wind parameters of texas tech university field site
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WIND PARAMETERS OF TEXAS TECH UNIVERSITY FIELD SITE
by
CHEE VUI CHOK, B.S. in C.E.
A THESIS
IN
CIVIL ENGINEERING
Submitted to the Graduate Faculty of Texas Tech University in
Partial Fulfillment of the Requirements for
the Degree of
MASTER OF SCIENCE
IN
CIVIL ENGINEERING
August, 1988
AJ 0 • ' ' • ACKNOWLEDGEMENTS
I would like to express my sincere gratitude and thanks to my committee
chairman, Dr. Kishor C. Mehta, for his guidance, encouragement and constructive
criticism throughout the course of this research. Special thanks are extended to
my thesis committee members, Dr. James R. McDonald and Richard E. Peterson,
for their valuable suggestions and comments.
Financial support by the National Science Foundation through Grant No.
CES8611601 and Civil Engineering Department is acknowledged and appreciated.
Deepest appreciation is reserved for my family. I am grateful to my parents and
my brother, Chee Leong, for their unending support in countless ways. Without
their help, I would not have been able to achieve what I have today.
Acknowledgements would be incomplete without expressing my utmost appre
ciation to the pioneering members of the Field Experiment team, Basilio Lakas,
Marc Levitan and Howard Ng, for the exemplary team work and enviable fun
we share in this project. Marc Levitan's help in my analysis work is greatly
appreciated.
11
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
ABSTRACT v
LIST OF TABLES vi
LIST OF FIGURES vii
CHAPTER
I. INTRODUCTION 1
II. LITERATURE REVIEW FOR CURRENT ENGINEERING PRACTICE 4
Stationarity 5 Atmospheric Stability 7 Wind Profile 9
Power Law 9 Logarithmic Law 9
Turbulence Intensity 12 Integral Scale of Turbulence 14
III. METEOROLOGICAL TOWER INSTRUMENTATION 19
Field Site and Terrain 19 Northeast Terrain 21 Southeast Terrain 21 Southwest Terrain 21 Northwest Terrain 25
Meteorological Tower 25 Instrument Boom 28
Instrumentation 30 Horizontal Wind Measurement System 30 Temperature Measurement System 34 Relative Humidity Measurement System 36 Barometric Pressure Measurement System 37
Data Acquisition System 37
IV. CALIBRATION OF METEOROLOGICAL INSTRUMENTS 39
Anemometer 39 \Mnd Vane 42
111
Temperature Sensor 43 Relative Humidity Sensor 47 Barometric Pressure Sensor 47 Cable Effect 49
V. ANALYSIS OF FIELD DATA 51
Time History 54 Stationarity 57 Descriptive Statistics 66 Wind Profile Parameters 69
Power Law Parameter 69 Logarithmic Law Parameters 71
Terrain Characterization 74 Turbulence Intensity 77 Longitudinal Integral Scale of Turbulence 80
VI. CONCLUSIONS AND RECOMMENDATIONS 85
Conclusions 85 Recommendations 86
LIST OF REFERENCES 88
IV
ABSTRACT
Wind parameters obtained from field data are generally simulated in wind
tunnel for studying wind effects on structures. The result of the wind tunnel study
depends on the reliability of field wind parameters and the simulation technique.
The objective of this study is to assess wind parameters from field data.
The National Science Foundation has sponsored a project at the Texas Tech
University Wind Engineering Research Field Laboratory to study wind effects on
low-rise building. Wind pressure and meteorological data are collected on the
test building and meteorological tower respectively. Meteorological data which
include wind speed, wind direction, temperature, barometric pressure and rela
tive humidity data, are measured at four levels of the tower. Wind speed, wind
direction and temperature data are used for assessment of wind parameters and
characterization of terrain.
A total of 63, 15-minute duration each, records are collected. Of these, 31
records are found to be suitable for analysis. These 31 records are analyzed to
determine wind profile parameters for both power and logarithmic laws, turbu
lence intensity and longitudinal integral scale of turbulence. The wind profile
parameters, mean wind directions and terrain features are used to characterize
the field site terrain. Results of the analysis are presented in this report.
LIST OF TABLES
2.1 Power Law Exponents in Different Codes 10
2.2 Longitudinal Integral Scale of Turbulence at 10 m 18
3.1 Specifications of Temperature Sensors 35
4.1 Results of Anemometer Test in Wind Tunnel 41
4.2 Results of Anemometer Test with Calibrator 41
4.3 Laboratory Test Results of Temperature Sensors 44
4.4 Field Test Results of Temperature Sensors 46
4.5 Test Results of Relative Humidity Sensor 48
4.6 Test Results of Barometric Pressure Sensor 50
5.1 Summary of Wind Data Set 52
5.2 Stationarity Results for Cold Front Records 63
5.3 Stationarity Results for Blowing Dust Records 64
5.4 Stationarity Results for Thunderstorm Records 65
5.5 Mean and RMS Values of Wind Speed 68
5.6 Mean and RMS Values of Wind Direction 70
5.7 Wind Profile Parameter Values 73
5.8 Average Wind Profile Parameter Values in Zones ' 76
5.9 Turbulence Intensity Values 78
5.10 Average Turbulence Intensity Values in Zones 79
5.11 Longitudinal Integral Scale of Turbulence Values 83
5.12 Average Longitudinal Integral Scale of Turbulence Values in Zones 84
VI
LIST OF FIGURES
2.1 Roughness Length Values (ESDU, 1982) 13
3.1 Field Test Facility and Surrounding Terrain 20
3.2 Map of Area Surrounding Test Facility 22
3.3 Northeast Terrain (a) North-northeast, and (b) East-northeast 23
3.4 Southeast Terrain (a) East-southeast, and (b) South-southeast 24
3.5 Southwest Terrain (a) South-southwest, and (b) West-southwest 26
3.6 Northwest Terrain (a) West-northwest, and (b) North-northwest 27
3.7 Meteorological Tower (a) Instrument Boom, and
(b) Instruments on the Tower 29
3.8 Anemometer and Wind Vane at 33 ft Level 31
3.9 Dynamic Response of 3 Cup Anemometer and Wind Vane Supplied by R. M. Young Company 33
5.1 Typical Wind Speed Time History (a) at 33 ft Level, and
(b) at 160 ft Level 55
5.2 Wind Speed Record with Defected Data 56
5.3 Typical Wind Direction Time History (a) at 33 ft Level, and
(b) at 160 ft Level 58
5.4 Wind Direction Record with Defected Data 59
5.5 Typical Wind Speed Autocorrelation Function Plot 61
5.6 Nonstationary Wind Direction Record 67
5.7 Determination of Power Law Exponent 72
5.8 Determination of Roughness Length and Shear \'elocity 75
5.9 Mean Wind Direction of 31 Data Sets 76
v i i
5.10 Wind Speed Autocorrelation Function Plot (a) Fluctuating about Zero, and (b) Nonfluctuating about Zero 81
V l l l
CHAPTER I
INTRODUCTION
Winds in the atmospheric boundary layer (ABL) have significant effects on
the design of structures. Wind forces can damage or even destroy structures.
The extreme winds are of particular interest to structural engineers as structures
have to be designed to prevent collapse. The turbulent nature of wind makes it
difficult to assess the effects of wind on structures. Assessment of turbulence and
other characteristics of wind from field data is necessary to understand the nature
of wind. This understanding of nature of wind will assist in simulation of wind
fiow in the wind tunnel where in-depth study of wind effects on structures can
be done. Only properly simulated wind flow can provide reliable results in wind
tunnels.
Simulation of wind flow requires the effect of test site terrain to be modeled
as the wind flow and the turbulence of the wind are affected by the roughness of
the terrain. Wind flow close to the ground in the field is obstructed by the terrain
roughness, causing turbulent wind with reduced wind speed. As height increases
in the ABL, the wind speed increases and turbulence of wind decreases because
the effect of terrain roughness reduces with height. It is important to assess wind
parameters in the ABL which depend on the terrain roughness.
Proper modeling of the ABL characteristics in the wind tunnel requires cor
rect simulation of wind profile and turbulence parameters. Only correct simu
lation can provide realistic model results in term of wind loading. Simulation
of wind profile and turbulence intensity are sufficient for mean load experiment.
Simulation of longitudinal integral scale of turbulence is required in addition to
1
the wind profile and turbulence intensity for unsteady load modeling of low-rise
buildings (Surry, 1979). An incorrect longitudinal integral scale of turbulence
gives unreliable model results.
At present, wind tunnel technology for low-rise building is not fully developed.
The pressure coefficients for low-rise buildings obtained from the wind tunnel are
questionable because of difficulties in scaling the model and in simulating wind
parameters close to the ground. Knowledge of wind characteristics from field data
is necessary to improve modeling for low-rise buildings in wind tunnel.
The well-known fuU scale wind pressure experiment for low-rise building con
ducted at Aylesbury, England, collected wind and pressure data on a test building
(Eaton and Mayne, 1974). In this experiment, wind data up to 10 m (32.8 ft)
were collected and analyzed. Simulation of this experiment in wind tunnel showed
that a change of wind profile slope occurred at a height of about 15 m because
of hedges around the test building (Surry and Vickery, 1982). But the field data
extended only up to 10 m. There was difficulty in matching the wind tunnel and
the full scale results. Without proper establishment of wind parameters in the
field, it is difficult to duplicate the results in the wind tunnel.
The need for better understanding of wind effects on low-rise buildings has
led to a research project on a full scale wind study in the field at Texas Tech
University. The National Science Foundation has sponsored the project to acquire
wind and associated pressures on a building in the field. This project provides
an opportunity to study wind parameters in the bottom layer of the ABL and to
assess the wind parameters as they are affected by terrain. Instruments for wind
speed, wind direction, temperature, relative humidity and barometric pressure,
are installed at various levels of a 160 ft meteorological tower. .A. computer
controlled data acquisition system is housed inside the data acquisition room.
Data collected at the site is used to assess wind parameters.
The objectives of this study are to assess wind parameters for the Texas Tech
University field site. These parameters will be used to analyze building pressure
data collected at the test site as well as to assist simulation of winds in wind
tunnel studies. Specific objectives in this research are :
1. the assembly of the meteorological tower instrumentation,
2. the calibration of the instrumentation, and
3. the characterization of the field site for wind profile, turbulence intensity
and longitudinal integral scale of turbulence.
The following chapter contains an overview of the literature review for current
engineering practice concerning stationarity of time series, atmospheric stability,
wind profile, turbulence intensity and integral scale of turbulence. Description
of the field site and the meteorological tower instrumentation are presented in
Chapter III. Methodology and results of calibration of the instrumentation are
presented in Chapter IV. Chapter V contains the analysis of the field data which
includes stationarity check, and assessment of the wind profile, turbulence inten
sity and longitudinal integral scale of turbulence parameters. Conclusions of this
study are presented in Chapter VI.
CHAPTER II
LITERATURE REVIEW FOR CURRENT
ENGINEERING PRACTICE
Large scale motion of the atmosphere is derived from solar energy which is
transmitted to the earth's surface. The movement of air in the atmosphere is
termed wind. At sufficient height above the ground surface, frictional forces
caused by the ground surface roughness become negligible and the wind speed
is essentially constant and is called gradient wind. The height at which the
gradient wind exists is termed gradient height. Between the earth's surface and
the gradient height, wind is affected by frictional forces (mechanical turbulence),
and this region is called atmospheric boundary layer (ABL). All the earth-bound
structures are subjected to complex wind turbulence in the ABL. The vertical
temperature variation which is called thermal gradient also modifies wind in the
ABL; however, major wind effects on structures are associated with strong winds
for which thermal gradient effects are small and generally neglected.
Wind in the ABL is turbulent in nature and fluctuates randomly in time and
space. Fluctuating wind can be assumed to consist of a steady component and
fluctuations about this steady component; these are called mean and turbulence
respectively. Because of its random fluctuating nature, it is essential to use sta
tistical analysis to define wind parameters.
Statistical analysis of the wind data requires the time series be stationary
before any analysis can be performed. Stationarity of time series, atmospheric
stability and wind parameters which include wind profile, turbulence intensity
and integral scale of turbulence are discussed in this chapter.
Stationarity
A randomly fluctuating time series can be categorized as being either station
ary or nonstationary. A time series is said to be stationary when its statistical
properties are invariant of time. It is important to assess the stationarity of the
time series because almost all time series analysis procedures in the current prac
tice assume that the data being analyzed is stationary (Jenkins and Watts, 1968).
If the time series is nonstationary, most of the currently used analysis procedures
are not applicable.
There are two stationary conditions, weakly stationary and strongly station
ary. A weakly stationary condition exists when the ensemble averaged mean is
invariant of time and the ensemble averaged autocorrelation function is indepen
dent of starting time (Bendat and Piersol, 1986). Any other stationary situation
is classified as strongly stationary condition. For analysis of wind data, only sta
tistical parameter, root mean square is used, hence weakly stationary condition
is sufficient.
For a single time series, a slightly different interpretation of stationarity is
needed. Stationarity of a time series means the statistical properties computed
over short time intervals do not vary from one interval to the next, which is usually
referred to as self-stationarity. A time series is said to be self-stationary when the
mean and the autocorrelation function averaged over short time interval do not
vary from interval to interval. The mean and autocorrelation function as given
by Simiu and Scanlan (1978), are as follows :
X = ^ i : x „ (2.1) n = l
1 ''•• ''' ^ = ^i (N3;) E (Xn - X)(X„^. - X) (2.2)
where p[r) = the autocorrrelation function at lag r,
X = the mean of the time series,
Xn = the nth data point of the time series,
(T^ — the variance of the time series, and
N = the total number of data point.
The interval length must be carefully chosen so that it represents a true aver
age properties of the time series. The interval must be statistically independent
(Levitan, 1988). Once the interval length is chosen, the time series is divided into
intervals. The mean and autocorrelation are calculated to examine any variation
from interval to interval.
Practically, computing the autocorrelation function of a large time series for all
the possible lags uses a large amount of computer time. Bendat and Piersol (1986)
have suggested that a time series can be considered self-stationary if the mean
and the autocorrelation function (see Equation (2.2)) at lag equal to zero (mean
square value), contain no trends or variations other than sampHng variations.
Two tests, the run and trend tests are used to check the stationaritv of a
time series. The run test is more powerful for detecting the fluctuating trends,
whereas the trend test is powerful for detecting monotonic trends (Bendat and
Piersol, 1986). It is hypothesized that the sets of mean and mean square value
are independent and self-stationary. The hypothesis is tested at a confidence
level of /? which is usually 90%, 95% or 99%. The hypothesis is accepted if the
number of runs for run test or the number of reverse arrangements for trend tost
fall within the acceptable region. The acceptance of the hypothesis means that
there is insufficient evidence to believe the time series to be self-nonstationary.
Rejection of the hypothesis shows that there is enough evidence to befieve the
time series to be self-nonstationarv.
Atmospheric Stabihty
Three general states of atmospheric stability conditions are defined : neutral,
unstable and stable. Under neutral stability condition, the lapse rate which is
the temperature variation with height, is equal to the dry adiabatic rate, which
is 5.5°F per 1000 ft (Navarra, 1979). Neutral stability condition usually exists
in strong winds where turbulence caused by ground roughness, called mechanical
turbulence, is predominant. Under unstable stability condition, the lapse rate
is greater than the dry adiabatic rate. Air near ground surface is warmer and
less dense than the air above, creating a thermal gradient. The thermal gradient
causes the air to rise rapidly which generates thermal turbulence. The combina
tion of mechanical and thermal turbulence exists in this condition. Under stable
condition, the lapse rate is less than the dry adiabatic rate. At the extreme, there
is a temperature inversion; typically, the winds are light and a cool dense layer
of air forms above the ground. In stable condition, the mechanical turbulence
may be suppressed. For the extreme wind that cause high loads on buildings, the
atmospheric stability condition is usually neutral where mechanical turbulence is
predominant.
It is desirable to determine the stability conditions at the time of data collec
tion because the wind profile equation is primarily valid for near neutral stability
condition. The gradient Richardson number. Ri. which indicates the relative
8
importance of thermal to mechanical turbulence, can be used to distinguish the
stability conditions as stable, neutral or unstable depending upon whether its
value is positive, zero or negative respectively. Fichtl (1968) has developed the
following equation to estimate gradient Richardson number at the geometrical
mean height by assuming that the mean wind speed and the temperature are
distributed logarithmically between two levels Zi and Z2. It is represented as :
Ri(ZJ = ^ T(Z,)
T(Z,)-T(Zi) g U(Z,)-U(Zi) - 2
(2.3)
where Ri(Zg) = the gradient Richardson number at the
geometric mean height,
g = the acceleration due to gravity,
T(Z) = the mean temperature at height Z.
Cp = the specific heat of air at constant pressure,
U(Z) = the mean wind speed at bight Z and.
Zg = the geometric mean height (= vZ]Z2)-
The limit of gradient Richardson number for near neutral stability condition
has been suggested by several researchers. Teunissen (1970) and Panofsky (1977)
have suggested |Ri| < 0.03 and |Ri| < 0.01 for neutral stabihty condition respec
tively. Duchene-MarruUaz (1978) assumed near neutral stability condition when
Ri is between 0.025 and 0.015.
Neutral stability condition is generally assumed to exist by engineers when
the wind speed at 33 ft is higher than 20 mph. ESDU (1982) has suggested that
near neutral stabihty condition exists when the mean hourly wind speed is greater
than 10 mps (22 mph) at the height of 10 m (33 ft).
Wind Profile
Wind profile is the variation of mean wind speed with height above ground.
It is usually represented by power law or logarithmic law.
Power Law
Power law is an empirical equation and is widely used by engineers because
of its simpHcity. It is represented by the following equation (Davenport, 1960) :
Ui /ZiN'^
u; = (z;) (2- )
where Ui, U2 = the wind speeds at height Zi, Z2 respectively, and
a = the power law exponent.
The power law exponent is dependent on ground surface roughness and aver
aging time. It is suggested by Davenport (1960) that the power law is valid in
near neutral atmospheric stability condition. Typical power law exponent values
used by various national codes are shown in Table 2.1. The power law exponent
value increases with rougher terrain.
Equation (2.4) is primarily used for tall structures because of its assumed
validity up to the gradient height. However, it has been criticized on the ground
that the power law exponent is not constant, but varies significantly with different
height range above ground (Hansen, 1970).
Logarithmic Law
Logarithmic law is developed from physical laws and is widely accepted by
meteorologists. It can be represented as follows (Simiu, 1973) :
10
Table 2.1 Power Law Exponents in Different Codes
Terrain
Category
Big city Centers
Urban, suburban areas
Open terrains
Flat unobstructed coastal areas
ANSI
Standard' (ANSI, 1982)
0.33
0.22
0.14
0.10
Canadian
CodeT (NRCC,1980)
0.36
0.25
0.14
Australian
Codet (SAA.1983)
0.20
0.14
0.09
0.07
* design wind speed based on fastest-mile. t design wind speed based on mean hourly average. I design wind speed based on two second gust.
11
U(Z) = ^ I n l ^ l - ^ (2.5)
where U(Z) = the wind speed at height Z above ground,
U» = the shear velocity,
k = the von Karman constant,
d = the displacement height,
Zo = the roughness length, and
ip = the universal function.
The shear velocity is defined for homogeneous terrain by U. = J^ evaluated
with surface stress, r and air density, p. The U« value in the logarithmic law is
the average value over the height range where the wind speeds are measured.
There is some disagreement in the value of von Karman constant, k. Tennekes
(1973) has recommended the k value of 0.35 ±0.02 over smooth terrain. A von
Karman constant over near smooth terrain of 0.35 is also suggested by Schotz
and Panofsky (1980). It is classically assumed to be 0.4.
The displacement height, d is the height at which the boundary layer begins
to form. For high roughness such as tall buildings, there will be a shift of the
boundary layer upward by a depth of d. For low roughness, d is usually neglected.
Typical value of d is about 70-80 % of the height of large roughness elements such
as trees and houses (Panofsky and Dutton, 1984).
The roughness length, ZQ, is physically represented by the vertical distance
from the displaced reference plane, d to the height where the wind profile extrap
olates to zero (Abtew, 1986). Panofsky and Dutton (1984) have suggested that
Zo represents the eddy size at the surface. The roughness length is dependent on
12
the surface roughness. Typical values of roughness length for different terrains
are shown in Figure 2.1.
The universal function, ij) is included in Equation (2.5) for diabatic condition
where the vertical thermal effects become important comparable to the effects of
mechanical mixing. It is assumed to be zero for neutral stability condition.
The logarithmic law is an excellent representation of wind profile in horizon
tally homogeneous surface (Simiu, 1973); it is assumed to be vaHd up to about
30-50 m above ground (Simiu and Scanlan, 1978). Garratt (1978) also suggests
that logarithmic law fails at Z < IOZQ. The reason is that condition at this small
height is no longer horizontally homogeneous because of the effects of individual
elements.
Turbulence Intensity
The most commonly used parameter to define turbulence in time domain is
turbulence intensity. It is a measure of the relative ampHtude of the fluctuations
compared to the mean component of wind. It is expressed as :
T. = J (2.6)
where Tu = the turbulence intensity.
a = the root mean square of wind speed, and
U = the mean wind speed.
Turbulence intensity decreases with height since the mean wind speed increases
and the fluctuation of wind decreases. The turbulence intensity increases with
13
Terrain description 9 S 7 • 9 '
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FOftltt
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10
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• s
i d \
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> Folrly lovol groH ftaint
AlrpOfli (rwMMy oroo)
> La«g« tipontM of I M I M ( M O Couollon C.I)
0«i*f«(nall
y Sno>-co»«r*d Hal or rolling ground
let , mud dolt
Id'
Figure 2.1 Roughness Length Values (ESDU, 1982)
14
averaging time as mean wind speed tends to decrease with increase in averaging
time (Kancharla, 1986).
Integral Scale of Turbulence
Integral scales of turbulence are measures of the average size of turbulence
eddies in appropriate directions (Simiu and Scanlan, 1986). They take the form
of ellipsoids, much elongated in the direction of the mean wind speed. Hence, there
are three integral length scales of turbulence corresponding to the longitudinal,
lateral and vertical fluctuating component of wind.
Reported integral scales of turbulence have displayed a large degree of vari
ability. Part of this variability is the result of the dependence of integral scales of
turbulence on terrain characteristics, atmospheric stability condition and height
above ground. Considerable variabifity also results from different computation
methods for integral scales (Teunissen, 1980). In general, the sizes of integral
scales of turbulence increase with smoother terrain and height above ground as
ground roughness distorts the formation of large eddies. They decrease slightly
with increasing atmospheric stability (Moore et al., 1985).
Mathematically, the integral scale of turbulence is the integral of the space
correlation function. But the measurement of wind speeds at various spatial lo
cations are not always possible. Subject to the validity of Taylor's hypc>thesis.
the observed time correlation function at a point can be interpreted as the space
correlation function along the mean wind direction. Taylors hypothesis has ini-
phed that for homogeneous turbulence, if the square of mean wind speed is much
greater than the variance of wind speed (U^ > > a-'), the lime correlation functic»n
can be converted into space correlation function as follows (Taylor. 193S) :
15
X = U t (2.7)
where X = the distance along mean wind direction,
U = the mean wind speed, and
t = the time.
Taylor's hypothesis implies that the turbulence field can be considered as
'frozen' in space and time, and travels past a point with velocity U. The variation
of (T^ with time when the turbulence is viewed from a stationary point is the
same as the variation observed from a point moving across the 'frozen field' with
velocity U in the negative mean wind direction. Lappe and Davidson (1963), had
shown that the Taylor's hypothesis is valid for wavelength ranging from at least
600 to 900 ft as mean wind speed varies from 20 to 30 fps respectively. Panofsky
and Dutton (1984) also suggested that Taylor's hypothesis is valid for weakly
stationary wind data. In this project, the mean square of wind speed, U^ can be
as low as 400 mph squared (mean wind speed of 20 mph) and the variance, cr
can be as high as 25 mph squared (root mean square value of 5 mph). Hence,
the mean square value is at least 16 times greater than the variance value and
it is assumed to satisfy Equation (2.7). As a result, the Taylor's hypothesis is
assumed to be valid.
The validity of Taylor's hypothesis has important consequences for statistical
analysis. The mean and variance measured in time must equal to those measured
in space. Similarly, the autocorrelation function, PS{T) in space and px[''') in
time must be equal. The longitudinal integral scale of turbulence can hence be
estimated as a product of mean wind speed and time scale measured at a point.
The time scale characterizes the average duration of the effect of eddies at a point
16
(ESDU, 1974). It is the area under the autocorrelation function curve of a time
series.
The longitudinal integral scale of turbulence can be represented as follows :
Lx = \] 1°° p(r)dr (2.8)
where Lx = the longitudinal integral scale of turbulence,
U = the mean wind speed, and
p{r) = the autocorrelation function at lag, r.
There are four different methods to evaluate the longitudinal integral scale of
turbulence. The methods are :
1. The direct integration of autocorrelation function method (Teunissen, 1979).
This approach is quite sensitive to the oscillatory behavior of the aotucor-
relation function. A cutoff value is required of time lag.
2. The spectral method (Teunissen, 1979). This method uses the frequency,
fmax at which the power spectrum is the maximum. The product of the
mean wind speed and the inverse of fmax is the longitudinal integral scale of
turbulence.
3. The exponential function method (Teunissen, 1979). This approach assumes
an exponential function. The lag time at which the autocorrelation function
is equal to 1/e (0.368) is multiplied by the mean wind speed to get the
longitudinal integral scale of turbulence.
4. The direct integration of a best fit function method (Mackey and Lo. 1975).
rhe best fit function is usually an exponential function.
Different values of longitudinal integral scale of turbulence at 10 m computed
using different methods by several investigators are shown in Table 2.2. A vari
ation of the values is observed for different terrains and different computation
methods.
18
Table 2.2 Longitudinal Integral Scale of Turbulence at 10 m
Reference
Choi (1978)
Duchene-Marullaz (1975)
ESDUt (1975)
Mackey &
Lot (1975)
Setheraman (1979)
Shiotani Sz Iwatanif (1979)
Teunissen (1979)
Terrain
Coastal area
Suburban
Flat & open
Sea
Sea
Sea Flat & open
Flat & open
Method 1
75 m
70 m
116 m
195 m 135 m
130 m
Method 2
• • •
62 m
Method 3
o • •
. . .
124 m
Method 4
190 m"
• • •
210 m
. . .
* Typhoon wind. t from longitudinal integral scale of turbulence model.
CHAPTER III
METEOROLOGICAL TOWER
INSTRUMENTATION
The National Science Foundation has sponsored a project to acquire wind
pressure data on a low-rise building. A 30 x 45 x 13 ft rotatable metal building, a
1 0 x 1 0 x 8 ft data acquisition room on a concrete slab and a 160 ft meteorological
tower are constructed for this project. Figure 3.1 shows the field test facihty
and surrounding terrain. Wind pressures will be measured on the surface of the
rotatable metal building and wind data will be measured on the tower. The data
acquisition room located inside the metal building houses the data acquisition
system.
The purpose of the field experiment is to acquire reliable wind and pressure
data. The field data will assist in further in-depth study of building pressures
in wind tunnels. The Lubbock, Texas, area is an appropriate site for this field
experiment because of its wide open and flat terrain and frequent strong winds.
Wide open and flat terrain minimizes the possible anomalies in wind parameters
caused by the terrain. Frequent strong winds occur in Lubbock, especially in
Spring months. The National Weather Service station in Lubbock recorded wind
speed of at least 20 mph for 864 hours in 1981. Wind speeds higher than 20 mph
are considered to have reasonable effects on structures.
Field Site and Terrain
Lubbock is located on the High Plains of Texas at an elevation of about 3300
ft. The surrounding terrain in Lubbock is extremely flat. There are no hills or
19
21
valleys within the 20 mile radius of the city. Most of the surrounding land is used
for growing cotton and sorghum. The rest of the land is sparsely populated with
semi-arid vegetation such as short grasses and mesquite trees.
The field site is on the land owned by Texas Tech University. The field test
facihty is on the Antenna Farm, south of 4th Street and half way between Indiana
Avenue and Quaker Avenue as shown in Figure 3.2. General description of the
terrain surrounding the field test facihty is given below.
Northeast Terrain
There are residential areas more than 4000 ft away in the azimuth range of 0°
to 80°. The area north of 4th Street in this direction, as shown in Figure 3.3 is
used for growing cotton which is about 2 to 3 ft tall during summer months. The
rest of the area is populated with short grasses.
Southeast Terrain
A few big structures are located in the southeast direction as shown in Figure
3.4. A 103 ft tall hospital is 1500 ft away in the azimuth range of 100° to 120°.
The closest structure to the field facility is a 15 ft tall dome-shaped observatory.
It is 200 ft away from the tower at an azimuth of 120°. A power plant in the
azimuth range of 130° to 140° is 1400 ft away. These structures can cause some
interference to the wind flows coming from the southeast.
Southwest Terrain
Residential areas begin 2000 ft away in the azimuth range of 180° to 260°. A
10 X 8 X 8 ft power supply shack is 250 ft away at an azimuth of 180°. A larger
25
building, 28 x 28 x 26 ft, used for electrical engineering research at an azimuth
of 200° is 250 ft away. There are a few 50 ft high utihty poles around the two
buildings. A large playa lake is about 800 ft away in the azimuth range of 200° to
230°. The playa lake is 800 ft long in the north-south direction and has a width
of 500 ft in the east-west direction. The water surface elevation of the lake is 15 ft
lower than the field test facility elevation. The elevation difference may increase
by another 10 ft during the summer months when the lake dries up. Figure 3.5
shows the southwest terrain.
Northwest Terrain
The northwest terrain is open and flat. Three large ponds forming a 600x800
ft rectangle are 2200 ft away in the azimuth range of 330° to 360°. The rest of
the areas north of 4th Street are sparsely populated with 3 to 5 ft tall mesquite
trees. Figure 3.6 shows the northwest terrain.
Meteorological Tower
The meteorological tower is 160 ft high. It is a three-legged truss tower. The
legs are 1.5 ft apart forming an equilateral triangle. The tower are supported by
two sets of guy wires, located at heights of 70 and 130 ft. The guy wire locations
are designed not to interfere with the wind flows measured by instruments at
various levels of the tower. Safety chmb system is installed on the tower for the
safety of the personnel.
The tower is located 150 ft west of the test building. This distance allows the
guy wire anchors which are 104 ft away from the tower, to be kept at a distance
from the test building. The closest guy wire anchor is 10 ft southwest of the
28
edge of the test building. Possible interference of the guy wires to the wind flows
around the test building is minimized.
Instrument Boom
Three retractable booms are placed on the tower at the 13, 33 and 70 ft levels.
These booms are custom made for this project. Each boom is constructed of a
steel square tube. It is supported by two aluminum angles to increase the stabihty
of the boom. Figure 3.7(a) shows the instrument boom and its supports. The
boom is instaUed inside a larger steel square tube which is welded to the tower.
RoUer bearings are mounted on the outer tube for ease of moving the boom
toward or away from the tower. The distance from the side of the tower to the
end of the boom where instruments are mounted, is 6 ft. This distance assures
the interference of the tower to the wind flows around the instruments will be
negligible except for winds from the direction of the tower. No boom is mounted
on the top of the tower since the wind instruments are 2 ft above the tower. The
interference of the tower on wind flow 2 ft above the tower is considered negligible.
All the booms mounted on the tower are aligned toward the azimuth of 300°.
This orientation provides a favorable exposure for the wind instruments to the
winds from south, west and north. Wind flows through the tower can be reduced
by the legs of the tower by as much as 40% (Carter. 1970). Wind flows that can
be affected by the tower is in the range of 40° on either side of the direction of
the boom. For this project, the possible affected wind flow is in azimuth range of
80° to 160°.
29
(a)
160 FT—1 S.D.T
130 FTvfGLrys
70 F T -
33 F T -
13 F T -
/5 , S
QLWS
S.D
S.T.H.P
LEGEND
S WIND SPEED
D WIND DIRECTION
T TEMPERATURE
H RELATIVE HUMIDITY
P BAROMETRIC PRESSURE
(b)
Figure 3.7 Meteorological Tower (a) Instrument Boom, and (b) Instruments on the Tower
30
Instrumentation
Meteorological instruments are mounted on the tower at four levels : 13, 33,
70 and 160 ft. Horizontal wind speeds are measured at all four levels. Three levels
of wind speeds are the minimum requirement for obtaining a good wind profile.
An extra level of wind speed plays an important role of backup in case one of the
anemometers breaks down. Wind directions are measured only at 33 and 160 ft
levels since the variation of mean wind direction over 160 ft is not large (Simiu
and Scanlan, 1986). Two levels provide credibifity in measurement through cross
check of wind direction. Measurements of the ambient absolute temperature at 13
and 160 ft levels give the differential temperature. The differential temperature
can be used to determine atmospheric stability. Relative humidity and barometric
pressure are measured at 13 ft level for determining air density. The air density is
used to estimate wind pressure exerted on the test building surfaces. Figure 3.7(b)
shows the instrumentation at different levels of the tower. All signals from the
instruments are brought down to the data acquisition room through the shielded
cables that are buried in a trench. Specifications of each of the instruments are
given below.
Horizontal Wind Measurement System
The horizontal wind measurement system consists of a wind speed instrument,
Gill 3 cup anemometer model 12102: a wind direction instrument. Gill Microvane
aluminum vane model 12304; and a translator model 04409. All of them are
supphed by R. M. Young. Figure 3.8 shows the anemometer and wind vane
mounted at 33 ft level.
32
The anemometer has a threshold speed of 0.9 mph and a distance constant
of 8.9 ft. The distance constant is the length of air that is required to pass the
anemometer to cause it to respond to 63.2% of the step function change in speed
(Gill and Hexter, 1972). As shown in Figure 3.9, the three cup anemometer never
overestimates the gust ampHtude. The anemometer can measure at least 90% of
the ampHtude of the sinusoidal gust if its wavelength is 32.5 m (107 ft) or greater.
The maximum range of the anemometer is 112 mph. The DC tachometer
generator in the anemometer produces analog voltage directly proportional to
wind speed. The translator filters and calibrates the analog signals from 0 to 1
volt to be directly proportional to 0 to 100 mph. A 25 volt. 1000 microfarad
capacitor can be used to replace the translator. The capacitor has the same
function as the translator to filter and calibrate the analog signal from 0 to 4
volts to be directly proportional to 0 to 106 mph.
The wind vane has a threshold wind speed of 0.9 mph for a 10° initial deflec
tion. It has a delay constant of 3.6 ft. Delay constant is the length of air that
passes a wind vane for it to respond to 50% of a sudden angular change in wind
direction (MacCready and Jex, 1964). The wind vane has a tendency to over
shoot the actual wind direction when it is subjected to a sudden shift in direction.
Figure 3.9 shows the dynamic response curve of the aluminum wind vane that
overshoots the actual gust amplitude by as much as 30%. The damping ratio of
the wind vane helps to reduce the overshoots, hence improving the accuracy of the
measurement. This wind vane has a damping ratio of 0.42 which is high enough
to damp out the second overshoot. Gill and Hexter (1972) have suggested that a
damping ratio in the range of 0.35 to 0.70 is required for diffusion and turbulence
studies where the standard deviation of the azimuth angle is used.
33
1.40
1.20
!< 1.00 DC LU Q D
IE <
.80
.60
.40
/
GILL MICROVANE AND 3 CUP ANEMOMETER AMPLITUDE RATIO VS GUST WAVELENGTH
FOR SINUSOIDAL FLUCTUATIONS
10 15 20 25 30 35 40
GUST WAVELENGTH - METERS 45 50
Figure 3.9 Dynamic Response of 3 Cup Anemometer and Wind Vane Supplied by R. M. Young Company
34
The wind direction signal is from a precision linear conductive plastic type
potentiometer which provides an analog output signal of 0 to 1 volt directly
proportional to the angle of 0° to 360°. The potentiometer requires a constant
excitation voltage suppHed by a translator. The operating range of the wind vane
is from the angle of 0° to 355°; the potentiometer has a dead band of 5°.
Because the measurements from north are important for this project, the 0°
of the wind vane is aHgned to the field azimuth of 120°. This azimuth is in Hne
with the boom. Thus the dead band of the instrument is located in the directions
where wind data are not usable in this project.
Temperature Measurement System
The temperature measurement system, supplied by Teledyne Geotech, consists
of a platinum temperature sensor, a wind aspirated thermal radiation shield and
a processor. Two different temperature sensors are used. For temperature mea
surement at 13 ft level, a relative humidity/platinum temperature sensor model
RH-200 (capable of measuring both relative humidity and temperature on one
probe) housed in a wind aspirated thermal shield model WAS-300 is used. A
calibrated platinum temperature sensor model T-200 housed in a wind aspirated
thermal radiation shield model WAS-100 is used to measure temperature at 160
ft level. Signals from each sensor is processed by a temperature processor model
10.32. Table 3.1 shows the specifications of the temperature sensors.
Both temperature sensors are platinum resistance temperature sensors. This
resistance sensor measures the electrical resistance of the platinum which increases
non-linearly with increase in ambient absolute temperature. The non-linear signal
is linearized by the temperature processor.
35
Table 3.1 Specifications of Temperature Sensors
Model
T-200
RH-200
Range
-58° to 122°F
-40° to 115°F
Accuracy
±0.1°F
±0.2°F at 32°F
Time Constant
45 sec
10 sec"
* reported as response time.
36
The temperature processor regulates the excitation voltage to the sensor. It
also filters, conditions, amplifies and linearizes the non-Hnear signals so that 0
to 5 volts is directly proportional to -58° to 122°F. The processor's accuracy is
±0.1°F for operating temperature of 77° ~ 9°F. The accuracy decreases to i0 .2°F
outside the operating range.
The wind aspirated thermal radiation shield acts as an effective shield to
temperature sensor against the effects of solar and terrestrial radiation. Direct
exposure of the sensor to the radiation will cause the sensor to give incorrect
ambient absolute temperature.
Relative Humidity Measurement System
The relative humidity measurement system, supplied by Teledyne Geotech. is
a combination of a relative humidity/platinum temperature sensor model RH-200
housed in a wind aspirated thermal radiation shield model WAS-300 and a relative
huniidity processor model 10.41/33. The RH-200 sensor and WAS-300 shield are
also used to measure temperature at 13 ft level as mentioned previously.
The relative humidity sensor has a measuring range of 0 to 100% relative
humidity and a response time of 5 seconds. The accuracy of the sensor is ±2%
from 0 to 80% and ± 3 % above 80% relative humidity.
The relative humidity processor regulates the excitation voltage to the sensor.
The signal is filtered, conditioned and amphfied to a gain of 50 . \'oltage signal
of 0 to 5 volts is directly proportional to 0 to 100% relative humidity.
Barometric Pressure Measurement System
The barometric pressure measurement system consists of a barometric pressure
sensor model BP-lOO and a barometric pressure processor model 10.22/61. Both
the sensor and the processor are suppHed by Teledyne Geotech.
The BP-lOO has a range of 24.3 to 31.5 in Hg which covers ah normal range
of absolute barometric pressure in the Lubbock area. The average absolute baro
metric pressure in Lubbock is 27 in Hg. The BP-lOO has a resolution of 0.15% of
the range span which is 0.01 in Hg.
The processor regulates excitation voltage to the sensor. It also filters and
conditions the output signal. No amplification of signal is involved since the
output signal of 0 to 5 volts is directly proportional to 24.3 to 31.5 in Hg.
Data Acquisition System
The data acquisition system samples the instrument signals in term of voltage
and converts the analog signals to digital signals. The digitized data are stored
in appropriate form for future analysis. The data acquisition is controlled by an
IBM PC XT computer housed in the data acquisition room.
Analog instrument signals are converted to digital form using a MetraByte
DAS-8 analog/digital convertor. This DAS-8 has the capability of converting
signals at a rate of 4000 Hz through eight input channels. Each input channel
is expanded to sixteen channels using MetraByte Universal Expansion Interface
board, EXP-16. The EXP-16 is an expansion multiplexer and amplifier system
that provides signal amplification, filtering and conditioning. With the use of
eight EXP-16, the system can be expanded to a maximum of 128 channels. Four
EXP-16 are used to provide 64 channels of data for this project.
38
Software acquired from Laboratory Technologies Corporation, LABTECH
NOTEBOOK, is the key to the data acquisition system. LABTECH NOTE
BOOK is a user-friendly software that aHow different channels to be set up with
different characteristics. It also allows real time display of the incoming data
which is very helpful for caHbration of the instrumentation.
The software can be set to trigger automatically when the wind speed reaches
a preset threshold level. Once triggered, the system is programmed to sample
data at a rate of 10 Hz for all meteorological channels except relative humidity
and barometric pressure channels which are sampled at 1 Hz. for a continuous
period of 15 minutes. After completing one record, the one minute average wind
speed is checked and another recording begins if the wind speed is still above
the threshold level. The records collected for this study are triggered manually.
Automatic triggering system is still being setup at this writing.
Once the data are sampled and digitized, they are streamed directly to a 20
megabyte BernoulH removable cartridge drive by the LABTECH NOTEBOOK.
This streaming ehminates the limitation imposed by the computer memory to the
duration of each record. Each removable cartridge can store a few hours of data.
The removable cartridge is brought back to Texas Tech University campus
and uploaded to the DEC \ AX-8650 computer. The uploading process is made
possible by the MS-Kermit software which is controlled by an IBM Personal Sys
tem/2 model 60 computer. All uploaded data are stored in magnetic tapes for
future analysis.
CHAPTER IV
CALIBRATION OF METEOROLOGICAL
INSTRUMENTS
All the meteorological instruments are purchased off the shelf from two com
panies, R. M. Young and Teledyne Geotech. They have been checked and certified
by the manufacturers to be in good working condition. However, it is the respon
sibility of this field experiment research team to verify the accuracy and field
applicability before using them in the field.
Meteorological instrument records the meteorological parameters and gives out
the output in terms of electrical signal. A controlled meteorological parameter
such as wind speed in wind tunnel, can be measured simultaneously by the new
meteorological instrument and at least one other dependable instrument. The
results of both instruments are compared to verify the new instrument.
Anemometers, wind vanes, and temperature, relative humidity and barometric
pressure sensors are tested in the laboratory and in the field wherever possible.
Effect of the cable length on the electrical signal is also checked in the laboratory.
Anemometer
The accuracy of the anemometers is checked in the 3x4 ft wind tunnel located
in the mechanical engineering department. The anemometer is mounted on a
tripod and is placed in the center of the cross-section of the wind tunnel. A pitot-
static tube is placed at the same height but 10 inches beside the anemometer. This
arrangement assures both instruments experience the wind flows with minimum
interference of the wind tunnel's walls.
39
40
Three different wind tunnel speeds that are representative of the expected wind
speed in the field are used to test the anemometers. The pitot-static tube provides
the reference wind speed in the wind tunnel. Wind speed of the anemometer is
recorded at 10 Hz by the same data acquisition system that wih be used in the
field. Table 4.1 shows the mean wind speeds recorded by four anemometers at
three different wind speeds. The reference wind speeds recorded by the pitot-stalic
tube are slightly higher than the mean wind speeds recorded by the anemome
ters. The difference is approximately 3%. The difference is considered acceptable
because the mean wind speeds recorded by the four anemometers are very close
to each other. The variation among the anemometers in the recorded speeds is
within the range of 0.1 to 0.3 mph which corresponds to less than 1% of the mean
speed.
Electrical signal of the anemometer can be checked for accuracy using a com
mercial calibrator. The calibrator is a motor with constant speed of 1800 rpm.
A rubber tubing connects the shaft of the anemometer to the calibrator. The
anemometer cup has to be removed when using calibrator. Rotation of the
anemometer shaft at 1800 rpm corresponds to wind speed of 63.9 mph. All the
ariemometers have been tested with the calibrator in the laboratory and in the
field. Anemometer mounted at 13 ft level can be tested in the field. Anemome
ters for the 33, 70 and 160 ft levels are brought down and mounted at 13 ft
for calibrator test. Results of the caHbrator tests are shown in Table 4.2. Both
the laboratory and the field test results indicate that the electrical signal of the
anemometers correspond to slightly less than the expected wind speed. The dif
ference however is small, less than 1%.
41
Table 4.1 Results of Anemometer Test in Wind Tunnel
Instrument
Anemometer 1
Anemometer 2
Anemometer 3
Anemometer 4
Pitot-static tube
Low Wind Speed (mph)
20.5
20.6
20.5
20.6
21.3
Medium Wind Speed (mph)
33.2
33.3
33.3
33.3
34.2
High Wind Speed (mph)
45.9
46.2
46.1
46.2
47.1
Table 4.2 Results of Anemometer Test with Calibrator
Instrument
Anemometer 1 (At 13 ft)
Anemometer 2 (At 33 ft)
Anemometer 3 (At 70 ft)
Anemometer 4 (At 160 ft)
Expected from calibrator
Laboratory Test (mph)
63.5
63.8
63.6
63.7
63.9
Field Test-(mph)
63.3
63.3
63.7
63.5
63.9
* tested at 13 ft,
42
The caHbrator test results show noticeable fluctuations in the electrical signal.
The fluctuations are found to be equivalent to the turbulence intensity of 1.5% at
mean wind speed of 63.9 mph. This fluctuation in signal is probably due to noise
of the DC generator in the anemometer.
Both the wind tunnel and caHbrator tests of the anemometers show that the
anemometers are in good working condition. The accuracy of the anemometers
is satisfactory.
W ind Vane
The balance, range and accuracy of the wind vanes have been tested in the
laboratory before mounting them on the tower. The vane balance is tested easily
by laying the vane on its side on a table. The vane shaft which has a counterweight
at one end and a fin at the other end, is free to rotate. A balanced vane would
let the shaft remain horizontaUy and will not have tendency to change position.
Both the wind vane instruments are found to be balanced.
The range and accuracy of the wind vane instruments are tested by connecting
the wind vane with the signal conditioning translator to the field data acquisition
system. To check the operating range, the wind vane is rotated through a complete
revolution. Data collected during the rotation show that the operating range is
from 0° to 355°. Angle in the range of 356° to 360° is dead band (zero signal).
The accuracy of the wind vane is tested by aligning the wind vane with known
angles. The known angles are sketched on a transparency with the angles of 0°,
45°, 90°, 135°, 180°, 225°, 270° and 315°. The 0° angle on the transparency is
aligned with the 0° angle of the wind vane. Once the 0° angle is estabHshed, the
wind vane is rotated and aligned with the next angle on the transparency. The
43
angle on the visual display is recorded. This process is repeated for aU the angles
on the transparency. The visual display results show that the deviations of the
wind vane angles are within ±4° of the angles on the transparency. The difference
can be due to the resolution of the visual display and the difficulty in aligning
the wind vane with the transparency. Since the electrical signal from the vane is
found to be Hnear from 0° to 355°, the wind vane is considered to provide desired
accuracy.
Temperature Sensor
The accuracy of the two temperature sensors, T-200 and RH-200 are checked
against a mercurial thermometer and a Weathertronics model 4480 temperature
sensor. The mercurial thermometer and the Weathertronics sensor have the ac
curacy of ±1°F and ±0.1°F respectively.
Temperature readings from T-200 and RH-200 sensors are recorded by the field
data acquisition system at a sampling rate of 10 Hz. The output signal of the
Weathertronics sensor is indicated by a digital voltmeter and recorded by hand.
Temperature of the mercurial thermometer is monitored visually and recorded
immediately after sensors' temperature readings are recorded.
To test the upper range of the sensors, all three sensors and the thermometer
are placed in an oven. Data is collected only when the sensors reach a steady state
temperature. The sensors are also tested at room temperature, near freezing and
below freezing temperatures. It is observed that the sensors take about 20 to 30
minutes to reach a steady state temperature of the environment.
Results of the laboratory tests are tabulated in Table 4.3. Temperature read
ings at 104°, 74° and 44°F recorded by the sensors and thermometer are very
44
Table 4.3 Laboratory Test Results of Temperature Sensors
Date
12/12/87
12/12/87
12/12/87
12/12/87
Mercurial Thermometer
(°F)
104
74
44
6
Weathertronics model 4480
(°F)
104.1
73.2
44.2
6.5
T-200
(°F)
104.2
73.3
44.5
5.7
RH-200
(°F)
104.6
73.3
44.4
7.0
45
close. The difference between the T-200 and RH-200 readings are within the
sensor accuracy and possible temperature processor error. Results of the temper
ature readings at 7°F show some variation. The reason of this variation at low
temperature is not known. However, the variation in temperature recordings at
below freezing temperature of 7°F is not critical in this project because strong
winds are not likely to occur during this low a temperature.
Field test of the T-200 and RH-200 sensors are also carried out with the same
mercurial thermometer used in the laboratory test. The atmospheric stabihty
condition on the test day is assumed to be stable since there was almost no wind.
It was expected that the temperature difference between 13 and 160 ft levels
would be less than the dry adiabatic rate, that is less that 0.8°F. The recordings
are taken after the thermometer is held in the shade for 10 minutes. The results
of the field tests are tabulated in Table 4.4. The temperature readings of the
mercurial thermometer at 13 and 160 ft levels are the same. The reason is the
inability of thermometer to measure the sHght temperature difference between
the two levels. The thermometer readings are not close to the readings of the
sensors. Also, there is a 2° and 4°F difference between the two sensors' readings.
The difference is much greater than the expected temperature of less than 0.8°F.
This difference in recordings by the sensors suggest that the instruments are not
usable to assess atmospheric stabihty. Additional field calibration and checking
are necessary before using the temperature readings to assess stability of the
atmosphere.
46
Table 4.4 Field Test Results of Temperature Sensors
Date
6/14/88
6/14/88
Mercurial Thermometer
(°F)
68-
83-
T-200 (At 160 ft)
(°F)
64.3
81.3
RH-200 (At 13 ft)
(°F)
66.6
85.4
* same temperature measured at 13 and 160 ft.
47
Relative Humidity Sensor
The laboratory test of the relative humidity sensor, RH-200 is to check the
range of the sensor. The RH-200 sensor is placed in the humidity room which
is believed to have close to 100% relative humidity (RH). The output signal is
indicated by a voltmeter and recorded by hand. The laboratory RH during the
test is 23%. Once the sensor is placed in the humidity room, an increase of RH is
noticed. The final humidity room RH is 96%. It is therefore concluded that the
operating range of the RH-200 sensor is at least 23% to 96% RH.
Another RH sensor is not available to check the accuracy RH-200 sensor in the
laboratory. One way of checking the accuracy of the sensor in the field is to com
pare RH measured by RH-200 with the RH measured by the National Weather
Service station at the Lubbock International Airport, about 7 miles from the test
site. The RH-200 sensor is mounted on the tower at 13 ft level. The output
is indicated by a digital voltmeter and recorded by hand. The RH reading is
recorded at the beginning of the hour when the National Weather Service up
dates weather information. Table 4.5 shows the field test results. The maximum
difference between RH-200 and National Weather Service measurements is 5%
RH. A difference of 5% in RH is considered acceptable because it has negligible
effect on the density of air.
Barometric Pressure Sensor
The barometric pressure sensor, BP-lOO, is checked ageiinst a barometer pres
sure sensor, Weathertronics model 71101 and a mercurid barometer. The mercu
rial barometer is located in mechanical engineering laboratory, which is about 200
ft away from the laboratory test location. Signals from the BP-lOO is recorded
48
Table 4.5 Test Results of Relative Humiditv Sensor
Date
12/12/87
12/12/87
12/13/87
12/13/87
National Weather Service (% RH)
36
57
75
25
RH-200 (% RH)
32
56
70
23
49
by the field data acquisition system at a sampUng rate of 1 Hz. A voltmeter is
used to indicate the signal from the Weathertronics barometric pressure sensor.
The mercurial barometer reading is recorded after the completion of the data
collection of two sensors. Results tabulated in Table 4.6 show that the difference
between BP-lOO and Weathertronics sensor readings is 0.01 in Hg. The mercurial
barometer readings are 0.04 to 0.07 in Hg higher than the sensors' readings. The
close results of the BP-lOO and Weathertronics sensor readings give the assurance
that the BP-lOO sensor is in good working condition.
Cable Effect
Two different cables are used for the tower instruments. Signals from wind in
struments are carried by multi-conductor cables. Shielded multi-conductor cables
are used for carrying signals from temperature, relative humidity and barometric
pressure sensors. The conductors for both cables are 20 gage. Effect of the cable
length on electrical signal is tested for both cables.
The length of the cable reduces the electrical output signals from the instru
ments. The effect can be checked by supplying a known input voltage to one end
of the cable and measuring the output voltage at the other end of the cable. The
difference between the input and output voltage is the voltage reduction caused
by the resistance of the cable. Two different lengths of cable, 50 and 375 ft are
used in the tests. The 375 ft is the length of the cable for instruments located at
160 ft level of the tower. The test results indicate that the input voltage is equal
to the output voltage with an accuracy of 0.001 volt. This voltage is equivalent
to wind speed of 0.1 mph, wind direction angle of 0.4° and temperature of 0.04°F.
Thus, the length effect of the cable is within the acceptable tolerance.
50
Table 4.6 Test Residts of Barometric Pressure Sensor
Date
12/11/87
12/12/87
12/13/87
Mercurial Barometer
(in Hg)
26.78
26.80
26.61
Weathertronics sensor (in Hg)
26.74
26.77
26.54
BP-lOO (in Hg)
26.73
26.77
26.55
CHAPTER V
ANALYSIS OF FIELD DATA
One of the objectives of this study is to assess the wind parameters of Texas
Tech University field site from field wind data. A total of 63 sets of field wind data
are collected during the period from February to April, 1988. Different weather
conditions are encountered during this data collection period. The weather con
ditions include cold front, thunderstorm and gusty blowing dust. Table 5.1 shows
the summary of all the data sets. Each set of data consists of four wind speed
records collected at 13, 33, 70 and 160 ft levels; two wind direction records col
lected at 33 and 160 ft levels; and two temperature records measured at 13 and
160 ft levels. Each record is collected at 10 Hz over a continuous period of 15
minutes. The first 24 sets of wind speed data are collected with translators for
33 and 160 ft level anemometers, and the other two records are collected with
capacitors. The rest of the wind speed sets are collected with four capacitors.
A statistical analysis of the data is presented here. Time histories of the
wind records are plotted for visual inspection. Descriptive statistics of the wind
records are also calculated for validation of data. Stationarity of the wind speed
and wind direction records are checked. Neutral atmospheric stability condition
during the time of data collection is assumed to exist when the mean wind speed
at 33 ft level exceeds 20 mph. Only stationary records that are in neutral stability
condition are used for analysis. Analysis of the wind records include wind profile
parameters, turbulence intensity and longitudinal integral scale of turbulence.
The wind profile parameters are used to characterize the field terrain. Results of
the analysis are presented.
51
52
Table 5.1 Summary of the Wind Data Set
Set-
AOl A02 A03 A04 A05 A06 A07 A08 A09 AlO Al l A12 A13 A14 A15 A16 A17 A18 A19 A20 A21 A22 A23 A24 A25 A26 A27 A28 A29 A30 A31 A32
Date
2/17/88 2/17/88 2/17/88 3/02/88 3/02/88 3/02/88 3/02/88 3/02/88 3/02/88 3/06/88 3/06/88 3/07/88 3/07/88 3/07/88 3/07/88 3/07/88 3/10/88 3/10/88 3/10/88 3/10/88 3/10/88 3/10/88 3/10/88 3/10/88 3/10/88 3/10/88 3/11/88 3/11/88 3/11/88 3/11/88 3/11/88 3/11/88
Weather Condition
Cold front Cold front Cold front Cold front Cold front Cold front Cold front Cold front Cold front Blowing dust Blowing dust Cold front Cold front Cold front Cold front Cold front Blowing dust Blowing dust Blowing dust Blowing dust Blowing dust Blowing dust Blowing dust Blowing dust Blowing dust Blowing dust Cold front Cold front Cold front Cold front Cold front Cold front
Mean Wind Speed at 33 ft (mph)
24.8 23.5 22.4 27.6 29.4 29.2 29.4 30.7 29.8 19.3 18.3 20.9 23.2 27.6 24.2 23.4 27.6 24.4 27.1 27.5 27.8 27.0 25.8 25.6 26.3 24.2 23.7 31.4 26.9 27.0 28.1 26.0
Mean Wind Direction at 33 ft (azimuth)
025 028 029 345 350 345 345 346 343 175 178 006 004 Oil 002 359 237 225 219 223 230 231 228 228 229 228 245 243 271 289 287 289
* each set is 15-minute duration.
53
(
Set"
A33 A34 A35 A36 A37 A38 A39 A40 A41 A42 A43 A44 A45 A46 A47 A48 A49 A50 A51 A52 A53 A54 A55 A56 A57 A58 A59 A60 A61 A62 A63
Date
3/11/88 3/11/88 3/11/88 3/16/88 3/16/88 3/16/88 3/17/88 3/17/88 3/17/88 3/17/88 3/17/88 3/17/88 3/17/88 3/24/88 3/24/88 3/24/88 3/24/88 3/24/88 3/27/88 3/27/88 3/27/88 3/27/88 3/27/88 3/27/88 3/27/88 3/31/88 3/31/88 3/31/88 3/31/88 4/09/88 4/09/88
Weather Condition
Cold front Cold front Cold front Blowing dust Blowing dust Blowing dust Cold front Cold front Cold front Cold front Cold front Cold front Cold front Blowing dust Blowing dust Blowing dust Blowing dust Blowing dust Thunderstorm Thunderstorm Thunderstorm Thunderstorm Thunderstorm Thunderstorm Thunderstorm Thunderstorm Thunderstorm Thunderstorm Thunderstorm Cold front Cold front
Table 5.1 continued)
Mean Wind Speed at 33 ft (mph)
26.7 26.5 27.0 27.1 28.4 23.5 24.3 27.0 27.1 27.6 27.2 26.4 25.7 28.0 28.5 29.0 26.0 25.8 22.4 21.4 24.6 25.2 31.6 32.7 26.8 35.8 35.0 34.3 29.6 25.2 23.8
Mean Wind Direction at 33 ft (azimuth)
289 285 280
X
X
X
352 354 353 352 359 356 359 308 313 318 322 316 170 172 178 187 197 207 201 045 038 043 048 030 023
* each set is IS-minute duration. X wind direction fluctuating about azimuth 120
54
Time History
The first step in time series analysis is to plot the time history of the record.
A time history is a plot of observed values versus time. It is useful in detecting
discontinuities, trends and patterns.
Time histories of all the wind speed and wind direction records are plotted
by averaging over every 10 points (1 second average). Descriptive statistics such
as mean, root mean square, maximum and minimum values are also calculated
during the plots. The mean and root mean square lines are also plotted on the
time history for the ease of visual inspection.
Visual inspection of the wind speed time history indicates that every set of
wind speed (four records) has the same pattern with more fluctuations seen on
the lower level wind record than the higher level wind record. Typical wind speed
time histories at 33 and 160 ft levels are shown in Figure 5.1(a) and (b). In
the time history plots, mean wind speed and standard deviation of wind speed
values are shown. In addition, maximum and minimum values and the time of
occurrence during the record are shown. The instantaneous value is the data
point recorded at 0.1 second while the interval vdue is for 1 second average.
Some of the wind speed records collected at 33 and 160 ft levels show sudden
drop in wind speed. Examining the minimum value reveals that there is a sudden
drop in wind speed to zero or negative value. Figure 5.2 shows that there is a
sudden drop of wind speed at 4.35 minutes. Practically, it is not possible for
the anemometer to slow down from a certain high wind speed, say 20 mph, to
a low value in a spHt of a second. These unexpected values are attributed to
the processing error caused by the translator since wind speeds collected ^^ th
capacitors do not have this problem.
55 R01WS033 2-17-1988 lOiOl TTU riELO EXFCRIMO
IHST. tIflX - 37.50 INT. «W - 35.21 INST. tllN - 12.60 INT. niN • 13.01
n roR HI NPH HPM HPH nPH
« PfCSSURC
TIfC -TIfC -Tinc -TItC -
2.302 2.331 M.36S M.367
niN niN niN niN
PLOT QHTE 6-f«)T-aa
fCHN - 21.76 HM INST STO OCV - 1.IS nPM INT STO OCV • 3.97 nPM NUfI PTS/INT -10
TIfC HISTORT rOR 1.000 SECOWJ iNTCRVft. 8VDWGCS
TIME (MINUTES)
(a)
n O l W S l B O 2-17-1988 10.01 TTU riCLO EXPtRirCNT rOR MINO PRCSSURC
INST. MAX - 12.10 INT. nnx - 10.70 INST. MIN - 19.10
INT. nIN - 21.61
MPH MPH MPH MPH
TIME -
TIME -
TIME -
TIME -
12.728 MIN 12.733 MIN
11.120 MIN 11.000 HIN
PLOT OflIC - 6-Mni-88
fCHN - 30.10 MPH INST STO OCV - 3.56 MPH INT STO Kv - 3.17 rrn Nir PTS/INT -10
TIME HISTORT rOR 1.000 SECOND INIERVflL flVCRflCES
X Q_
r:
a UJ LJ D_ in a
T T 6 9
TIME (MINUTES: 12 IS
(b)
Figure 5.1 Typical Wind Speed Time History (a) at 33 ft Level, and (b) at 160 ft Level
56
n 2 1 W S 0 3 3 3-10-1988 13109 TTU FIELD EXPERIMENT FOR UINO PRESSURE
INST. MAX - 13.90 MPH
INT. riflX - 11.3S MPH INST. MIN —89.10 MPH INT. MIN - 8.98 MPH TIME HISTORT FOR 1.000
TIME -TIME -TIME -TIME -
12.092 MIN 12.100 MIN
1.3S0 MIN 1.3S0 MIN
SCCONO INTERVAL RVERflGES
PLOT OflTE - 5-MflY-88
MERN - 27.81 MPH
INST STO OEV - S.68 MPH INT STO OCV - 5.19 MPH NUM PTS/INT -10
TIME (MINUTES)
Figure 5.2 Wind Speed Record with Defected Data
57
Typical time histories of the wind direction records are shown in Figure 5.3.
The time history of wind direction at 160 ft level is smoother than that at 33 ft
level as seen in the figure. Some wind direction time histories also show a sudden
change in value. Figure 5.4 shows distinct sudden changes in wind direction val
ues. The explanation for this sudden change is the malfunction of the translator.
It is also noticed that no sudden drop in wind direction value occurs after set A24
when the wind speeds are no longer processed by translators.
Three sets of wind direction time histories show a drastic increase or decrease
in wind direction value at the azimuth of 120°. The reason is that the time history
program is not designed to wind direction fluctuating about the azimuth of 120°
(0° of the wind vane). This is not a concern since the wind flow from this direction
is disturbed by the buildings and the tower legs as well as the dead band of the
wind vane is in this direction. It is therefore decided not to use wind data from
this direction.
Visual validation of the wind data has eHminated 10 sets of data. Five sets are
rejected because of translator malfunction and three sets are due to the unusable
direction. The other two sets of data are eHminated because the mean wind speeds
at 33 ft level are less than 20 mph and they are assumed to be in non-neutral
stabihty condition. The remaining data sets that pass the visual validation are
checked for stationarity.
Stationarity
A stationary record means that the statistical properties are invariant of time.
Current statistical and structural response analytical procedures only apply to
stationary records. Before any analysis can be proceeded, stationarity of the wind
58 n25WD033 3-10-1988 ,6.39 TTU riCLO CXPCHIMCNT TOR UlNO PHCSSUC
INST, nnx - 26S.O0 oca INT. HRX - 2S2.SO U.U INST, MIN - 193.00 mo I N T . niN • 201.80 OLD
PLOT OHTC TIME -TIME -TIME • TIME -
12-Mni-aa B.6S3
7.913
13.992
2.200
MIN
MIN
MIN
MIN TIME HISTORT rUR I.QUO SCCONO iNTCHVtt. HVCHRGES
"CAN - 229.92 OES
INST STO DEV - B . B S ULG
I N I STO OLV • 7 . 7 9 QCG
Nm PTs/iNi -10
6 9
TIME (MINUTES)
(a)
fl25WD160 3-10-1988 I6i39 TTU riELO EXPERIMEN
INST, nnx • 261.00 INT. MAX - 2SI.60 INST. MlN - 206.00 INT. MIN • 212.SO
T rOR HIM
OEO OEG 0E6 OEG
) PRESSUIE
TIME -TIME -TIME -TIME -
6.IS2 S.200 12.187 12.183
MIN MIN MIN MIN
PLOT OHTE - l2-nni-8l
MEAN - 230.6S OEG INST STO ttv - 7.31 OEG INT STO OEV - 6.61 OEG Ntfl PTS/INT -10
TIME HISTORT TOR 1.000 SECONO INTERVrt. RvERflCES
'M»$f^l[
TIME (MINUTES)
(b)
Figure 5.3 Typical Wind Direction Time History (a) at 33 ft Level, and (b) at 160 ft Level
59
R 2 1 W D 1 6 0 3-I0-I900 13.09 TTU riCLO EXfERIIlCNT FOR UINO PRESSURE
INST. Mnx - 275.00 OCG TIME -
INT. Mnx - 2G6.90 OEG TIME -
INST. MIN —633.00 OEG TIME -
INT. MIN - 127.20 OEG TIME -
0.107
0.117
11.007
11.900
MIN MIN MIN MIN
PLOT oniE - I? MOT-no
MCnN - 220.09 OCG INST STO DEV - 17.99 OCG INT STO OEV - 9.80 OCG NUM PTS/INT -10
R_ TIME HISTORY FOR 1.000 SCCONO INTCRVOL nvEROGCS
CD UJ g
a
O u> •
CJ o — LJ " ct: H Q 5.
o 2Z o
ID •
O rsi —
W/W^k (Jv^ . .; v,. A .-/'"A^^^^^^ g;
-, . 1 1 1 1 . . I 3 G 9
- | , r 12 IS
TIME (MINUTES)
Figure 5.4 Wind Direction Record with Defected Data
60
sire speed and wind direction records should be checked. Both run and trend tests
used to check the fluctuation and trend of the wind speed. Only the trend test
is used to check the trend of wind direction record since a large trend will make
the mean wind direction meaningless. A trend exists when there is a sudden or
a continuous change of wind direction during the 15-minute period of the record.
The mean wind direction will not be representative of the predominant direction
as there may be more than one or no predominant direction. Hence, the mean of
the nonstationary wind direction record is not usable.
Both the run and trend tests require the record to be divided into independent
intervals. The interval size is determined by the autocorrelation function com
puted using Equation (2.2). The autocorrelation function of all wind speed and
wind direction records are calculated using 120 seconds (1200 data points) and
are plotted for visual inspection. A typical wind speed autocorrelation function
plot is shown in Figure 5.5. The autocorrelation fimction fluctuates randomly and
never dies off to exactly zero, but will reach a point where it fluctuates about zero
at very small values. The point where the autocorrelation function first becomes
zero is assumed to be the die off point. The die off point for the plot in Figure
5.5 is 40 seconds. Any point beyond the die off point has httle or no correlation.
Hence, the die off point is assumed to be the minimum independent interval size.
Autocorrelation function plots of all the wind speed records show that most
of the autocorrelation function die off in the range of 35 to 70 seconds. Some of
the autocorrelation function do not die off before 120 seconds, and those records
are more Hkely to be nonstationary. Interval sizes of 45, 56 and 75 seconds which
correspond to 20, 16 and 12 intervals in 15-minute duration records, are chosen
to check the stationarity of wind speed records. These interval sizes are similar to
61
R48WS033 3-21-1988 I6i02 TTU riELO EXPERIMENT FOR HINO PRESSURE PLOT GATE 3-JUN-88
TIME (SECONDS)
Figure 5.5 Typical Wind Speed Autocorrelation Function Plot
62
the ones used by Levitan (1988) for his master thesis work on wind data collected
in Oregon.
Wind direction autocorrelation function plots show that most of the records
do not die off in 120 seconds. The rest of them have die off points of less than
40 seconds. A time interval of 45 seconds which corresponds to 20 intervals, is
chosen to test the stationarity of the wind direction record.
Both the mean and mean square values of each interval are calculated and
tested at 95% confidence hmit using run and trend tests. The results show that
most of the mean and the mean square results of a record follow the same pattern
of stationarity or nonstationarity.
For the wind speed records, if all six tests (run and trend tests for three in
terval size each) are stationary, then the record is considered stationary. If one of
the tests shows nonstationarity, then the record is considered questionable. The
record is considered nonstationary if two or more tests of a record are nonstation
ary. Since, for the wind direction record, trend test is performed using only one
interval size, the result will be either stationary or nonstationary.
Results of the stationary tests of wind data for different weather conditions of
cold front, blowing dust and thunderstorm are tabulated in Tables 5.2, 5.3 and
5.4 respectively. They indicate that not all of the wind speed or wind direction
records of the same data set are stationary. So a question arises as to which set
of data should be considered stationary and be used for analysis. For wind speed
records, if at least three of the wind speed records of the same set are stationary,
then the set of wind speed is selected for analysis. The reason is that only three
wind speed records are needed to get a good wind profile. There is an exception
to the wind speed set that has two stationary and two questionable records. The
63
Table 5.2 Stationarity Results for Cold Front Records
Set AOl A02 A03 A04 A05 A06 A07 A08 A09 A12 A13 A14 A15 A16 A27 A28 A29 A30 A31 A32 A33 A34 A35 A39 A40 A41 A42 A43 A44 A45 A62 A63
^/
^/
y/
y/
y/
x/
V v/
V
V y/
x/ y/
y/
y/
y/
v/ v/ y/
J
Wind Speed Record WS013 WS033 WS070
S S S Q Q Q s s s s s s Q S S Q N S S S S S S S S S N N Q N
N N N s s s Q S S Q Q N s s s N N N N N N Q S S s s s s s s s s s S S Q N N N Q N N s S s s s s s s s s s s Q Q S Q S Q S S N
y/ selected for analysis. S stationary. N nonstationary. Q questionable. Bba id re cord.
WS160 S N S N S S N S N N B Q Q S Q s N N Q s Q s s N N S S s s s N s
Wind Direction Record WD033
S S S S S N S N N N
N N N S S N S N S S N N N N S S s N N S S
WD160 S S S S S S N N N N
N S N S N N S S s s s s N _N s N S S S c S S
L
64
Table 5.3 Stationarity Results for Blowing Dust Records
Set
AlO Al l A17 A18 A19 A20 A21 A22 A23 A24 A25 A26 A36 A37 A38 A46 A47 A48 A49 A50
X
X
V
x/
y/
v/ v/ x/
WS013
S N N
Q
Q s
Q N S s s
Wind Speed Record WS033 WS070
S S N N S S B B B N S B Q S N Q
S Q N N s s Q s s s
WS160
S N S B B B S B S S
Q N N S N
Wind Direction Record WD033 WD160
S S N N s s
B B B
S N B B s s N N u u u u u u S N S s N S s s s s
y/ selected for analysis. S stationary. N nonstationary. Q questionable. B bad record. . X assumed to be in non-neutral stabihty condition. U unusable wind direction.
65
Table 5.4 Stationarity Results for Thunderstorm Records
Set
A51 A52 A53 A54 A55 A56 A57 A58 A59 A60 A61
V
y/
y/
y/
y/
WS013
N
Q Q N S s N N N S s
Wind Speed Record WS033 WS070
N Q s s N N N N S S s s N N N N N N s s s s
WS160
S S N N N S N N N S S
Wind Direction Record WD033 WD160
S S N N N N S S N S N N N N N N S S S S S N
y/ selected for analysis. S stationary. N nonstationary. Q questionable.
I
66
time histories of those wind records are examined to see whether they appear to
be stationary; that is the mean and fluctuation have no obvious trend. Only three
data sets require this exception.
The criterion for selecting wind direction record is if one of the wind directions
is stationary, then the data set is used for analysis. The logic behind this is that
only one wind direction is required since both the mean wind directions do not
vary much. In some cases, all the wind speed records are stationary, but both the
mean wind direction records are nonstationary, so the time histories of the wind
direction records are examined again. If most of the trend of the wind direction
record is within one root mean square and the trend does not have a sudden
change, then the wind direction set is used. A typical example is shown in Figure
5.6, which is tested to be nonstationary, but most of the trend is within one root
mean square. So it is accepted for analysis.
The stationarity test results show that about 60% of the good frontal wind
speed sets are stationary whereas less than 50% of the thunderstorm wind speed
sets are stationary. The percentage of stationary wind speed sets for the blowing
dust condition is in between the percentage of the cold front and thunderstorm
conditions. There is no clear correlation between stationarity and weather condi
tion.
Descriptive Statistics
Mean and root mean square (RMS) values of the 31 sets of stationary wind
data are calculated. Table 5.5 shows the mean and RMS values of wind speed at
four different levels. The mean wind speed values of the same set increase with
height. The RMS value of wind speed records increases from 13 ft level to 33 ft
f 67
R52ND033 3-27-1988 tgisi TTU riELO EXPERIMENT FOR HINO PRESSURE
INST, tmx - 20S.00 OEG INT. MflX - 197.00 OEG INST. MIN - 139.00 X 6 INT. MIN - M8.70 OEG
TIME -TIME -TIME -TIME -
a.76S MIN 3.733 niN I1.20S niN 7.883 NIN
TIME HISTORT FOR 1.000 SCCONO INTERVRL RVERRGES
PLOT OflTE - l2-nRT-8e
"EflN - 172. IS OEG INST STO OEV - 8.20 K 6 INT STO XV -7 .10 KG NUn PTS/INT -10
CD LJ o .
r*
CJ LiJ
^ g-Q
Q
^ S -
R-12 IS
TIME (MINUTES)
Figure 5.6 Nonstationary Wind Direction Record
LL
!
68
Table 5.5 Mean and RMS Values of Wind Speed
Set
AOl A03 A04 A05 A07 A08 A15 A16 A17 A19 A25 A28 A31 A32 A33 A34 A35 A41 A42 A43 A44 A45 A48 A49 A50 A52 A55 A56 A60 A61 A63
Wind Speed (mph)
13 ft
22.1 19.6 24.2 25.5 25.5 26.6 21.1 20.1 25.2 24.1 23.6 28.7 24.6 23.1 23.5 23.3 23.6 23.5 24.0 23.8 23.2 22.5 25.4 22.5 22.3 18.1 27.2 28.3 29.8 25.3 20.7
Mean 33 ft
24.8 22.4 27.6 29.4 29.4 30.7 24.2 23.4 27.6 27.1 26.3 31.4 28.1 26.0 26.7 26.5 27.0 27.1 27.6 27.2 26.4 25.7 29.0 26.0 25.8 21.4 31.6 32.7 34.3 29.6 23.8
70 ft
28.5 25.6 32.0 34.1 34.1 35.8 27.9 27.2 31.1 30.4 29.7 34.7 31.0 29.4 29.8 29.4 30.2 31.0 31.5 31.3 29.7 29.1 32.4 29.2 28.8 24.8 36.6 37.6 39.1 32.7 27.0
160 ft
30.4 26.9 35.0 37.2 37.5 39.3 32.0 31.2 33.0 30.8 32.2 36.6 35.2 33.6 33.4 33.1 34.0 34.1 34.8 32.9 32.5 31.9 35.8 32.5 31.9 27.0 38.6 39.9 42.7 35.4 29.3
Root Mean Square 13 ft
3.67 3.95 4.97 4.28 4.82 4.86 4.55 4.09 4.42 4.72 5.18 5.47 4.12 4.48 4.50 4.19 4.62 4.07 4.26 4.29 3.95 4.11 4.38 4.04 3.71 3.92 5.65 5.72 5.13 4.52 3.98
33 ft
4.15 4.43 5.44 4.53 5.00 5.18 4.87 4.29 4.54 4.79 5.13 5.62 4.15 4.64 4.60 4.24 4.60 4.43 4.46 4.50 4.20 4.20 4.78 4.42 3.94 3.88 5.82 5.69 5.60 5.09 4.11
70 ft
3.99 4.49 5.14 4.02 4.65 4.95 4.89 4.37 4.76 4.77 5.57 5.89 4.52 4.78 4.68 4.18 4.57 4.40 4.60 4.46 4.11 4.09 4.69 4.63 4.08 3.88 5.89 5.63 5.36 5.68 3.98
160 ft
3.56 4.22 5.04 3.95 5.37 5.14 4.45 4.57 4.72 4.85 6.22 6.30 4.30 4.84 4.62 4.27 4.29 3.83 4.01 4.11 3.54 3.34 4.03 3.91 4.04 4.07 5.80 5.84 5.45 5.17 3.<0
r 69
level; then decreases with height. The RMS value at 33 ft level is higher than
that at 13 ft level by 0.2 to 0.4 mph in most of the data sets. Higher RMS value
means more turbulence. More turbulence at 33 ft level than at 13 ft level seems
unrealistic because ground roughness generates more turbulence at 13 ft level than
at 33 ft level during high wind condition. This anomaly of higher turbulence at
33 ft level than at 13 ft level is not known.
Mean and RMS values of the wind direction are tabulated in Table 5.6. Gen
erally, the variation of mean wind direction follows the Ekman spiral which states
that the mean wind direction increases with height in a clockwise direction (Panof
sky and Dutton, 1986). Most of the variation of mean wind direction is from 1°
to 5°. Six of the wind direction sets show decrease of 1° to 2° in mean wind direc
tion with height in clockwise direction respectively. Another five wind direction
sets do not show any variation of mean wind direction. The RMS values of the
wind direction decrease with height by 1° to 3° which is expected as there is less
fluctuation high above ground.
Wind Profile Parameters
The wind profile parameters power law exponent a, roughness length ZQ and
shear velocity U. are determined from the power and logarithmic laws. Both of
the a and ZQ parameters will be used to characterize the roughness of the terrain.
Power Law Parameter
The power law exponent a can be obtained by making the power law of Equa
tion (2.4) to be hneax so that hnear regression can be performed to obtain the
best fit hne. The hnear form of the power law is :
F 70
Table 5.6 Mean and RMS Values of Wind Direction
Set
AOl A03 A04 A05 A07 A08 A15 A16 A17 A19 A25 A28 A31 A32
A33 A34 A35 A41 A42 A43 A44 A45 A48 A49 A50 A52 A55 A56 A60 A61 A63
Wind Direction (azimuth) Mean
33 ft
025 029 345 350 345 346 002 359 237 219 229 243 287 289 289 285 281 353 352 359 356 359 318 322 316 172 197 207 043 048 023
160 ft
030 032 349 354
349 350 006 004 235 221 231 246 287 287 287 284 280 357 357 364 001 003 318 321 316 172 200 208 043 049 025
Root Mean Square 33 ft
09.0 09.0 09.4 08.1 08.2 07.4 07.6 08.0 10.4 10.0 08.9 10.2 10.7 10.1 09.4 09.2 06.9 07.3 08.5 08.3 09.3 10.2 08.8 10.4 08.5 08.2 08.4 09.5 07.6 08.2
08.1
160 ft
6.3 7.1 7.7 5.8 5.9 6.4 6.0 5.7 9.3 9.8 7.3 9.6 9.9 8.2 7.3 7.2 5.5 4.9 6.4 7.3 7.3 7.9 6.0 7.0 6.0 7.1 7.9 7.8 5.5 6.7 7.1
71
where Ui, U2 = the wind speeds at height Zi, Z2 respectively, and
a = the power law exponent.
Equation (5.1) can be plotted using four levels of wind speed with the reference
height and wind speed taken at 13 ft level. Figure 5.7 shows the hnear relationship
^^ ^^ (u t ) ^^^ ^^ (fe) ' '^^^ " v^^« can be obtained from the slope of the best fit
hne. The a values range from 0.10 to 0.17 as tabulated in Table 5.7.
Logarithmic Law Parameters
The roughness length, ZQ and shear velocity, U. parameters can be determined
from the plot of the logarithmic law of Equation (2.5). The displacement height,
d in Equation (2.5) is neglected because the roughness elements of grass, crop
and mesquite trees at the field site are low. Smsdl values of d has neghgible
effect on the logarithmic law parameters. The universal function, V' is taken to
be zero because of assumed neutral stabihty condition of the atmosphere. The
logarithmic law is simplified and is rearranged as follows :
InZ = : ^ U ( Z ) - h l n Z o (5.2)
where U(Z) = the wind speed at height Z above ground,
U. = the shear velocity,
k = the von Karman constant, and
Zo = the roughness length.
73
Table 5.7 Wind Profile Parameter Values
Set
AOl A03 A04 A05 A07 A08 A15 A16 A17 A19 A25 A28 A31 A32 A33 A34 A35 A41 A42 A43 A44 A45 A48 A49 A50 A52 A55 A56 A60 A61 A63
Power Law a
0.14 0.14 0.15 0.16 0.16 0.16 0.17 0.17 0.11 0.11 0.13 0.10 0.14 0.15 0.14 0.14 0.14 0.15 0.15 0.14 0.14 0.14 0.14 0.15 0.14 0.16 0.15 0.14 0.15 0.14 0.14
Logarithmic Law Zo(ft)
0.025 0.022 0.061 0.070 0.077 0.085 0.124 0.124 0.006 0.004 0.017
1 0.002 0.039 0.065 0.038 0.035 0.047 0.058 0.056 0.028 0.027 0.038 0.032 0.050 0.038 0.090 0.049 0.039 0.047 0.025 0.036
U.(mph)
1.40 1.24 1.79 1.94 1.97 2.10 1.77 1.81 1.31 1.21 1.41 1.32 1.68 1.70 1.59 1.56 1.66 1.73 1.75 1.55 1.50 1.53 1.68 1.61 1.53 1.46 1.96 1.95 2.11 1.63 1.40
74
A plot of In Z versus U(Z) of Equation (5.2) for the four levels is shown in
Figure 5.8. A best fit hne obtained by hnear regression analysis is shown in the
figure. The interception on the vertical ajcis is the In ZQ value. The slope of the
Hne is the ^^ value. The shear velocity can be determined easily by assuming k
equal to 0.4. Table 5.7 shows the profile parameter values. The roughness length
values range from 0.002 to 0.124 ft while the shear velocity has a range of 1.21 to
2.11 mph.
Terrain Characterization
The power law exponent, a, the roughness length ZQ values, the mean wind
directions of records along with terredn features (see Figure 3.2) are used to char
acterize the terrain. The terrain of the field site is divided into four zones. The
results of the terrain characterization axe summarized in Figure 5.9 and Table
5.8.
Zone A is from azimuth of 270° to 70°. These areas are consistently flat
and wide open. Twenty four sets of wind data are available in this zone. The
profile parameters, ZQ and a show consistent values in this zone. Average ZQ and
a values are 0.045 ft and 0.14, which fit into the category of fairly level grass
plains by ESDU (1982) and flat and wide open terrain by ANSI standard (1982)
respectively. Table 5.8 shows the range of values obtained in the 24 sets of data.
Wind flows from the southeast are disturbed by the buildings, and the legs of
the tower. The tower can reduce the mean wind speed in the azimuth range of
80° to 160°. The test building may disturb the wind flows from azimuth of 70° to
80°. This terrain in the azimuth range of 70° to 160° is unpredictable terrain in
the field and is classified as Zone B. Data in this Zone are not used for analysis.
^
75
•>»»
o ro
N
(/I
0
e tSJ
^ 1 I CO O •«1< C<4
^ ''^ ^ A " n o ^ • -> . r -Tj« t o
II II II
o o tS3 ISJ
(O "T lO
"T T" CM
_ O
u o
a M cn a
a
w
a bO
o
d o Id d
V •*»
V
O (X)
d bO
eg I
ro
t>J
Zone A
270^
Zone D
21Q0
70°
Zone B
Zone C 160°
Figure 5.9 Mean Wind Direction of 31 Data Sets
Table 5.8 Average Wind Profile Parameter Values in Zones
Zone
A
B
C
D
Azimuth Range
270° - 70°
70° - 160°
160°-210°
210° - 270°
Number of Data Set
24
• • •
3
4
a
0.14-
(0.14-0.17)t
0.15 (0.14-0.16)
0.11 (0.10-0.13)
Zo (ft)
0.045
(0.022-0.124)
0.059 (0.039-0.090)
0.007 (0.002-0.017)
U. (mph)
1.68
(1.24 2.11)
1.7! (1.46-1.96)
1.31 (1.21-1.41)
* average value t range of minimum to maximum
77
Between azimuth range of 160° to 210°, the average Zo and a values indicate
sHghtly rougher terrain than terrain in Zone A. This area is classified as Zone C
(see Figure 5.9). The result of this zone is not conclusive due to the fact that only
three sets of wind data are available. The range of ZQ and a values are shown in
Table 5.8.
Zone D is from the direction of the playa lake in the azimuth range of 210° to
270°. The average ZQ and a values are 0.007 ft and 0.11 respectively (see Figure
5.8). The parameters distinctly indicate the smoothest terrain at the field site. It
should be pointed out that there are 14 sets of wind data collected in this zone.
Only four of them are stationary and are used to get the wind profile parameters.
The rest of them have the same wind profile parameters that distinctly show that
Zone D is the smoothest terrain.
Turbulence Intensity
The turbulence intensity can be calculated using the mean and root mean
square values of the wind speed. Equation (2.6) is used for the calculation. The
turbulence intensity values for 31 sets of data are tabulated in Table 5.9. The
turbulence intensity values decrease with height. The decrease in turbulence
intensity value from 13 ft level to 33 ft level is due to the increase in mean wind
speed. As noted previously, the RMS values for 33 ft level are higher that 13
ft level for most of the data sets (see Table 5.5). Table 5.10 shows the average
turbulence intensity values in three zones. The average turbulence intensity values
at various heights in Zone A are the lowest as compared with Zone C £md Zone
D.
78
Table 5.9 Turbulence Intensity Values
Set
AOl A03 A04 A05 A07 A08 A15 A16 A17 A19 A25 A28 A31 A32 A33 A34 A35 A41 A42 A43 A44 A45 A48 A49 A50 A52 A55 A56 A60 A61 A63
Turbulence Intensity 13 ft
0.17 0.20 0.21 0.17 0.19 0.18 0.22 0.20 0.18 0.20 0.22 0.19 0.17 0.19 0.19 0.18 0.20 0.17 0.18 0.18 0.17 0.18 0.17 0.18 0.17 0.22 0.21 0.20 0.17 0.18 0.19
33 ft
0.17 0.20 0.20 0.15 0.17 0.17 0.20 0.18 0.17 0.18 0.20 0.18 0.15 0.18 0.17 0.16 0.17 0.16 0.16 0.17 0.16 0.16 0.17 0.17 0.15 0.18 0.18 0.17 0.16 0.17 0.17
70 ft
0.14 0.18 0.16 0.12 0.14 0.14 0.18 0.16 0.15 0.16 0.19 0.17 0.15 0.16 0.16 0.14 0.15 0.14 0.15 0.14 0.14 0.14 0.15 0.16 0.14 0.16 0.16 0.15 0.14 0.15 0.15
160 ft
0.12 0.16 0.14 0.11 0.14 0.13 0.14 0.15 0.14 0.15 0.18 0.17 0.12 0.14 0.14 0.13 0.13 0.11 0.12 0.13 0.11 0.11 0.11 0.12 0.13 0.15 0.15 0.15 0.13 0.15 0.13
'.•w)5
Table 5.10 Average Turbulence Intensity Values in Zones
Zone
A
B
C
D
Number of Data Set
24
3
4
13 ft
0.18-(0.17-0.22)t
0.21 (0.20-0.22)
0.20 (0.18-0.22)
Turbulence Intensity
33 ft 70 ft
0.17 (0.15-0.20)
0.18 (0.17-0.18)
0.18 (0.17-0.20)
0.15 (0.12-0.18)
0.16 (0.15-0.16)
0.17 (0.15-0.19)
160 ft
0.13 (0.11-0.16)
0.15 (0.15)
0.16 (0.14-0.18)
79
* average value. t range of minimum to maximum.
80
Longitudinal Integral Scale of Turbulence
One of the method of determining longitudinal integral scale of turbulence
as discussed in Chapter II, is the product of the mean wind speed and the time
scale. The time scale is the area under the autocorrelation function curve. The
mean wind speed can be obtained easily, but the correct time scale is difficult to
obtain.
The autocorrelation function never dies off exactly to zero, but fluctuates
about zero. The fluctuations after the die off point usually do not have much
contribution to the time scale because the fluctuations about zero tend to cancel.
Figure 5.10(a) is a typical wind speed autocorrelation function plot. The sum of
the area after the die off point of 50 seconds is close to zero. The time scale for
this case will be the same if 50-, 80- or 120-second lag time is used.
There are some autocorrelation function plots that do not show much fluctu
ations about zero for the flrst 120 seconds. Figure 5.10(b) is an example of this
behavior. The die off point is about 40 seconds, but the autocorrelation function
does not fluctuate about zero beyond that point. In this case, if the lag time of
120 seconds is used, the time scale will turn out to be negative. The correct lag
time should be the die off point of about 40 seconds. In general, the time scale is
sensitive to the lag time used.
Most of the wind speed autocorrelation function die off in the range of 35
to 70 seconds. Examination of all the wind speed autocorrelation function plots
indicates that the best lag time is 80 seconds. There are a few cases such as that
shown in Figure 5.10(b), where 40- or 50-second lag time is used. Equation (2.8)
is used to calculate the longitudinal integral scale of turbulence.
fl52WS033 j-a;-,* ,9.5, nu riofl cxPDtircNT nw uim ncssuRc
81
njOT ORTC 3-JW-M
TIME (SECONDS)
(a)
R44NS033 3-i7-i9n is.o TTU riCLO cxPCRinorr FOR HINO PRCSSUC njn OBTC ]-jui-aa
TIME (SECONDS)
(b)
Figure 5.10 Wind Speed Autocorrelation Function Plot (a) Fluctuating about Zero, and (b) Nonfluctuating about Zero
82
diie The results of the time scale and longitudinal integral scale of turbulence
tabulated in Table 5.11. The time scale increases with height, which impUes the
average duration of the effect of eddies at a point increases with height. Thus,
the longitudinal integral scale of turbulence is expected to increase with height.
Table 5.11 shows the increasing trend of longitudinal integral scale of turbulence
with height. The increase is due to the combination of increasing time scale and
mean wind speed. A larger integral scale of turbulence is formed at higher level
because there is less effect of ground roughness on the formation of large eddies.
Average values of longitudinal integral scale of turbulence in the zones are
tabulated in Table 5.12. Zone D, which has the smoothest terrain, has the highest
average value, whereas the lowest average value is in Zone C. In general, the
average longitudinal integral scale of turbulence value increases with smoother
terrain.
The average longitudinal integral scale of turbulence value at 33 ft level is
compared with other investigators' results tabulated in Table 2.3. Zone A and
Zone C average values are close to the results obt£dned over flat and open terrain
by Teunissen (1979) and Shiotani and Iwatani (1979). Zone D average value of
619 ft is close to 190 m (623 ft) by Choi (1975), 210 m (689 ft) by Mackey and Lo
(1975), and, 195 m (640 ft) by Shiotani and Iwatani (1979) which are obtained
over coastal and sea terrain.
Table 5.11 Longitudinal Integral Scale of Turbulence Values
83
Set
AOl
A03 A04 A05 A07"" A08'' A15 A16 A17 A19 A25 A28 A31 A32 A33 A34 A35 A41 A42 A43 A44"' A45-A48 A49 A50 A52-A55
A56t
A60t
A61 A63
Long 13 ft
09.2
15.7 17.5 09.4 06.6 07.0 11.0 04.2 09.0 10.4 15.3 15.7 07.9 04.4 07.5 18.9 16.5 07.5 07.5 09.2 07.1 06.7 10.8 12.8 05.4
09.8 07.6
06.4
03.4 16.5 16.6
itudinal Time 33 ft 70 ft
09.9 14.6 19.9 18.8 08.9 06.6 08.0 13.5 06.6 11.0 10.3 20.7 17.9 09.2 04.7 06.6 21.7 19.2 08.9 12.2 12.6 10.0 07.3 12.1 17.1 07.2
11.0 11.1
06.7
05.5 19.4 17.7
21.8 20.0 12.9 09.4 12.2 13.3 12.6 10.0 11.9 24.1 17.0 08.1 06.4 07.1 21.3 22.9 14.5 13.1 17.9 11.2 08.6 18.5 18.7 12.3 10.6 13.4
05.1
05.5 18.6 16.7
Scaled (sec)
160 ft
21.9 25.7 24.8 13.5 17.8 15.3 21.3 11.0 19.4 10.1 31.4 13.6 10.9 12.1 24.6 22.2 21.7 16.1 17.3 27.5 13.6 15.2 23.0 22.6 26.3 07.8 14.3
04.6
08.6 26.3 11.9
Longitudinz 13 ft 33 ft
300 451 621 352 248 272 340 125 332 367 530 662 285 150 258 647 573 258 263 332 243 222 402 422 177 261 304
256
150 611 505
358 640 763 384 284 362 479 228 443 410 798 825 379 179 260 843 759 355 493 504 386 275 512 651 271 346 516
323
278 843 618
d Length 70 ft
0610 0819 0937 0646 0468 0641 0545 0503 0457 0528 0998 0865 0368 0278 0310 0916 1015 0670 0605 0821 0488 0369 0879 0800 0521 0387 0722
0280
0316 0891 0662
Scale (ft) 160 ft
0975 1014 1276 0738 0979 0881 1000 0504 0940 0458 1480 0731 0562 0595 1209 1076 1080 0805 0880 1328 0648 0714 1207 1080 1229 0308 0811
0266
0537 1367 0510
* 50 seconds of lag time used. t 40 seconds of lag time used. t longitudinal time scale is area under autocorrelation plot. Lag time used is 80 seconds unless otherwise noted.
84
Table 5.12 Average Longitudinal Integral Scale of Turbulence \'alues in Zones
Zone
A
B
C
D
Number of Data Set
24
3
4
Longitudinal Integral Scale of Turbulence (ft)
13 ft 33 ft 70 ft 160 ft
342-
(125-647)t
274 (256-304)
473 (332-662)
463 628
(179-843) (278-1015)
. . .
395 463 (323-516) (280-722)
619 712 (410-825) (457-998)
924
(504-1367)
462 (266-811)
902 (458-1480)
* average value. t range of minimum to majdmum.
CHAPTER VI
CONCLUSIONS AND RECOMMENDATIONS
In the study presented here, wind data from four levels of the meteorological
tower are analyzed. Time history plot, stationarity check and descriptive statistics
are used to vahdate the fleld data. Of the 63 sets of field data, 31 of them are found
to be suitable for analysis. The rest of the data sets are rejected because of bad
data, unusable wind direction, non-neutral atmospheric stabihty condition or non
stationarity. Analysis of data include the assessment of wind profile parameters,
turbulence intensity and longitudinal integral scale of turbulence.
Conclusions
Based on the observations of the results in this study, the following conclusions
are made concerning the wind parameters of Texas Tech University field site.
1. Only five of the 63 sets of data are classified as bad data due to instrument
malfunction. The high percentage of good data imphes that the tower
instruments are assembled correctly and are functioning properly.
2. Calibration tests in the laboratory and field of the instruments indicate that
the instruments provide good accuracy. Field tests of temperature sensors
give questionable readings. Inherent noise in the anemometer data is also
detected in the cahbrator test of the anemometers.
3. The variation of mean wind direction with height follows the Ekman spiral.
The mean wind direction increases with height in the clockwise direction.
The general increase is from 1° to 5°.
85
86
4. The roughness length, ZQ and power law exponent, a values show some
variations. However, four zones of the field site are classified based on
profile parameter values, mean wind directions and terrains features. Zone
A, from the azimuth range of 270° to 70°, has flat and wide open terrain.
The average ZQ and a values are 0.045 ft and 0.14 respectively. Zone B has
the roughest terrain in the field and buildings nearby the tower. It is from
azimuth range of 70° to 160°. Field data collected in Zone B are not used
for analysis. Zone C is from the azimuth range of 160° to 210°. This is a
rougher terrain than that in Zone A. Zone D is the smoothest terrain in the
field. It is from the azimuth range of 210° to 270°.
5. The average shear velocity value decreases from rougher zone to smoother
zone, that is from Zone C to Zone A, then to Zone D.
6. Turbulence intensity value has a general decreasing trend with height. The
average turbulence intensity value at 33 ft is 0.18. However, the RMS values
of wind speed at 33 ft are higher than those at 13 ft.
7. Even though the time scale and longitudinal integral scale of turbulence
values show wide variations, both of them have a trend of increasing with
height. Average longitudinal integral scale of turbulence values at four
heights also increase with smoother terrain. Zone D has an average longi
tudinal integral scale of turbulence value at 33 ft of 619 ft, followed by Zone
A, 463 ft and Zone C, 395 ft.
Recommendations
The following recommendations are made for improving future field experi
ment results.
87
1. Only visual validation of field data are performed for this study. Spectral
analysis should be included for future study as part of the validation process
to detect possible noise.
2. A better temperature measurement system that has the accuracy of one
himdredth of a degree Fahrenheit is recommended for this project. A ther
mocouple system which measures the differential temperature of two levels,
can meet the requirement. This degree of accuracy is necessary to assess
atmospheric stability condition.
3. More field data from the south and southwest are needed for analysis before
Zone C and Zone D can be classified conclusively.
4. A wide variation of longitudinal integral scale of turbulence values is ob
served due to direct impact of time scale variation. The time scale variation
is in turn affected by the shape of the autocorrelation coefficient plot. The
autocorrelation coefficient plots should be investigated further to detect any
correlation between the shape of the autocorrelation coefficient plot and the
atmospheric stability condition.
5. Further study of longitudinal integral scale of turbiilence should include the
possibihty of developing different empirical models to predict longitudinal
integral scale of turbulence for different zones.
» "
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88
89
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90
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39 Teunissen H. W., 1970: "Characteristics of the Mean Wind and the Turbulence in the Planetary Boundary Layer," UTIAS Report No.32, University of Toronto, Canada.
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