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In this Study, Linear
regression analysis was done to develop a predictive model which predicted
temperature at various depths considering both Air Temperatures and Surface
Temperatures. The input variables for the modelling are Pavement Surface
Temperature, Air Temperature and depth. The surface temperature of the pavement
was obtained from FWD testing data. An assembly of data was done with the
temperature at various depths, surface temperature and air temperature. The
relationship between interpolated temperature and manual temperature was
checked and was obtained to be positively correlated. The accuracy of data
interpolation was shown using a bar chart. Scatter plots were used to find
relationships between individual parameters such as pavement surface
temperature vs air temperature, pavement surface temperature and temperature at
a depth of 25mm, 50mm and 100mm. Then after obtaining positive linear
relationship between these parameters data analysis was conducted, and a
predictive model was built. The model was then used to predict temperature
using just pavement surface temperature, air temperature and depth values.
However, the model was not able to predict temperature after the depth of 100mm
as the temperature data for all the sections could not be obtained and the
relationship between the depth and change in temperature was not linear. Thus,
for predicting temperature the main factors to be considered are surface
temperature and air temperature. The change in temperature according to depth
of pavement should also be carefully considered as the change in temperature
was found to be linear for certain depth under the pavement. Since pavement
temperature and air temperature data remains critical in predicting pavement
temperature at various depths independent checks should also be performed to
ensure accuracy of temperature data. Temperature of pavement
is one of the most influencing factor in both Asphalt pavements and rigid
pavements. The stiffness, or modulus, of AC is
extremely sensitive to temperature. Deflection testing is used to evaluate
variety of pavement characteristics, including axle or vehicle load capacity,
structural life, and uniformity. Deflection test results are dependent on
seasonal variation. To get correct deflection results it should be adjusted
according to temperature values. Temperature and moisture affect
deflection response of both flexible pavements (asphaltic concrete) and rigid
pavements (Portland Cement Concrete). The stiffness (rigidity) of asphalt
concrete (AC) is very sensitive to temperature changes occurring over both long
term (seasonal) and short term (hourly) periods. As the temperature of the
pavement increases, the magnitude of deflection from a given impulse load will
increase if all other factors remain the same. Therefore, deflections measured
on a hot summer day will be larger than the deflections measured during a
cooler period. Also, changes in temperature with depth (vertical temperature
gradients) influence stresses in the AC layer. The influence of vertical
temperature gradients becomes more pronounced as the thickness of the AC
increases. 5 Therefore, Temperature has a vital role
in predicting pavement characteristics. The temperature values for the state of
TEXAS can reach up to 110 F. These temperature values have profound effects on
the test that are done on test sections. The report uses several temperature
values to predict temperature at various depths. The surface temperature of the
pavement is measured during the FWD testing using IR sensors. The
FWD computer automatically records the information. Associated information
includes the site number, date of test, and time of test. Air temperature is
another important parameter that contributes to the temperature at various
depth of the pavement. Several instruments are used to record temperature.
Thermistors, a type of resistor whose resistance is dependent on temperature is
used at various depths to record temperatures. Manual in-depth pavement
temperature measurements from holes drilled at each end of test section to
specified depth in the pavement. Temperatures are measured at two locations,
generally about a meter before and after the test section. The in-depth
temperature is measured manually with a hand-held digital thermometer. The
temperatures are measured about every half hour and hand recorded on a form,
along with information about the station and site number, time and date of the
measurement, depth of the hole. 2 Linear interpolation is a
technique that is used to find temperature at various depths as temperature
follows linear trend and the interpolated values are compared with the manually
recorded temperatures. The temperature data are obtained from LTPP (Long Term
Pavement Performance) database and Seasonal Monitoring Program (SMP) sections. 1.     
BackgroundThe use of surface
deflection of pavements has increased popularity with highway agencies as it is
used to characterize various aspects of pavement such as including axle or
vehicle load capacity, structural life, and uniformity. 1 Deflection
equipment and analysis methodologies have continued to improve over the years,
but the study of the effects of temperature on the deflections of asphalt
pavements have generally been limited in scope or location. The Seasonal
Monitoring Program (SMP) of Long Term Pavement Performance program provides the
most comprehensive temperature and deflection data set ever to be assembled.
The purpose of the SMP is to obtain a fundamental understanding of the
magnitude and impact of temporal variations in pavement response and material
properties due to the separate and combined effects of temperature, moisture,
and frost variations. Various approaches have been put forward which predicts
temperature. The Braun Intertec
Corporation presents improved methods of estimating the temperature within an
asphalt pavement based on the measurement procedure used for the LTPP program.
The data necessary to estimate the temperature within the asphalt included the
surface temperature, time of the day, depth below the surface and the average
air temperature from the previous day. The LTPP program’s SMP is the source of
all the data used in the study. Some of the environmental factors include
temperature and seasonal effects on pavement deflection response to load. The
SMP requires much more intensive monitoring than the rest of the LTPP program.
The purpose of the study was to establish methods of predicting asphalt
temperatures from surface temperature measurements. The objective of the paper
was to develop new coefficients for the BELLS temperature prediction
model.  The equation was developed to
predict temperature within asphalt pavements at the third-depth. Independent
variables used in the equation include surface temperature, time of test, the
previous 5-day average air temperature, and the depth to the third-point. The
other objective is to determine if improvements could be made in the BELLS model
and whether previous 5-day average air temperature, which is difficult to
obtain, could be replaced by a more easily obtained air temperature.The 5-day air
temperature has proven to be difficult to obtain for routine testing; the
previous day’s air temperature is more easily obtained by the FWD
operator.  Sources, such as local radio
or newspapers, can provide a recent temperature history.  For LTPP data analysis, the 5-day air
temperature can be obtained from the climatic database that is associated with
LTPP; however, agencies performing routine testing have no easy source for such
information. Based on the information the report also used air temperature that
was easily obtained. The air temperature was taken from the same database where
surface temperature was measured. Consulpav International focuses on the quality
of the pavement temperature data in the Long Term Pavement Performance program.
The LTPP database is now undergoing various quality investigations focusing on
comparisons of the data from two independent sources—infrared surface
temperature measurements that were recorded automatically and in-depth
temperature measurements that were made manually. The comparative processes
identified various data errors and errors in associated data elements such as
the time measurement.

 A study done in University of Wyoming came up
with a transient, two-dimensional finite-difference model is developed to
assess temperature fluctuations in asphalt pavements due to thermal
environmental conditions. Fluctuations in temperatures significantly affect
pavement stability and the selection of asphalt grading used in pavements. The
ability to accurately predict asphalt pavement temperature at different depths
and horizontal locations based on thermal environmental conditions will greatly
help pavement engineers in performing back-calculations of pavement modulus
values and in selecting the asphalt grade to be used in various pavement lifts
through detailed examination of predicted pavement temperature distributions on
various pavement mixes. As part of the model validation, sensitivity analyses
are performed to study the impact of a number of thermal environmental and
pavement geometric parameters on predicted temperature responses. A two-dimensional finite difference model is
presented that can determine temperatures on an hour-by-hour basis at any
arbitrary point in an asphalt pavement. The model considers thermal ambient
conditions, such as the ambient dry bulb temperature, global solar radiation
intensity, pavement geometry and orientation, ambient wind conditions and
pavement thermal properties. 3The Long Term Pavement
Performance (LTPP) program is the largest source of data required for pavement
research and analysis. It was initiated in 1987 as part of Strategic Highway
Research Program (SHRP). The program has monitored more than 2500 sections all
over United States of America and Canada. LTPP data has been used to provide $2
billion in saving and as the program continues
to monitor existing test sections and constructs new experiments, it provides
enormous potential for development of products to further improve pavement
technology for decades to come. There are 44 Test sections used in the report
which are extracted from LTPP. The website for the program is available online
all the time and goes by the name of Infopave. The FHWA/LTPP updates the database
information on this website periodically.  The material contained on this
website may have inaccuracies or typographical errors. Therefore, independent
check should be done for better accuracy and good results.The
data that were collected from LTPP for analysis were:3.1.1 Infrared Surface Pavement TemperatureAs part of the
deflection testing process, an IR temperature sensor measures the temperature
of the surface of the pavement under the FWD at the end of each test sequence.
The FWD computer automatically records the information. Associated information
includes the site number, date of test, and time of test.3.1.2 Manual In-Depth Pavement TemperaturesTemperatures are
measured at two locations, generally about a meter before and after the test.
Holes are drilled in the pavement to depths of 25 mm below the
surface, at mid depth, and 25 mm above the bottom of the asphalt or concrete.3.1.3 Air Temperature The air temperature is also recorded during
FWD testing at the same time the pavement surface temperature is recorded. As
new method was developed to use easily available Air Temperature data instead
of using 5-day Air temperature. This facilitates to assemble the temperature
data as air temperature and surface temperature are on adjacent cells. Air
temperature data are taken in very short intervals.3.1.4 Depth

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The depth of
location of thermometers are also extracted for corresponding temperature
results. Temperature depths are located for five locations where thermometers
are installed. The temperature depth data are also extracted from LTPP database
and later it is match with the reading of temperature.

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