Final Analysis
Space Cadets
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Table of Contents
Introduction ..................................................................................................................................... 3
Background ..................................................................................................................................... 3
Sensors ............................................................................................................................................ 5
System Testing Results ................................................................................................................... 6
Calibration Results .......................................................................................................................... 8
Conclusion .................................................................................................................................... 10
References ..................................................................................................................................... 13
Table of Figures
Figure 1: collected balloon payload temperatures from Ft. Worth, TX from May 24-30, 2009 at
0000 GMT [7] ................................................................................................................................. 4
Figure 2: collected pressure data from Ft. Worth, TX from May 24-30, 2009 ............................. 4
Figure 3: Altitude vs. Humidity at Fort Worth, TX collected on May 20, 2009 ............................ 5
Figure 4: System testing data for Pressure/Humidity vs. Time ...................................................... 7
Figure 5: System testing data for Temperature vs. Time ................................................................ 7
Figure 6: Humidity Sensor Calibration Graph ................................................................................ 8
Figure 7: Calibration Graph for Pressure Sensor ............................................................................ 9
Figure 8: Temperature Sensor Calibration Graph ......................................................................... 10
Figure 9: Temperature vs. Altitude graph for data collected from Lubbock, TX ......................... 11
Figure 10: Relative Humidity vs. Altitude for data collected from Lubbock, TX........................ 11
Figure 11: Pressure vs. Altitude for data collected from Lubbock, TX ........................................ 12
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Introduction
The goal was to study the relationships between the temperature, pressure, humidity, and
altitude ranging from 0 to 100000 ft in an effort to identify and verify trends at various layers of
the atmosphere using a balloon payload launched from Lubbock, TX. The two atmospheric
layers encountered in the flight were the first two layers of the atmosphere: Troposphere, and
Stratosphere.
Background
The five layers of Earth’s atmosphere are Troposphere, Stratosphere, Mesosphere,
Thermosphere, and Exosphere. The two atmospheric layers encountered in the flight were the
first two layers of the atmosphere: Troposphere, and Stratosphere.
The first atmospheric layer of Earth, Troposphere, extends from 8 to 14.5 km high (5 to 9
miles). Temperature decreases from about 17 to -52° C, linearly, in the troposphere [2]. As you
ascend in stratosphere, from 14.5 km to about 20 km, temperature remains fairly constant. This
constant height portion is referred to as an isothermal layer. From an altitude of 20 to 50 km,
temperature increases with an increase in altitude, ranging from ~60° Celsius to ~0° Celsius [3].
Unlike temperature, pressure decreases exponentially with altitude. Atmospheric
pressure is usually measured in millibars (mb), equivalent to 1g/cm2. At sea level, the pressure is
on average 1013 mb, whereas, at Mt. Everest (altitude of 8.848 km (29,029 feet)), the
atmospheric pressure is approximately 300 mb. As the pressure decreases, the amount of oxygen
intake per breath decreases, which is why the higher you go, the harder it is to breathe [5].
Humidity, which is the amount of moisture the air can hold before it rains, is measured
by psychomotor. During the day near the surface, particularly with clear skies, absolute
humidity usually decreases with height [8].
Usage of weather balloons to measure atmospheric parameters dates back to January,
1930. It was first used by Pavel A. Molchanov, a Russian meteorologist, who made a successful
cosmic ray reading in the Stratosphere. This method of measuring temperature, moisture, and
wind data was first used by U.S. Weather Bureau in 1936. Currently, there are more than 70
stations located around U.S. These stations launch weather balloons twice daily just before 0000
and 0012 GMT. One of these locations is Forth Worth, TX. This location was selected because
of its similar altitude and geographical location with the LaACES launch point [6].
This data which was collected on May 24-30, 2009 was used to graph the variations in
temperature, pressure, and humidity with altitude. The results are shown in Figure 1-3. The data
from these 7 days was chosen because of similar launch dates of late May, 2010.
Temperature analysis can be broken down in three sections in order to determine the
sampling rate. The first section is the linearly decreasing temperature in troposphere. The
second section is the constant temperature section in the first 5 km of the Stratosphere. The third
section is the increase in temperature from ~18 km to ~33 km. The greatest change in
temperature with altitude occurs in the troposphere layer. This can be seen graphically in figure
1. The temperature decreases is approximately 6.1 °C/m. With balloon payload ascending at
1000 ft/min, which is 304.8 m/min, change in temperature is 1.08 °C/35sec. Approximately 1 °C
of change happens every 35 sec, so the sampling rate does not have to be less than 1 sample/30
sec.
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Figure 1: collected balloon payload temperatures from Ft. Worth, TX from May 24-30,
2009 at 0000 GMT [7]
Figure 2: collected pressure data from Ft. Worth, TX from May 24-30, 2009
As shown in Figure 2 change in pressure is exponential with altitude, with the greatest
change being in the first 10000 m. The change in pressure during the first 10000 m is ~800 hPa.
If the assent rate is 304.8 m/min, the change will be 41 Pa/sec. Since, we are only measuring the
trend of pressure, the sample rate of 1 sample/30 sec is sufficient.
Humidity changes dramatically in the first 2000 meters of altitude as can be seen in
figure 3. Once at 2000m, the range of humidity ranges from 4 to 15 %. In addition, at around 20
km we do see a decrease in humidity.
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Figure 3: Altitude vs. Humidity at Fort Worth, TX collected on
May 20, 2009
Sensors
The temperature sensor is a temperature-sensitive semiconductor, the 1N457 diode. The
1N457 is a small signal silicon PN junction diode. A PN diode is the interface at which p-type
silicon and n-type silicon make contact with each other. The forward biased voltage across a
diode has a temperature coefficient of about 2.3mV/ºC and is fairly linear. The voltage has a
negative temperature coefficient (at a constant current) but depends on doping concentration and
operating temperature. The diode’s analog signal will be processed through signal conditioning
where it will manipulate the analog signal in such a way that it meets the requirements of the
ADC. The Basic Stamp reads the data from the ADC and stores the information in EEPROM.
The humidity sensor, HIH-4030, is a linear voltage humidity sensor. This sensor contains an
integrated circuit that includes a humidity-sensing capacitor and signal conditioning. The water
vapor within the capacitor reaches equilibrium with that of the surrounding atmosphere. This
change in vapor level changes the capacitive value of sensor. The internal signal conditioning of
the chip then converts this change in capacitance and outputs a linear voltage.
The pressure sensor, Model 1230 Ultrastable, detects the pressure in the atmosphere.
This is an absolute pressure sensor, meaning it detects the ambient pressure. Four piezoresistors
are arranged in a wheatstone bridge configuration to minimize the temperature sensitivity. The
piezoresistors vary in resistance according to applied mechanical stresses which occur due to
difference between the ambient pressure and the vacuum pressure. This variance in resistance
causes a potential difference between the output nodes when a constant current is applied to the
input.
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System Testing Results
First the vacuum test was performed and we were able to confirm that the payload
operates and the sensor outputs were used to confirm the calibration. The result is shown in
figure 4. We placed only the circuitry of the payload in the vacuum chamber because the shell
would not fit. The chamber was then activated and allowed to run for 15 minutes and the
chamber reached approximately 50 mmHg of absolute pressure. After the 15 minutes, we turned
off the vacuum chamber and allowed the payload to rest in the chamber at low pressure for an
additional 5 minutes. We then removed the payload from the chamber and verified the results of
the test by checking the sensor outputs. We used the values of the vacuum chamber to confirm
our earlier calibration data of the pressure sensor. The pressure exponentially reaches 3.1 mm
Hg and remains there for the time the vacuum chamber was left at a pressure near absolute zero.
Then, as you can see, there is almost an instantaneous gain to 760 mm Hg when the pressure
valve is opened. The pressure values were converted from ADC data points to pressure points
using the equation: ADC value * 3.1, determined using the calibration data. The humidity vs.
time can also been on the same graph. As the pressure decreases, the humidity also decreases as
expected. The humidity values were converted from ADC data points to humidity points using
the equation: (ADC value -19)/2.
Next the temperature test was performed. This graph can be seen in figure 5. We moved
both the payload and a Hobo between room temperature, the refrigerator, the freezer, and the dry
ice box for the time mentioned in the thermal test procedure in that order to simulate the ascent
of the flight. We connected the payload to the computer and confirmed that the payload was
operational and taking measurements the entire time. The equation used to convert the ADC
values to temperature values is (ADC-115.16)/-2. The thermal test performed as expected.
Finally, the shock test was performed. We dropped the payload approximately 10 feet.
On the initial drop, the sensors and soldered parts of the payload remained intact, but the
camera’s control wire became detached. We fixed this issue by placing plastic locking
connectors to hold the wires in place during flight, and re-tested to confirm this prevented the
camera from disconnecting again. These were then added to additional wires that we wanted to
further ensure remained connected during flight.
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800
700
600
500
400
Pressure
300
Humidity
200
100
0
0
500
1000
1500
2000
Time (sec)
Figure 4: System testing data for Pressure/Humidity vs. Time
40
Temperature (ᵒC)
30
20
10
0
0
1000
2000
3000
4000
5000
6000
-10
-20
-30
Time (sec)
Figure 5: System testing data for Temperature vs. Time
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Calibration Results
Humidity Sensor Calibration Graph
200
y = 1.999x + 18.918
180
160
ADC Value
140
120
ADC Value
100
Linear (ADC Value)
80
60
40
20
0
0
20
40
60
80
100
Relative Humidity (%)
Figure 6: Humidity Sensor Calibration Graph
Humidity
83.3
57.8
56.8
78.2
ADC Value
185
126
120
171
Table 1: Calibration Data for Humidity Sensor
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300
250
y = 0.3275x - 7.1246
200
ADC Values
150
Linear (ADC Values)
100
50
0
0
200
400
600
800
Figure 7: Calibration Graph for Pressure Sensor
Pressure
760
350
120
60
ADC Value
244
102
33
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Table 2: Pressure Sensor Calibration Data
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Temperature Sensor Calibration Graph
160
140
120
ADC Value
100
Series1
80
Linear (Series1)
y = -2.0148x + 115.16
60
40
20
0
-20
-10
0
10
20
30
Temperature (C)
Figure 8: Temperature Sensor Calibration Graph
Temp (C)
23.3
21.8
10
-9.522
ADC Value
61
70
86
133
Table 3: Temperature Sensor Calibration Data
Conclusion
Our expected results matched our system results closely. These results also resembled the
data we obtained for our science background results. We knew from our science background,
that Temperatures decrease in the troposphere as we go higher in this atmospheric layer, then
began to increase after entering the stratosphere. This could not be confirmed in our system
testing, but from our actual results of the flight.
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Temperature vs. Altitude
20
Temperature (°C)
10
0
-10 0
20000
40000
60000
80000
100000
120000
-20
-30
-40
-50
-60
Altitude (ft)
Figure 9: Temperature vs. Altitude graph for data collected from Lubbock, TX
Our payload’s temperature reading matches the expected temperature trends, with the
temperature steadily decreasing as the payload began its ascent, then once the payload reached
the stratosphere, the temperature began slowly increasing. When the balloon burst and the
payload began dropping, it recorded a very low temperature as it passed back into the
troposphere and the temperature began rapidly increasing as the payload descended. These
trends match what we expected to encounter based on previously taken data.
Relative Humidity vs. Altitude
Relative Humidity (%)
70
60
50
40
30
20
10
0
0
20000
40000
60000
80000
100000
120000
Altitude (ft)
Figure 10: Relative Humidity vs. Altitude for data collected from Lubbock, TX
Our humidity readings differ a little from the expected results, but overall follow the
same trends we expected. The humidity begins high at ground level then drops drastically as the
payload first took off. The detected humidity also spikes back up shortly after the flight began
then continues to slowly decrease for the rest of the flight. These trends match the expected
trends, but we detected a faster drop-off in humidity than the expected value.
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Pressure vs. Altitude
1200
Pressure (mm Hg)
1000
800
600
400
200
y = 1356.3e-6E-05x
0
0
20000
40000
60000
80000
100000
120000
Altitude (ft)
Figure 11: Pressure vs. Altitude for data collected from Lubbock, TX
The pressure graph looks almost exactly as we expected. Once the flight takes off, the
pressure experiences an exponential decrease relative to altitude. After the balloon burst and the
payload began to fall, the sensor experienced some erratic readings before returning to the
expected values after landing. In figure above, the pressure profile of flight ascent is shown.
Comparing these results to pressure data collected from Fort Worth, TX, it can be clearly seen
that the pressure trend is same.
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References
[1] "NASA - Earth's Atmosphere." NASA - Home. Ed. Shelley Canright. 10 Apr. 2009. Web. 16 Nov.
2009. <http://www.nasa.gov/audience/forstudents/912/features/912_liftoff_atm.html>.
[2] Christian, Stefan. "How Sensors Work." Sensorland. Web. 19 Nov 2009.
<http://www.sensorland.com/HowPage047.html>.
[3] "The Earth and the Atmosphere--Images and Diagrams." Welcome to the Physics Department at
ISU. Web. 17 Nov. 2009. <http://www.physics.isu.edu/weather/kmdbbd/unit1_images.htm>.
[4] "Types of Temperature Sensors." Temperatures. Web. 18 Nov 2009.
<http://www.temperatures.com/sensors.html>.
[5] Pidwirny, M. (2006). "The Layered Atmosphere." Fundamentals
of Physical Geography, 2nd Edition. Web. 16 Nov.
2009. <http://www.physicalgeography.net/fundamentals/7b.html>.
[6] "Atmosphere: Composition & Structure." Indiana University. Web. 16 Nov. 2009.
<http://www.indiana.edu/~geog109/topics/01_atmosphere/atmos.htm>.
[7] "Types of Temperature Sensors." Temperatures. Web. 18 Nov 2009.
<http://www.temperatures.com/sensors.html>.
[8] "Humidity and Electronics - TechSpot OpenBoards." TechSpot - PC Technology News and
Analysis. Web. 24 Nov. 2009. <http://www.techspot.com/vb/topic90239.html>.
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