infrared thermography princeton university gas dynamics
DESCRIPTION
This report outline a summer research project to use infrared thermography to measure heat flux on a flat plate in Mach 8 flow in Princeton University's Gas Dynamics lab in Summer 2012.TRANSCRIPT
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INFRARED THERMOGRAPHY IN A HYPERSONIC BOUNDARY LAYER FACILITY
MAE PRACTICAL INTERNSHIP
SUMMER 2012
Mechanical & Aerospace Engineering Department
Princeton University
Name Signature Date
David Harris David Harris August 4, 2012
Laboratory Work and Report Submission Date
Infrared Thermography (Research Work) June 11, 2012
Infrared Thermography (Experimental Work) June 25, 2012
Infrared Thermography (Report Submission) August 20, 2012
Final report submitted September 6, 2012
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LETTER OF TRANSMITTAL
David Harris
Princeton Undergraduate Class of 2015
Forbes College
Princeton, NJ 08544
August 4, 2012
Alexander J. Smits
Eugene Higgins Professor of
Mechanical & Aerospace Engineering
D218 Engineering Quad
Princeton, NJ, 08544
Dear Professor Smits:
I submit herewith a scientific report for the experiment conducted during my MAE
Practical Summer Internship: Infrared Thermography in a Hypersonic Boundary Layer Wind
Tunnel. It has been turned in according to the due date instructed to by Owen Williams (August
10, 2012) and pledge my honor that I have not violated the Honor Code during the composition
of this lab report.
The report itself contains information and analysis of data retrieved from experiments at
the Hypersonic Boundary Layer Facility (HyperBLaF) at Princeton’s James Forrestal Campus.
It is intended to relay the results of the lab experiments, and provide insight and analysis which
can be used in later experiments.
I hope that your find the report to be informative and comprehensive. I also hope that the
analysis presented within will prove to be fruitful in further developing the foundation required
for hypersonic testing.
Yours sincerely,
David Harris
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INFRARED THERMOGRAPHY IN A HYPERSONIC BOUNDARY LAYER FACILITY
MAE Practical Internship
Princeton University
Abstract
Hypersonic aircraft travel at high speeds ranging from Mach 6 to Mach 25 (the speed
attained during atmospheric reentry). In these conditions the speed of air particles hitting the
aircraft creates intense friction and generates heat that is very detrimental to the aircraft. These
thermal loads are dominated by convective heat transfer, which is difficult to measure accurately.
An experiment was designed at Princeton’s HyperBLaF (Hypersonic Boundary Layer Facility)
to test a non-intrusive optical measurement technique, known as infrared thermography, with the
aim of obtaining quantitative heat transfer data on a flat brass plate subjected to hypersonic flow.
An infrared camera along with compatible computer software was used to measure surface
temperature over time for a section of Macor in the flat brass plate. This data was then run
through programs written in Matlab to find the heat flux over time and the heat transfer
coefficient for the Macor embedded in the flat brass plate. The equations used in the Matlab
programs use the one-dimensional semi-infinite model to calculate the heat flux and heat transfer
coefficient. Results for heat flux & the heat transfer coefficient were found. However, the
Matlab code and infrared camera readings require further validation before final conclusions can
be made.
HyperBLaF Facility
The HyperBLaF is a Mach 8 blowdown tunnel (Figure
1) used for studies of compressible turbulence, shock
wave/boundary layer interactions, shock/shock interactions
and configuration studies for hypersonic vehicles. The test
section has a diameter of 229 mm (9”), with a length of 2.0m
(6 ft). The max stagnation temperature is 870K (1100 F) at a
max stagnation pressure of 10 MPa (1500 psia). Run times
vary from approximately 2 to 10 minutes. The range of
possible Reynolds numbers allow for completely laminar flow
at the lowest value and completely turbulent boundary layers
on a flat plate at its highest value. When the tunnel turns on,
air from an outdoor storage facility is heated by traveling
through an electrically preheated pipe. Flow properties are
considered constant through the test section. Figure 1: HyperBLaF Wind Tunnel
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Infrared Camera
The camera used for infrared thermography is called the ThermoVision A320G
purchased from Forward Looking InfraRed (FLIR) Systems Inc. The package included
compatible software titled ThermaCam Researcher 2.9 which was installed on the lab computer.
The computer interfaced with the camera via a CAT-5 Ethernet cable. Technical data is
presented in Table 1.
The camera’s field of view was calculated (see Table 2) based on the distance from the
lens of the camera to the Macor, which was the object of focus. The camera has a very small
focal range, as seen by the small F-number in Table 1. The IFOV (Instantaneous Field of View)
and IPA (Instantaneous Projected Area) were calculated (see Table 2) to determine the pixel size
in the images and the image area measured by each detector in the camera’s focal plane array,
respectively.
Imaging Performance
Field of view 25 x 18.8
Close Focus Limit 0.4 m (1.31 ft.)
Focal Length 18 mm (0.7 in.)
Spatial Resolution (IFOV) 1.36 mrad
F-number 1.3
Detector Performance
Detector Type Focal Plane Array (FPA), Uncooled
Microbolometer
Spectral Range 7.5 – 13
Resolution 320 x 240 pixels
Thermal Sensitivity/ NETD 70 mK @ 30 (+86
Detector Pitch 25
Detector Time Constant Typically 12 ms
Measurement
Object Temperature Range -20 C to +120 C (-4 F to +248 F)
0 C to +350 C (+32 F to +662 F)
Accuracy C ( 3.6 F) or 2% of reading
Emissivity Correction Variable from 0.01 to 1.0
Table 1: Technical Data for ThermoVision A320G (A325)
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Equipment Validation
Based on the radiation theory presented in the Appendix 1, the camera requires inputs
describing the surrounding environment, interfering mediums, and the object being studied in
order to return accurate temperature data. First, the Macor insert, the object being studied, is
considered to be a grey-body, so the emissivity had to be measured and compared to another
source for validation. Likewise the wind tunnel viewing window (4” wide and 0.5” thick), made
out of zinc selenide, has a transmissivity factor that had to be measured and compared to data
from the manufacturer.
Figure 2A: Schematic of the different mediums accounted for to conduct infrared thermography
Spatial Resolution
Distance from Camera 0.4 m (1.31 ft) = Close Focal Limit
Width Height Area
FOV 6.982 in. 5.214 in. 36.404
IFOV 0.210 in. 0.210 in. 0.044
IPA 0.406 in. 0.406 in. 0.165
Table 2: Optical Field of View at Minimum Focal Distance
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This validation was accomplished by conducting three test trials in a simulated wind
tunnel setup (Figure 2). The ThermaCam Researcher software contains an algorithm for
estimating the emissivity and transmissivity based on the input of a “known” and an “un-
calibrated” temperature measurement. The “known” temperature is recorded for a piece of
electrical tape attached to the Macor. This tape has a known emissivity so the temperature
recorded is considered to be the real temperature. The “un-calibrated” temperature is recorded
for the Macor next to the tape, whose emissivity is not known. The environmental conditions for
the three trials are recorded in Table 3, with the “known” and “un-calibrated” temperature inputs
specified.
Environment
Conditions Trial 1 Trial 2 Trial 3
Reflected
Apparent
Temperature ( )
26.7 31.0 26.5
Ambient
Temperature ( ) 26.0 26.5 26.1
Relative
Humidity 41% 41% 41%
Temperature
Measurements
( )
Known Un-calibrated Known Un-calibrated Known Un-calibrated
59.7 59.3 55.0 54.0 52.3 52.1
Table 3: Radiation Parameter Measurements
The emissivity values obtained during these three trials (see Table 4) were averaged to
obtain the value for emissivity used to calibrate the camera for the actual wind tunnel test. The
emissivity values for the Macor were compared to a graph (Figure 3) found in the paper Infrared
Thermography for Convective Heat Transfer Measurements by Carlomagno and Cardone
Figure 2B: Simulated Wind Tunnel Setup
Infrared Camera
Wind Tunnel
Window
Macor
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because no data regarding emissivity was provided by Macor manufacturers. The emissivity
values from the FLIR for the Macor compare favorably with the values shown in Figure 3.
The wind tunnel window transmissivity measurements (see Table 4) were compared to a
graph of transmissivity (Figure 4) with respect to wavelength provided by the company for zinc
selenide windows of similar thickness (~ half). The averaged transmissivity values were
sufficiently close to the manufacturer/researcher values.
Trial 1 Trial 2 Trial 3 Average
Emissivity 0.938 0.903 0.895 0.912
Transmissivity 0.676 0.70 0.680 0.685
Table 4: Measurements for Infrared Camera Algorithm
Experimental Setup: Wind Tunnel Model
The wind tunnel test model consisted of Macor, a white glass ceramic, embedded in a
sharp, flat, brass plate (Figure 7). Macor was chosen because it has properties suitable for
studying transient heat conduction, such as low thermal conductivity and low thermal diffusivity.
It also has a relatively high emissivity which facilitates the task of calibrating the infrared
camera.
Figure 4: Manufacturer Transmission Graph for Zinc Selenide Window
Figure 3: Directional Emissivity of MACOR (Carlomagno & Cardone, 2010)
Side View
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Emissivity of the Macor & transmissivity of the window are considered constant across
the spectral range of 7.5 – 13 . Emissivity has been observed to vary with temperature, but the
influence is only significant at extremely high
temperatures (around 1273 K, experimental temperatures
were only up to 473 K). The FLIR training manual stated
that any tests conducted within a “couple hundred Kelvin”
of experimental temperature will have negligible error for
emissivity, so the trials are considered valid. (FLIR
Systems, Level I: Course Manual, 2007)
Specular radiation causes emissivity to vary with
angle between the direction of emission and the surface
normal vector. This was measured for MACOR in the
paper Infrared Thermography for Convective Heat
Transfer Measurements to show that dielectric materials
have a relatively constant emissivity if 60 . In this
experiment the angle was estimated to be 30 .
Figure 5: Geometrical Measurements for MACOR Insert and Brass Plate
Figure 6: Directional Emissivity of MACOR (Carlomagno & Cardone, 2010)
Emissivity
Angle
Top View
Side View
Top
View
Plate &
Macor
Macor
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Experimental Setup: Tunnel Setup & Software Calibration
The camera was set up on a tripod facing the wind tunnel window at an angle of ~ 30 as
shown in Figure 7. The data entered into the ThermaCam Researcher software for calibration is
listed in Table 5. The Spot Tool referenced in Table 5 is a small pointer used in ThermaCam
Researcher to specify the spot at which the user would like to measure temperature over time.
The pixel coordinates indicating where the Spot Tool was placed on the images of the Macor is
provided. A distance and emissivity value is supplied for the Spot Tool because measurement
tools in ThermaCam Researcher can be calibrated for different emissivities and object ranges.
Image Frequency 30 Images/Second
Spot Tool
X-Position (from Bottom Left) 111 pixels
Y-Position (from Bottom Left) 157 pixels
Object Distance 0.4 meters
Emissivity 0.91
Object Parameters
Emissivity 0.91
Object Distance 0.4
Reflected Temperature 26
Atmospheric Temperature 26.7
Atmospheric Transmission 1
Relative Humidity 0
Reference Temperature -273.1
External Optics Temperature 40
External Optics Transmission 0.68
Table 5: Input Values for the Infrared Camera Software used in Wind Tunnel Test
Figure 8: Side View of Experiment Setup
Figure 7: Top View of Experiment Setup
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Experimental Execution: Data Collection
The infrared camera recorded infrared images at 30 Hz and sent the images through the
CAT-5 Ethernet Cable to the computer where they were saved in FLIR’s ThermaCam
Researcher software. Each infrared image consists of an array of 76,800 pixels; equal to the
number of detectors installed on the camera’s focal plane array. Each detector generates a signal
based on the amount of infrared radiation absorbed in its IFOV. A color palette applied to the
image distinguishes areas of similar temperature. Surface temperature measurements on one
spot of the Macor are equal to the size of one pixel (which equals the area of the IFOV) was
recorded for each infrared image and saved in a text file (Table 6). All measurements were made
at the same spot across the entire run time of the tunnel. These surface temperature
measurements are graphed with respect to time in Figure 9.
ThermaCam Researcher output the temperature data measured over time at one spot as a text
file with several columns. The data used in the Matlab programs are the surface temperature data in
column 1 and the time values in column 2 (shaded in Table 6).
Temperature
( Kelvin)
Relative Time
(seconds) Date & Time
# Images
Taken
Initial
Temperature
&
Initial Time
297.213 1344376159.625 8/7/2012
5:49:19.625 PM 1
297.052 1344376159.658
8/7/2012
5:49:19.658 PM 2
297.052 1344376159.692 8/7/2012
5:49:19.692 PM 3
297.025 1344376159.725 8/7/2012
5:49:19.725 PM 4
Table 6: Text File output by ThermaCam Researcher with Surface Temperature Data
Figure 9: Surface Temperature Graph over time recorded by FLIR Infrared Camera
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The Semi-Infinite Model
Only the heat transfer methods of conduction and convection (see Table 8) are measured
in this experiment. Radiation heat transfer, which is proportional to (see Table 4), is assumed
to be negligible due to the relatively low temperatures in this experiment (298.13 –
373.13 ). As seen in the following energy balance equation, conductive and convective heat
fluxes are considered equal (Figure 10) and radiation heat flux is considered negligible:
The semi-infinite model assumes that heat transfer is one-dimensional and is occurring
through a product of low thermal diffusivity (a property satisfied by Macor material). It is called
the “thick-wall” technique because it uses the assumption that the material is infinitely thick.
The initial conditions are that at time the temperature is the initial wall temperature (see
Table 7). The model breaks down once heat has penetrated through half the thickness of the
material (1.5 cm (0.59 in.).
Heat Transfer Method
“Thick Wall”
Equation Explanations
Conduction
Convection )
Radiation
Table 8: General Heat Transfer Equations
Initial Wall Temperature 297.213
Final Wall Temperature 437.079
Total Change in Temperature 139.866
Table 7: Temperature Boundaries for the Measurement Spot on Macor
Figure 10: Semi-Infinite Model Illustration is convective heat transfer, is radiative heat
transfer, and is conductive heat transfer].
Penetration Depth
= 1.5 cm
𝑅
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Transient Heat Conduction Criteria
The period between the beginning of a heat transfer process and when the device reaches
steady state is known as the transient period where temperature varies with time and position.
Measuring heat flux allows us to understand the thermal loads on the object during the transient
period. The criterion that determines how long a body undergoes transient heat conduction
before reaching steady state is defined by Equation (1) in Table 9. A Matlab program was
written to display a graph indicating when the solution violates the boundary condition. (See
Figure 11).
The measuring time for which the semi-infinite model assumption holds is dictated by
Equation (2) (Astarita, Cardone, & Carlomagno, 2006) in Table 9.
Criteria Equation Variables Time Limit for
this Test
Tunnel Run-Time for
this test Known “ ~179.00 seconds
Transient Heat
Conduction Criteria (1)
= Penetration Depth
= thermal diffusivity
= Measurement Time
~55.00 seconds
Time Measurement
Criteria for thick-wall
technique (2)
= Penetration Depth
= Thermal Diffusivity
= Measurement Time
27.49 seconds
Table 9: Time Approximations based on material properties and dimensions
Figure 11: Graph of Transient Heat Conduction Criteria over Time
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Heat Flux Calculations
The equation derived to calculate heat flux based on temperature change across time for a
semi-infinite body is: (Astarita, Cardone, & Carlomagno, 2006)
Where = is the surface temperature difference, is the mass density, is the
specific heat, and is the thermal conductivity. It is assumed that the entire object is the same
temperature at time = 0. However, the integral becomes infinity at the upper boundary
condition which makes the equation unsuitable for use in a computer program. A different form
of the equation that approximates the solution using a piecewise function was developed in
(Cook & Felderman, 1965); where , , and are specific times within the summation and is the total time elapsed in a particular summation interval.
–
(1)
This approximation is further simplified by expanding the sum of the first two terms to
get the equation into this final form:
(2)
Equations (1) and (2) were run in Matlab using the surface temperature measurements
from the infrared camera as input and outputting a graph of heat flux over time. The order of
magnitude for heat flux is about 2-4 kilowatts in an area the size of the IFOV described earlier in
this paper (the unit label for the y-axis is inaccurate with regard to the ). The equations
should have output graphs that were visually similar, but as seen in Figure 9 there is some
discrepancy between the outputs of the two equations. One explanation is that the violation of
the transient heat conduction criteria at t = 50s caused the equations to diverge. Another possible
cause is a bug in the code relating to summations. A previous bug was discovered that caused
the solutions to cluster about the zero position because there was an error in the summation code.
Lastly, it is possible that the initial conditions for Equation (2) differ from Equation (1) and
weren’t accounted for in the code. Since the slopes of the graph change dramatically at 50
seconds, the first explanation appears to be the more likely cause. An attempt will be made in
future experiments to apply a smoothing technique to minimize the random noise.
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Findings: Heat Flux
With regard to heat flux, the implementation of the Cook-Felderman approximation in a
Matlab program proved successful in generating heat flux readings of the expected order of
magnitude. Random noise is present so more precise readings can hopefully be obtained in
future experiments using data smoothing techniques such as the “least squares” approximation.
The discrepancy between Equation (1) and (2) will also be addressed in for future experiments.
Heat Transfer Coefficient Calculations
The Heat Transfer Coefficient estimate is 28
An effective formula for determining heat transfer coefficients is found in (Astarita, Cardone, &
Carlomagno, 2006). This form is used when the heat transfer rate and the reference temperature
are constant. is the constant reference temperature, is the initial wall temperature, and
is the current wall temperature. In addition, is the complementary error function, and
, , and are mass density, specific heat, and thermal conductivity, respectively.
(3)
(4)
Using a Matlab program, Equation (4) is solved for and substituted into Equation (3) for
values of the heat transfer coefficient ranging from 0 to 500. Values of 870 and 297.213
are used for and respectively. The difference between the value generated for based
on is compared to the value of in the text file generated by ThermaCam Researcher
software. A plot of these differences or “errors” for each heat transfer coefficient value is shown
Figure 12: Output for Equation (1): Red Line = Equation (1), Blue line = Equation (2)
14
in Figure 13. The value with the lowest error is considered to be the best estimate for the heat
transfer coefficient.
Findings: Heat Transfer Coefficient
Based on the graph it appears that the best estimate for the heat transfer coefficient is a
value of 28. Unfortunately, the tolerance for this program is based on how many value are
chosen to be sampled between 0 and 500. Another program could be written to search with a
higher tolerance between the values of 27 and 29 to find a more precise value for the heat
transfer coefficient, but this is slightly inefficient. This also does not return show how the heat
transfer coefficient changes with time.
To summarize, an estimate of the heat transfer coefficient was determined using a Matlab
program. The technique described above for calculating the heat transfer coefficient has the
potential to deliver a more precise estimate but requires revision of the code based on the range
of values to sample. More importantly, the program needs to show how the heat transfer
coefficient changes with time. This can be accomplished by simply implementing the equation
for convective heat flux: )
This requires that the previous heat flux program that calculates be verified and the free-
stream temperature in the wind tunnel be matched in time with the temperature measurements , in
the ThermaCam Researcher text file.
Considerations for Future Experiments in Heat Transfer
Stanton Number
A future goal for this experiment is to calculate the non-dimensional Stanton Number
using tunnel properties and the heat flux values found in Table 10.
Figure 13: Output for Equation (3): The point of minimum is equal to the estimated heat transfer coefficient = 28.
Minimum Error
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Heat Transfer Gage Research
Initial research was conducted to determine what type of heat sensor is best to validate
the presumed absolute temperature readings from the infrared camera. Criteria for the sensors
are quite restrictive. First, the sensor must operate on the thin-film semi-infinite medium
assumption. Second, the sensor must be small so as to minimize interference with the flow
around the model, but also large enough to be observed properly with the infrared camera
(diameter no less than
of an inch). Lastly, the sensor must be able to withstand the tunnel
conditions, which cover run times from 2 to ten minutes long, and a stagnation temperature as
high as 500 .
Two options are currently available that meet these criteria. The first is a differential
thermopile sensor (called HFM’s) from a company called Vatell. These sensors have the lowest
time constant in the field (300 ). They also present the option of purchasing either a resistance
temperature sensor or a thermocouple design. They can withstand up to 700 . The sensors are
short enough to be fully embedded in the Macor. These sensors ship along with software
designed to compute heat flux over time. Thermopiles are known to have good-signal-to noise
ratio and the Resistance Temperature Sensor outputs an accurately linear “temperature vs.
resistance” graph. However, the advantages of these heat flux sensors are offset by the fact that
they cost three times as much as other competing sensors.
The competing sensor is a heat flux transducer that uses a Gardon Gage design. The
device can withstand up to 500 in the wind tunnel via heat sink/water cooling. The sensitivity
is on the order of milli-volts instead of micro-volts for the HFM’s. The time constant is on the
order of milliseconds as opposed to microseconds for the HFM’s. This sensor has a more
affordable cost comes with an optical black coating that gives it a high emissivity (favorable for
infrared thermography). An optical coating is optional for the HFM sensors.
Stanton Number
(Dimensionless Parameter)
𝑅
Table 10: Description of the Stanton Number for Future Calculations
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Literature Cited (References) 1Carlomagno, Giovanni M.; Cardone, Gennaro. (last edited August 3, 2010). Infrared
Thermography for convective heat transfer measurements. Exp Fluids (2010) 49:1187-
1218.
2
( November 19, 2007). User’s manual: ThermoVision A320;TermoVision A320G. FLIR
Systems,Inc.
3 (2007) ThermoVision A320G: Infrared Camera System. FLIR Systems, Inc
4 Simeonides, George. (1992). Infrared Thermography in Blowdown and Intermittent Facilities.
VKI
5
(2007). FLIR Systems, Inc. Level I Course Manual. Infrared Training Center: N. Billerica:
Massachusets
9Corning Incorporated. Lighting & Materials. Corning: New York
6T. Astarita, Cardone, Gennaro,Carlomagno, Giovanni M. (last edited May 23, 2005). Infrared
Thermography: An optical method in heat transfer and fluid flow visualization. Optics &
Lasers in Engineering 44 (2006) 261-281
7de Luca, Luigi; Cardone, Gennaro. Viscous Interaction Phenomena in Hypersonic Wedge
Flow. AIAA VOl. 33, No. 12, pp. 2293-2298
8Rathore, M.M.; Kapuno, Jr., Raul R.A. Engineering Heat Transfer: Second Edition. Jones &
Bartlett Learning: Ontario. (2011)
9Cook, W.J.; Felderman, E.J. Reduction of Data from Thin-Film Heat-Transfer Gages: A
Concise Numerical Technique. AIAA Vol. 4, No. 3, pp 561-562.
10
Cook, W.J. Determination of Heat-Transfer Rates from Transient Surface Temperature
Measurements. AIAA Vol. 8, No. 7, pp. 1366-1368
17
Appendix 1
Infrared Thermography (IRTh) requires an understanding of radiation starting with the concept
of the electromagnetic spectrum and the existence of blackbodies. Good overviews are found in
(Buchlin, 2010), (Meola & Carlomagno, 2004), and (Carlomagno & Cardone, 2010), as well as
in the software documentation for all FLIR infrared thermography products. Planck’s law
dictates the emissive power (i.e. radiative heat flux) of a blackbody as a function of wavelength:
is absolute temperature, is the wavelength, is Boltzmann’s constant, and is Planck’s
constant. Boltzmann’s law follows from the integration of Planck’s law across all wavelengths,
giving the total emissive power of a blackbody over the entire spectrum.
The Stefan-Boltzmann constant (a simple constant of proportionality) is equal to
. Most real objects, however, are not blackbodies and only emit a fraction of their
actual blackbody emissive power for any specific temperature. These are called grey-bodies and
a correction factor known as emissivity is added to Boltzmann’s law to calculate heat flux for
grey-bodies. Emissivity can be a constant, but usually is a function varying with surface state,
temperature, and viewing angle (Simeonides, 1992). The equation of radiative heat flux for a
grey-body is:
The following equation dictates all the radiation from an object that the camera can see.
Absorbance , reflectance , and transmittance are all ratios of greybody radiance to blackbody
radiance over blackbody radiance at a specific wavelength:
It is usually assumed that the grey-body follows Kirchhoff’s Law, which is described by the
equality below.
For opaque bodies, transmittance is equal to zero, and the equation becomes:
Lastly, the Wien Displacement Law is obtained by differentiating Planck’s law. The expression
relates a particular wavelength to its max blackbody temperature,
Units of (
is the temperature in degrees Kelvin and is wavelength in micro-meters. Based on this
theory, the emissivity, transmissivity, and reflectivity had to be calculated using a well-
documented procedure.
0
Appendix 2 Company Vatell Vatell Medtherm SWL Germany SWL Germany SWL Germany SWL GermanySensor Name HFM - 8 - E/H HFM - 7 - E/H Heat Flux Transducer
Model Number None None 4-200-.125-36-20942 Standard model KL MI MI with thread M 3.5 MI with pressure tap and adapter
Important Properties
Heat Flux Range Not Advertised Not Advertised 200 Btu/ft^2.sec
Peak Operating Temperature 700 C 700 C 400 C
Uncoated Response Time 17 µs 17 µs ~10ms
Coated Responset Time 300 µs 300 µs Not Applicable
Sensor-Specific Properties
Pressure Tap No No No No No No Yes
Temperature Sensor Thermocouple--Type E RTS Not Applicable Thermocouple--Type E or Type K Thermocouple--Type E or Type K Thermocouple--Type E or Type K Thermocouple--Type E or Type K
Heat Flux Sensor Differential Thermopile Differential Thermopile Transducer--Gardon Gage
RTS Metal Not Applicable Platinum Not Applicable
RTS Resistance Not Applicable 100-200 ohms Not Applicable
Temperature Sensor Resistance Not Applicable 0.25-0.35 ohms/ C Requires Heat Sink/Cooled Model
Min. Sensitivity 150 µV/W/cm^2 150 µV/W/cm^2 10 mV at 200 Btu/ft^2.sec
Physical Attributes
Diameter 0.25 in. 0.25 in. 0.0625 in. 1.9 mm 4.8 mm/3.6 mm 3.5 4.8 mm/3.6 mm
Lead Wire Material (Temp Resist.) Mineral Sheath (350 C) Mineral Sheath (350 C) AWG Solid Copper w/ Teflon Inslation
Lead Wire Length ~ 36 in. ~ 36 in. 36 in.
Body Length 0.96 in. 0.96 in. 0.125 in. 20 mm 12 mm 12 mm 12 mm
Sensor Material Nichrome/Constantan Nichrome/Constantan
Body Material Nickel Housing Nickel Housing OFHC Copper/ Aluminum Alloy chromel/constantan--chromel/alumel chromel/constantan--chromel/alumel chromel/constantan--chromel/alumel chromel/constantan--chromel/alumel
Lab/Experimental Concerns
Price $3,285 $3,285 $1,331.00
Shipping Time 3-4 weeks 3-4 weeks ~ 5 weeks
Mounting (Thread or Flush Mount) 1/2-20 THD or M12 x 1.75 1/2-20 THD or M12 x 1.75 Not Specified
Coating Otpional Coating--Emissivity = 0.94 Optional Coating--Emissivity = 0.94 Standard "Optical Black" Coating
Output Heat Flux & Temperature Heat Flux & Temperature Heat Flux
Data Acquisition
Connection 4-pin Lemo Connector 4-pin Lemo Connector Need to call company back
Thermocouple Characterization Function T = a * V^3 + b * V^2 + c * V + d T = a * V^3 + b * V^2 + c * V + d
Base Temperature Resistance Not Applicable R_o = e * T_o + f
Resistance relation to Voltage Output Not Applicable ((V_rts) / (I_rts * G_rts)) + R_o
Thermocouple Voltage Output V_tc/G_tc Not Applicable
Heat Flux Computation q = (V_hfs/G_hfs) / (g * T + h) Not Applicable
Convection Computation q = h * del_T = (V_o(E))/ S_in q = h * del_T = (V_o(E))/ S_in
Compare/Contrast
Linearity of Output Non-linear output for thermocouple Linear Output for RTS
Extra Purchase Items Vatell AMP-6 (Amplifier) Vatell AMP-6 (Amplifier)
Sensor Performance thermopile = good signal-noise ratio thermopile = good signal-noise ratio