind and Engineering, Vol. 9, No. 1, January 2012, pp. 33-53

ABSTRACT

This paper presents a comparative study of different wind characteristics pertaining to dynamic wind load for

three terrain categories namely: sub-urban, heavy sub-urban and urban as given in different international

wind codes and standards. The different codes used in the present study include Japanese, Australia/

New-Zealand, American, British/European, Canadian, Hong-Kong, Chinese and Indian [existing (1987) as

well as proposed (2011)]. Experimental results for above terrain categories are also compared with different

standards and available literature. Wind characteristics include mean wind velocity, turbulent intensity

profiles, integral length scale of turbulence and power spectral density. The differences in various codes

standards for the above parameters have been discussed with reasons.

Key words: Wind characteristics, Wind codes and standards, Terrain categories, Velocity profile.

NOTATION

H Height of building (m) x Reduced frequency

b Width of building (m) R Roughness factor

d Depth/length of building (m) n, f Eddy frequency

u Mean wind velocity at height z vo

Basic wind velocity (m/s)

u* Shear velocity LZ Turbulent length scale at any height (m)

ug

Mean wind velocity at gradient height VZ Hourly mean wind velocity (m/s)

α Power law index na

First mode frequency of building (Hz)

β Critical damping ratio LH

Turbulent length scale at building height (m)

ρair

Density of air N Effective reduced frequency

φ Factor to account for second order turbulent

intensity

G Gust factor CeH

Exposure factor

ZeZ ,. Reference height (m) VD/ V

aUp-crossing frequency (Hz)

zo

Roughness length (m) K A factor related to surface roughness coefficient

of the terrain

T Averaging time σu

Standard deviation (σ) of fluctuating wind

velocity component in longitudinal direction

IZ Turbulent intensity at height Z xLu

length scale of turbulence in longitudinal

wind direction

z Height above ground level Su

Power spectral density function

zg

Gradient height k2

Terrain, height factor

B, b1, b

2Constants

Comparison of Codal Values and Experimental Data Pertaining to

Dynamic Wind Characteristics

Nikhil Agrawal1, V. K. Gupta2, Amit Gupta3, Achal Mittal4

1Research Scholar, Department of Civil Engineering, IIT Roorkee ([email protected])2 Professor, Department of Civil Engineering, IIT Roorkee ([email protected])

3 Structural and Wind Engineering Consultant, Roorkee ([email protected])4 Principal Scientist, Structural Engineering Group, CSIR-CBRI Roorkee ([email protected])

Usual meaning of notation unless/otherwise mentioned in the text

INTRODUCTION

Wind loads are the typical dynamic loads on buildings and the wind-induced effects on buildings are deter-

mined by wind characteristics, aerodynamic and dynamic properties. The approaching wind

characteristics are largely controlled by the roughness of the upwind fetch over which it blows (assuming

that the fetch is relatively flat). The ways in which characteristics of the approaching wind are incorporated

by various wind codes and standards are very different.

Several studies have been carried out in past that focus on the comparison of wind loads and

corresponding building responses, estimated with different codes and standards. Limited information is avail-

able on comparison of wind characteristics. A few relevant studies are presented in the following text.

Zhou et. al. (2002) presented a comparative study on maximum wind load effects in the along wind direction

for open and urban terrains, highlighting that each code and standard employs unique definitions of wind field

characteristics such as mean velocity profile, turbulent intensity profile, wind spectra,

turbulence length scale and wind correlation, which may lead to significant variations in estimating Gust

loading factor, mean wind loads. Correspondingly these parameters lead to significant variation in the

estimates of the equivalent static wind load and associated wind-induced load effects. Different mathematical

forms and properties of wind spectra for along wind response have been discussed in detail by Tamura et. al.

(2005). Spectral densities used in various wind codes and standards are tabulated, apart from a comparison

of gust loading factors. The authors reviewed the wind induced response of building using major codes and

standards, and also discussed the combined effects of along wind, across-wind and torsional wind load

components along with dynamic characteristics of building.

Emphasis on the topics of terrain and exposure, shielding and amplification, topographic effects, tropical

cyclone and hurricane wind have been given for their codification in wind loading codes and

standards by Holmes et.al. (2005). Different laws for velocity-height profile, turbulence profile have been

discussed in detail and comparison of codal provisions on terrain-height profile has also been presented.

Choi (2009) discussed the roughness classification, terrain category and wind profiles in different wind codes.

In addition, a set of terrain categories and corresponding wind profiles were proposed. Some

inconsistencies in the way that terrain categories are specified in various codes have been pointed out.

Pictorial presentation of the terrain categories for physical understanding of these has been presented.

Lee and Ng (1988) and Kikitsu et. al. (2003) compared international building codes for dynamic along wind

response and peak pressure coefficients. Inconsistencies have been observed among codes due to differ-

ences in the different wind parameters. Kijewski and Kareem (1998) carried out a comparative study of

provisions given in different wind codes and standards for along-wind, across-wind and torsional responses

for a given building.

Although sufficient work has been carried out on codes and standards but a comprehensive

review of different wind characteristics, particularly for rough terrains has not been carried out in the past.

The Codes and Standard considered are:

Architectural Institute of Japan (AIJ-2004) Recommendations for Loads on Buildings.

Minimum Design Loads for Buildings and Other Structures (ASCE 7-05).

34 Comparison of Codal Values and Experimental Data Pertaining to Dynamic Wind Characteristics


Australian Standard: Minimum Design Loads on Structures (AN/NZS 1172.2:2002).

National Building Code of Canada (NBCC-1995).

British/European Standard: Euro-code 1: Actions on Structures (BS EN 1991-1-4:2005).

Code of Practice on Wind Effects in Hong-Kong (CPWEHK-2004).

Code of Practice for Design Loads for Buildings and Structures IS: 875(Part-3)-1987 (Existing).

Code of Practice for Design Loads for Buildings and Structures IS: 875(Part-3)-2011 (Proposed).

China National Standard (GB50009-2001).

A comparison of formulation for wind characteristics in wind codes and standards for different terrain

categories is presented in this study. The following sections will first review the basic wind

characteristics such as the mean wind velocity profile, turbulent intensity profile, integral length scale of

turbulence and power spectral density and then present a comparative study of these characteristics for tall

buildings located in rough (sub-urban, heavy sub-urban and urban) terrains based on different wind loading

codes and standards. The results of experimental programme have been presented along with the codal

values.

MEAN WIND VELOCITY PROFILES

Conventionally, the first representation of the mean wind profile in horizontal homogeneous terrain has been

the power law, given in equation (1),

(1)

where α is the power law exponent, u is the mean wind velocity at a height z above ground level, and

subscript ref indicates a condition of reference height (usually taken as 10 meters).

Value of α generally varies from 0.10 in coastal area (open) to 0.37 in city centre (very rough terrain)

locations. The advantage of such an approach lies in its simplicity and usability. However, it has a drawback

that it does not work near to the ground surface as the gradient of the curve is infinite as z approaches zero.

Consequently, it provides a poor fit to experimental data near to the ground surface. Nonetheless its use

continues in a significant number of international codes and standards, where the reference height is

generally taken as the gradient height (zg). At gradient height the movement of air is no longer affected by

ground roughness. Here α and zg both depends on terrain roughness and on the averaging time used in the

calculation of wind speed.

Due to above limitation, some codes (refer Table 1) have adopted the logarithmic velocity profile (eq.2),

(2)

where u* is the shear velocity , τ is the shear stress at ground level, ρ is air density, κ is Von Karman

constant approximately equal to 0.4, and zo is the surface roughness length which varies with the type of

terrain. When expressed in terms of reference velocity and reference height, it becomes (eq. 3)

α

=

refref z

z

u

u

=

=

oo z

zu

z

zuu ln*5.2ln

*

κ

ρτ

(3)

This approach has the advantage of having better theoretical background comes from classical boundary

layer theory and provides better approximation close to ground level. It is valid in the bottom of 20 to 30 %

of the boundary layer, Stathopoulos (2007). However, this approach gives a poor fit to experimental data for

heights greater than 30 to 50 m, Holmes et. al. (2005).

For avoiding this, a number of codes and standards (refer Table 1) have adopted the logarithmic format but

with additional linear and non-linear terms. Perhaps the most sophisticated model of this type is that of

Deaves and Harris (1981), which is based on a rigorous similarity analysis of the atmospheric boundary

layer. The velocity profile is given by

(4)

The theory of Deaves and Harris gives values for gradient height explicitly. Near ground z=0, equation 4

reduces to unmodified logarithmic format (eq. 2). Whilst more complex than the power law (eq. 1) and

unmodified logarithmic law (eq. 2) approaches, this method incorporated a rigorous analytical background,

and gives good fit to the velocity variation over large height range.

The above discussion has assumed that the velocity profile extends down to ground level. However, for

urban terrain this is not the case. To remedy this, it is assumed that the "effective" ground level will be above

the actual ground level by replacing z by z-zd, where z

d is the zero plane displacement. This is allowed in

several codes and standards. Here d is determined empirically and is the function of nature, height and the

distribution of roughness elements. Typical value of this parameter is usually around 0.8 times the average

building/local roughness height (Simiu and Scanlan 1996).

TURBULENCE INTENSITY PROFILES

The turbulent intensity is defined as the ratio of the standard deviation (σ) of fluctuating wind to mean wind

speed for a given duration as:

(5)

There are two fundamental methods of estimating values of turbulent intensity for dynamic structural

response. The first approach is similar to the power law approach for velocity profiles and is given by:

(6)

=

o

g

o

g

z

z

z

z

u

u

ln

ln

+

−

−

+

×=

432

25.033.188.175.5ln*5.2ggggg z

z

z

z

z

z

z

z

z

zuu

uI

σ=

βσ

×=

g

u

z

zk

u


where σu is the standard deviation of fluctuating wind velocity component in longitudinal direction, k and β are

simple functions of chosen reference height and power law exponent. This approach has the same

advantages and drawbacks as the power law (Holmes et. al. 2005). For a classic rough wall turbulent

boundary layer the stream-wise turbulence component is given by

(7)

where δ is the boundary layer thickness. If this equation and the logarithmic law are used together they result

in the following expression for the longitudinal turbulent intensity, in the lower part of the boundary layer

where (z/δ) tends to zero.

(8)

Many codes and standards (refer Table 6) use expressions similar to this equation 8. Since logarithmic law is

not valid for z > 100m, this expression is also valid up-to 100m. The theory of Deaves and Harris also results

in an expression that is theoretically valid throughout this boundary layer. This is given by

(9)

The use of this equation with the logarithmic law velocity profile (eq. 2) enables an expression for turbulent

intensity to be derived.

TURBULENT LENGTH SCALE FOR LONGITUDINAL WIND DIRECTION

Integral length scales of turbulence are the measure of the size of vortices or average size of eddies in a given

wind direction (Dyrbye and Hansen 1997). The integral length scales depends on the height z, zo and wind

velocity at a site. There are several methods to calculate the values of length scale from measured data.

Harris (1986) carried out extensive analysis of equations for calculating length scale deduced from existing

spectrum formulas. However, these formulas have several parameters, which are complex and not easy to

apply in wind tunnel tests.

In general, length scale of turbulence in longitudinal direction (xLu ) can be estimated using the following

equation:

(10)

−×=δ

σ z

u

u 8.015.2*

=

o

u

z

zuln

1σ

+

+×

−×

=

−

o

g

z

z

ogu

z

z

z

z

z

z

u

g

6156.01

ln09.0538.015.7

*

6/1

1

σ

∫∞

==

0

)()(. ττ dRuTuL ux

ux


where xTu is the time scale of longitudinal turbulence in along wind direction, u is the mean wind speed, and

R(τ) is the cross-correlation function of measured time history data.

In this paper, four methods are presented to estimate the values of turbulent length scale from measured

data.

Counihan (1975) has suggested the following empirical expression (eq.11) for estimating longitudinal

integral length scale for z ranging from 10m to 240m:

(11)

where c and m depend on roughness length (zo). According to Counihan, integral length scales decrease with

increasing surface roughness. The opposite variation is specified by ESDU - 85020, Simiu and Scanlan

(1996).

In addition to equation 11, length scale can be estimated using the existing spectrum expressions, for

example, using Von Karman spectrum at the natural frequency n = 0 is:

(12)

where Su(z,0) is the value of power spectral density function at frequency n = 0 at height z.

Another empirical formulation recommended by American Society of Civil Engineers (ASCE, 1999) is:

(13)

where is the reduced frequency of structure for which length scale is a maximum. As per

ESDU (75001), length scale of turbulence is estimated by

(14)

WIND SPECTRA

It describes the distribution of turbulence with frequency. This spectrum (i.e. spectral density function)

represents the contribution of various ranges of frequencies to the variance (σ2, square of standard deviation

for wind velocity components).

The following three conditions are generally used to estimate the power spectral density:

1. The value of spectra for n=0 is:

(15)

where lu is the integral length scale of turbulence.

mu

x zcL ×=

)(

)0,()()(

2 z

zSzuzL

u

uu

x

σ=

mu

x

f

zL

π2=

unzfm /=

( )

×=

063.0

35.0

25

o

ux

z

zmL

u

lS uu

u

24)0(

σ=


2. The area under the spectral curve equals to the total variance of fluctuating wind speed, and is then

consistent with turbulence intensity :

(16)

3. At high frequencies, where B is in the range of 0.10 to 0.15.

Different spectral models available to describe the distribution of power spectral density are presented below:

Von-Karman (1948)

(17)

This spectrum satisfies all three conditions. In case of condition#3, B is 0.12.This spectrum can be used in

applications where the effect of low frequency component could be important such as analysis of structures

having long natural period of vibrations. This is the most common form for the longitudinal velocity

component developed by Von Karman (1948) and adapted by Harris (1968).

Modified Kaimal (1972)

(18)

This eq. satisfies condition#1 of power spectra only for assumed ratio of b1 to b

2 0.67. Condition#2 is also

satisfied if b1=4 and b

2=6 are chosen. Value of B in condition#3 should be taken as 0.2 (which is outside the

range) to satisfy Kaimal's spectra.

For built-up terrain, the equation overestimates the result of structural response by 5%. This equation is

satisfactory, if the response of structure does not depends significantly upon the shape of the spectrum in

lower frequency range.

Davenport (1961)

(19)

This equation has been obtained by averaging the result of measurements obtained at various heights above

ground level. It overestimates the longitudinal spectra of turbulence in the high frequency range by 100-400%.

1

)(

02

=∫∞

dnnS

u

u

σ 3/2

2

)(−

=

u

nlB

nnS u

u

u

σ

6/52

2

8.701

4)(

+

=

u

nl

u

nl

nnS

u

u

u

u

σ

3/52

2

1

2

1

)(

+

=

u

nlb

u

nlb

nnS

u

u

u

u

σ

3/42

2

1

67.0)(

+

=

u

nL

u

nL

nnS

u

u

σ


In case of Davenport spectrum, condition#1 is satisfied but condition#2 is not satisfied. Assuming the length

scale L, to have a value 11.9 lu, condition#3 is satisfied.

Although all three spectral forms satisfy the condition#1 and condition #3, only Von-Karman spectrum

satisfies all three conditions.

TERRAIN AND EXPOSURE CATEGORIES

It has long been recognized that wind speed varies with height and the variation is related to the drag on the

wind as it blows over upstream areas, the drag among other things being related to the roughness of the

ground (zo). To cater to these varying roughness conditions, different terrain categories are specified in

different wind load codes and standards. The roughest terrain type with zo=2m-3m is usually specified for

the large city center or urban situation, whilst the smoothest is either defined as flat open terrain or as a

coastal situation with zo=0.001 m.

BRIEF DESCRIPTION OF EXPERIMENTAL PROGRAME

The experiments have been carried out in the BLWT at Indian Institute of Technology Roorkee. This is an

open circuit, continuous flow, suction type tunnel using single blower fan (125 HP) having a test section of

2.1 m × 2.0 m size. The length of test section is 15 m. Further details regarding wind tunnel at IIT Roorkee

are pronounced in Asawa et. al.(1985).

Part of an experimental study reported in this paper, has focused on wind flow characteristics generated in

the BLWT.

Five numbers Counihan type elliptical wedge vortex generator elements, along with a 15cm high barrier

wall and cubical roughness blocks of 5cm, 7cm, 10cm and 15cm have been used for generating the different

boundary layer profiles in the tunnel.

For the measurement of velocity fluctuations, constant temperature hot-wire anemometer system from 'Dentec'

was used. The hot-wire probe and the associated instrumentation were calibrated to give a voltage-velocity

relationship, to enable conversion of the acquired raw voltages to the wind velocities. Calibration has been

carried out in a smooth uniform flow at 24 different velocities, with turbulence level not exceeding 0.5% at

1.0m height in the test section. Static velocity head was measured using a standard pitot-tube connected to a

highly sensitive MKS Baratron (capacitance type) transducer and its digital display unit. Corresponding

head was converted to velocities and simultaneous values of voltage output at mean value unit of hot-wire

system were recorded for a range of wind speed between 2m/s and 12m/s. Instantaneous velocity fluctua-

tions have been recorded at a sampling frequency of 4 KHz for duration of approximately 4 seconds, viz, a

total of 16384 samples are recorded at each point for flow characteristic measurement.

DESCRIPTION OF WIND CHARACTERISTICS FOR DIFFERENT CODES AND

STANDARDS

Power Law Exponent (ααααα) and Surface Roughness Length (zo)

In order that codes with wind profiles specified using Power Law can also be compared with others using

logarithmic law, the following approximate equation is used for conversion (Choi Edmund 2009)


(20)

where Z1=10m and Z

2=100m are set.

Another simple relation between power law exponent, surface roughness and the turbulent intensity is given

by EPA (Environmental Protection Agency, U.S -1981)

(21)

These two formulae have been used in this study for the conversion purpose.

Table 1 shows how the methods (presented in this paper for mean velocity and turbulent intensity profiles)

are adopted by major codes and standards. It is to be noted that the number of terrain specified in various

codes are different and vary from 1 to 5. For example, Hong Kong has only one terrain type whereas Japan

has five types.

=

OZ

ZZ 21ln

1α

=

o

o

z

z

zIu

ln

30ln

(%) α

Table 1 Summary of terrain-height and averaging time format in various wind codes

Code/Standard

Number of terrain Velocity and Turbulence

Intensity Profiles

Averaging Time for

basic wind velocity

definition categories

IS:875 (Part 3)-1987 4 Power Law 3-sec

IS:875 (Part 3)-2011 4 Log Law 3-sec

HK-2004 1 Log Law 1 hr

AIJ 2004 5 Power Law 10 min

AS/NZS1170.2:2002 4 Deaves and Harris 3 sec

ASCE-7-05 3 Power Law 3 sec

BS EN 1991-1-4.2005 5 Log Law 10 min

NBCC (1995) 3 Power Law 1 hr

GB 50009-2001 4 Power Law 10 min

ISO/FDIS 4354: 2008 4 Deaves and Harris 3 sec

SNiP 2.01.07-85 3 Power Law 10 min

The averaging time for basic wind velocity employed in different codes and standards are also summarized in

Table 1. For the purpose of comparison, the conversion factor for 3second gust velocity and 10minute mean

from 1hour mean wind velocity is given in Table 2 (Simiu and Scanlan 1996). For example, a 3sec.

gust velocity for sub-urban terrain will be 1.4 times the mean velocity for 1hour.


Table 2 Conversion factors for 1-hour averaging time

Terrain Categories/Averaging Time 3 Seconds 10 Minutes

Sub-Urban (zo=0.2m) 1.40 1.05

Heavy Sub-Urban (zo=0.7m) 1.47 1.06

Urban (zo=2m) 1.54 1.07

Basic wind speed profile simulation parameters specified in different codes and standards are presented in

Table 3 for sub-urban, heavy sub urban and urban terrains. Indian Standards (both existing as well as pro-

posed) and ISO (2008) do not specify any value for heavy suburban terrain. It may be noted that a large gap

exist in Indian Standards between suburban (α=0.18) and urban (α=0.36) terrain, that affects the design of

any structures. As sub-urban terrain gives conservative values while urban provides unsafe values for design

forces. Further, Australian/New-Zealand code does not categorize heavy sub-urban terrain in its code, but

allows linear interpolation between different terrain categories. Canadian Code does not specify any value

for terrain corresponding to α=0.15 to α=0.25. On the other hand Hong-Kong code provides the value for a

single general terrain category.

The city centre classification (Exposure A), was discontinued in the American Code (ASCE7-05), but for

comparison purpose, it is taken from an earlier version of same (ASCE 7-98). This terrain category is also

not included in British/European Standard (BS EN 1991-1-4.2005).

Table 3 Values of Basic Wind Speed Profile Simulation Parameters in Different Codes and Standards

Code/Standard

Sub-Urban Heavy Sub-Urban Urban/City Centre

Exponent Roughness

length (m) Exponent

Roughness

length (m) Exponent

Roughness

length (m)

IS:875 (Part 3)-1987 0.18 0.12 - - 0.36 1.96

IS:875 (Proposed) 0.20 0.20 - - 0.31 2.0

HK-2004 0.11 0.0035 0.11 0.0035 0.11 0.0035

AIJ 2004 0.20 0.20 0.27 1.28 0.35 1.82

AS/NZS1170.2:2002 0.20 0.2-0.4 0.26 0.4-1.0 0.34 2.0

ASCE-7-05 0.20 0.10 0.25 0.30 0.33** 2.0**

BS EN 1991-1-

4.2005 0.21 0.30 0.28 1.0 - -

NBCC (1995) - - 0.25 0.58 0.36 1.97

GB 50009-2001 - - 0.22 0.30 0.30 1.0

ISO/FDIS 4354:

2008 0.22 0.30 - - 0.31 3.0

SNiP 2.01.07-85 0.20 0.18 0.25 0.90 - -

Note- (1) Values in Italics font are estimated by given conversation formulae or logarithmic plot of velocity profile.

(2)**ASCE-7 (95)

Limited information could be obtained for the Chinese code (GB 50009-2001), Russian code (SNiP 2.01.07-

85) and ISO standard (4354: 2008). It appears that Chinese code does not specify any value for terrain

corresponding to α= 0.15 to α=0.22. Russian code provides value of α up-to 0.25 only.

Table 4 shows the comparison of roughness length and power law exponent obtained from experiments for

three different terrains, as given in literature. Experimental values of α in present study as well as by Wang

and Stathopoulos (2007) are close to values recommended by Indian & Canadian respectively.


ASCE and BS EN Standards give approximately same value of turbulent intensity. It is noted that, the values

are significantly higher than those with other codes and standards, especially for H>75m. Japanese and

Australian codes initially have a narrow gap between their turbulent intensity values but this gap increases as

the height increases up-to 300m, and after more than 300m height the gap has disappeared.

Heavy Sub Urban terrain

Figure 2 represents the variation of mean wind velocity and turbulent intensity with height for heavy

sub-urban terrain (0.21 < α ≤ 0.29). Present experimental data shows similar trend for mean wind velocity as

other codes and standards, but lower values up-to 175m. This heavy sub urban terrain does not exist in

Indian standards (1987 and 2011), and a very large gap exists between terrain category III (α=0.18) and

category IV (α=0.36). Thus, there appears to be a need for more refined terrain category classification for

Indian Standards.

Similarly, in AS/NZS Standard this terrain is not defined, but they allow linear interpolation. HK code shows

same values as in the suburban and urban terrain category.

Figure 2.Mean wind velocity and turbulent intensity profile for heavy-suburban terrain in codes and

standards for corresponding value of ααααα

Chinese Code shows the highest value of mean wind velocity despite of lower power law exponent because

it considers twice the value of the power law exponent, while calculating mean wind velocity as shown in

Table 5. BS-EN Standard and AIJ Code give the almost same value up-to 150m height. However, for greater

heights, the values are different with maximum difference of 11.12% at 400m height.

Present experimental data follow the BS EN Standard for H<175m. However, for H>175m the values are

higher than the BS EN Standard values but lower than the others codes and standards.

Up-to 150m ASCE, BS-EN, NBCC and AIJ turbulent intensity values lie near the zone of turbulent intensity

specified by ESDU guidelines in spite of having different values of exponent or roughness length values.

Hong-Kong has the unique profile for all terrains.

BS-EN Standards considers the much higher values of turbulent intensity at lower heights than the others,

ranging between 18%-43%, in spite of having lower value of roughness length (1m) than AIJ code (1.28m).

This may be because of higher value of gradient height considered by Japanese Code.

0

50

100

150

200

250

300

350

400

10 20 30 40 50 60 70 80

Ht

(m)

Velocity (m/s)

HK-2004 (0.11)

AIJ-2004 (0.27)

ASCE 7-05 (0.25)

NBCC 1995 (0.25)

Present Study (0.25)

BS EN (0.29)

CHINA-GB 50009-2001 (0.22)

0

50

100

150

200

250

300

350

400

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45

Ht

(m)

Turbulent Intensity (%)

HK-2004(0.11)

AIJ-2004 (0.27)

ASCE 7.05 (0.25)

NBCC-1995 (0.25)


ESDU (0.23)

ESDU (0.28)

BS EN (0.29)


Urban terrain

Figure 3 shows mean velocity and turbulent intensity profiles for urban terrain (α > 0.29). The existing and

proposed Indian Standards give the same values of velocity at all height despite of using different approach

for velocity estimation.

AIJ 2004, AS/NZS 2002, ASCE 7.05, NBCC, BS EN.2004 codes show a variation of 5-20%, 7-17%, 12-

31%, 11-35, 18-22% respectively with Indian Standard (1987) for H>100m and for lower heights (<30m)

this variation is very high (>200%) for HK Code.

Chinese code shows higher values of velocity at all heights than any other code except Hong-Kong at lower

heights. However, Indian Standards give lower values at all heights despite of having the highest value of

power law exponent. The reason behind the greater value of velocity by Chinese code is that they use a

multiplier of 2 to the power law index coefficient of their exposure coefficient formula.

Figure 3.Mean wind velocity and turbulent intensity profile for urban terrain in codes and standards

for corresponding value of ααααα

Present experiment results are in good correlation with other codes and literature. At H>100m experimen-

tal values follow AIJ and Indian Standard (1987) and at lower heights trend is similar to Khanduri results

and is different from Indian Standard (1987).

Indian Standard (1987) provides high value of turbulent intensity for H<75m and lower values at greater

height (H>200m) as compare to other codes/standards. The proposed and existing Indian Standards have

significant variation in their turbulent intensity values at all heights. It is noted that Indian Standard (1987)

does not provide any value of turbulent intensity below 40m.

AIJ and IS: 875-1987 codes show a very similar trend of values for turbulent intensity at H>150m. Similarly

AS/NZS and Indian Standard (proposed) show the similar values of turbulent intensity at H>100m. ASCE 7-

95, shows the greater values at H>75 m and significant difference of 121.2% and 62.4% at H=400m with

Indian Standard (existing) and Indian Standard (proposed) respectively. NBCC shows the variation of 10

87% at H>100m and less than 30% for H<75m with Indian standard (1987).

It may be pertinent to note that American as well as British/European Standard discontinued this category

from latest versions ASCE-7 and recommend wind tunnel study for such terrains.

0

50

100

150

200

250

300

350

400

0 10 20 30 40 50 60 70 80

Ht

(m)

Velocity (m/s)

IS-875-1987 (0.36)

IS-875-2011 (0.31)

HK-2004 (0.11)

AS/NZS 1170.2.2002 (0.34)

AIJ-2004 (0.35)

NBCC 1995 (0.36)


CHINA-GB 50009-2001 (0.30)

0

50

100

150

200

250

300

350

400

0 0.1 0.2 0.3 0.4 0.5 0.6

Ht

(m)

Turbulent Intensity (%)

IS:875-1987 (0.36)

IS:875-2011 (0.31)

HK-2004 (0.11)

AS/NZS 1170.2.2002 (0.34)

AIJ-2004 (0.35)

NBCC-1995 (0.36)


Khanduri et. al. (0.36)

ASCE 7.95 (0.33)


Table 6 Turbulent intensity profile in codes and standards

Turbulent Intensity Profile

Sub-Urban Heavy Sub-Urban Urban

IS-875

(Proposed)

( )7

3 1,4,1,3,

ZZZZ

IIII

−×+∗=

_

×−=

0.21358.0466.0 104,

ZLogIZ

HK-2004 11.0

901055.0

−

×=H

I Z 11.0

901055.0

−

×=H

I Z 11.0

901055.0

−

×=H

I Z

AS/NZS

1170.2.2002 Table 6.1

AIJ-2004 25.0

4501.0

−

×=

ZIZ

32.0

5501.0

−

×=

ZIZ

40.0

6501.0

−

×=

ZIZ

ASCE 7-05 6/1

1015.0

×=

ZIZ

6/110

30.0

×=

ZIZ **

6/110

45.0

×=

ZIZ

NBCC (1995) _ He

ZC

KI

25.0=

K=0.1 and 5.0

7.125.0

×=Z

CHe

HeZ

C

KI

25.0=

K=0.14 and 72.0

304.0

×=Z

CHe

BS EN 1991-

1-4.2005

=

3.0ln

1

ZIZ

=

0.1ln

1

ZIZ

_

It is observed from Figure 1, 2 & 3 that there is large variation among the values of turbulent intensity as the

terrain category changes from sub-urban to urban terrain. Since there is a large variation in turbulent

intensity as the terrain category moves from sub-urban to urban terrain, it appears to be logical that wind

tunnel study should be carried out for rougher terrains. Similar recommendation has also been made by

American and British/European Standards

Turbulent Length Scales

Table 7. shows the different formule used for estimating turbulent length scale in codes and standards.

Hong-Kong code gives the maximum value of length scale at all heights and for all three terrains due a

multiplier of thousand in its length scale formula as shown in the the Table 7. The existing Indian code show

slightly lower values of turbulent length scale than Hong-Kong, but much higher than others codes/

standards. Length scales in existing Indian code has been determined by Figure 8 in (IS:875 (Part 3) 1987).

This log-log graph is plotted between length scale and building height for different terrains. NBCC adopted

only a single value of length scale for all terrain, at all heights that is 1220m given by Davenport. Other the

codes/standards seem to show close variation of length scale because of different multipliers and powers

used in their respective codes.

It is interesting to note that in many codes like HK, AS/NZS and AIJ, length scale depends only on height

and is independent of roughness of terrain. Only the Indian Standards and BS-EN standard take the variation

of both height and terrain roughness, as also specified in the Table shown below.


Table 7 Turbulent length scales in different codes and standards

Codes/Standards Turbulent Length Scale (m)

IS-875 (Proposed)

0.25

10

h

×c

c depends on terrain category (c=85 for I, II, III terrain and 70 for IV terrain category)

HK-2004 0.25

10

h1000

×

AS/NZS 1170.2.2002 0.25

10

h85

×

AIJ-2004 0.5

30

h100

×

ASCE 7-05

ε

×

10

zl

l and ε depend on terrain type (table 6-2 in respective code)

NBCC (1995) 1220

BS EN 1991-1-4.2005

ZoZ

ln05.65.0

200300

+

×

zo depends on type of exposure

ESDU

×

063.0

35.0

25Zo

Z

zo depends on terrain type

*Note here h and z are in meter

For clear understanding about the variation in the LH the graph for all three terrain categories have been

shown in Figure 4. Experimental values obtained from wind tunnel tests are consistent with other codes and

standards and not with the existing Indian Standard. It may be noted that proposed Indian Standard is

harmonized with rest of the international wind codes/standards.

0

50

100

150

200

250

300

350

400

0 500 1000 1500 2000 2500 3000

Ht

(m)

Turbulent Length Scale (m)

Sub-Urban Terrain

IS 875-1987 (0.18)

IS 875-2011 (0.18)

HK-2004

AS/NZS 1170.2.2002

AIJ-2004

NBCC-1995

BS EN-2004 (0.21)


ESDU-1976 (0.20)

ASCE.7.05 (0.20)

0

50

100

150

200

250

300

350

400

0 500 1000 1500 2000 2500 3000

Ht

(m)


Heavy Sub-Urban Terrain

HK-2004

AS/NZS 1170.2.2002

AIJ-2004

ASCE 7.05 (0.25)

NBCC-1995

BS EN-2004 (0.29)


ESDU-1976 (0.28)


Figure 4 Turbulent length scales different terrains in codes and standards for corresponding value of ααααα

Wind Spectra

Table 8 shows the expressions for wind spectra adopted by different codes/standards. The Indian,

Hong-Kong, Australian and Japanese code use Von-Karman spectra, while BS-EN and ASCE use the

modified Kaimal spectra. However, NBCC uses Davenport spectra.

Despite of using Von-Karman spectran or Modified Kaimal spectra some variation has been observed due to

slight change in multipliers values used in numerator and denominator by these codes.

From Figure 5, it is clear that the experimental values for different terrains are consistent with the other

spectra. On comparing the Von-Karman spectra with the spectra obtained from expermental values, length

scale of turbulence was 172m, 140m and 108m for sub urban, heavy sub-urban and urban terrain

respectively.

Table 8 Wind spectra in different codes and standards

Wind Spectra Spectra Used

IS-875 (Proposed) H

H

v

v

V

Lfx

x

xffS . ,

)8.701(

.)(

6/522=

+=

π

σ Von-Karman

HK-2004 H

H

v

v

V

Lfx

x

xffS . ,

)2(

47.0)(

6/522=

+=

σ Von-Karman

AS/NZS

1170.2.2002 H

H

v

v

V

Lfx

x

xffS . ,

)8.701(

4)(

6/52=

+=

σ Von-Karman

AIJ-2004 H

H

v

v

V

Lfx

x

xffS . ,

)711(

4)(

6/522=

+=

σ Von-Karman

ASCE 7-05 Z

Z

v

v

V

Lfx

x

xffS . ,

)3.101(

47.7)(

3/52=

+=

σ Modified Kaimal

NBCC (1995) H

H

v

v

V

Lfx

x

xffS . ,

)1(3

2)(

3/42

2

2=

+=

σ Davenport

BS EN 1991-1-

4.2005 Z

Z

v

v

V

Lfx

x

xffS . ,

)2.101(

8.6)(

3/42=

+=

σ Modified Kaimal

0

50

100

150

200

250

300

350

400

0 500 1000 1500 2000 2500 3000

Ht

(m)


Urban Terrain

IS 875-1987 (0.36)

IS 875-2011 (0.31)

HK-2004

AS/NZS 1170.2.2002

AIJ-2004

NBCC-1995


ESDU-1976 (0.36)

ASCE 7.05 (0.33)


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1. Architectural Institute of Japan (AIJ-2004), "Recommendations for loads on buildings", (in English version).

2. ASCE, ''Minimum design loads for buildings and other structures'', ASCE 7-05.

3. AS/NZS: 1170.2:2002, Australian / New Zealand "Standard structural design actions", Part 2-Wind action.

4. AS/NZS: 1170.2 Supplement 1:2002, "Structural design actions", Part 2-Wind action-commentary

(Supplement to AS/NZS: 1170.2:2002).

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(Part 3)-1987 wind loads on buildings and structures", IITK-GSDMA Project on Building Codes.

7. BS EN 1991-1-4:2005, Eurocode 1: ''Actions on Structures-Part 1-4: Wind actions.''

8. Choi, E. C. C (2009), "Proposal for unified terrain categories exposures and velocity profiles",

Proceedings of 7th Asia Pacific Conference on Wind Engineering, 8th -12th November, 2009, Taipei,

Taiwan.

9. CISM Courses and Lectrues.No.493 (2007), "Wind effects on buildings and design of wind sensitive

structures", edited by Stathopoulos T. and Baniotopoulos C. C.

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the 80s- Proceedings of the CIRIA Conference, 12th -13th November 1980, London, CIRIA.

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(England).

12. Environmental Protection Agency (1980), "Guideline for fluid modeling of atmospheric diffusion,"

EPA Report 600/8-81-009, USA

13. ESDU. (1976), "Characteristics of atmospheric turbulence near the ground, Part M: Variations in space

and time for strong winds", (neutral atmosphere), Item75001, ESDU International Ltd., London.

14. ESDU. (2001), "Characteristics of atmospheric turbulence near the ground", (neutral atmosphere),

Item85020, ESDU International Ltd., London.

15. Farell, C. and Iyengar, A. K. S. (1999), ''Experiments on the wind tunnel simulation of atmospheric

boundary layers'', Journal of Wind. Engineering and Industrial Aerodynamics, Vol. 79, pp 11-35.

16. Ferraro, V., Irwin, P. A., and Stone, G. K. (1989). ''Wind-induced building accelerations'' Proceedings

of 6th U.S. National Conference on Wind Engineering, A. Kareem, ed., Univ. of Houston, Houston.

17. Gupta, A (1996), "Wind tunnel studies on aerodynamic interference in tall rectangular buildings",

Ph.D. Thesis, University of Roorkee, Roorkee, India.

18. Harris, R. I. (1986), "Longer turbulence length scales", Journal of Wind. Engineering and Industrial

Aerodynamics, Vol.24, pp 61-68.

19. Holmes, J. D., Baker, C. J., English, E. C. and Choi, E. C. C. (2005), ''Wind structure and codification'',

Wind & Structures, 8 (4), 235-250.

20. Holmes, J. D., Tamura, Y. and Krishna, P. (2009), "Comparison of wind loads calculated by fifteen

different codes and standards, for low, medium and high-rise buildings", Proceedings of 11th

American Conference on Wind Engineering, San-Juan, Puerto Rico, June 22-26, 2009.

21. Hong Kong (2004),"Code of Practice on Wind Effects in Hong Kong".


22. Indian Standards IS: 875 -Part 3 (1987), "Code of practice for design wind loads (other than

earthquake) for buildings and structures", Bureau of Indian Standards, New Delhi.

23. Indian Standards IS: 875 -Part 3 (2011), "Code of practice for design wind loads (other than

earthquake) for buildings and structures", Bureau of Indian Standards, New Delhi.

24. John, A. D. and Kumar, K. (2006), "Design wind velocity: Review of codal provisions". Third

National Conference on Wind Engineering, NCEW-2006, Kolkata, 5th January to 7th January,

2006, pp. 293-305.

25. Kasperski, M. (2006), "The new ISO-Approach for codification of wind loads", Journal of Wind and

Engineering, Vol. 3, No. 1, pp 38-47.

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27. Kikitsu, H. and Okada, H. (2003), ''Comparison of peak pressure coefficients for wind load among

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K. Mehta, eds., Wind Engineering Research Council, Lubbock, Tex.

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Canadian commission on building and fire codes, National Research Council of Canada, Ottawa, Part 4.

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35. Popov, N. A. (2000), "The wind load codification in Russia and some estimates of a gust loading

accuracy provided by different codes", Journal of Wind. Engineering and Industrial Aerodynamics,

Vol.88, pp 171-181.

36. Simiu, E., and Scanlan, R. (1996), "Wind effects on structures: Fundamentals and Applications to

design", 3rd Ed., Wiley, New York.

37. Tamura, Y., Kareem, A., Solari, G., Kwok, C. S. K., Holmes, J. D. and Melbourne, W. H. (2005),

''Aspects of the dynamic wind-induced response of structures and codification'', Wind & Structures,

8 (4), 251-268.

38. Xiangting, Z. (1988), "The current Chinese code on wind loading and comparative study of wind

loading codes", Journal of Wind. Engineering and Industrial Aerodynamics, Vol.30, pp 133-142.

39. Wang, K. and Stathopoulos, T. (2007), "Exposure model for wind loading on buildings", Journal of

Wind. Engineering and Industrial Aerodynamics, Vol.95, pp 1511-1525.

40. Zhou, Y., Kijewski, T. and Kareem, A. (2002), ''Along wind load effects on tall buildings: Comparative

study of major international codes and standards'', Journal of Structural Engineering, 128(6), 788-796.


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