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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations

This report is an archived publication and may contain dated technical, contact, and link information
Publication Number: FHWA-RD-02-071
Date: March 2005

Study of LTPP Pavement Temperatures



Since its inception, the Long Term Pavement Performance (LTPP) program has been collecting temperature data from the General Pavement Studies (GPS) and Specific Pavement Studies (SPS) test sections. Temperature has a strong effect on pavement deflection test results, primarily in asphalt concrete (AC), but also in portland cement concrete (PCC) structures. Adjustment for temperature is made to deflection test results; and, for this reason, complete and accurate data on surface temperature and in-depth temperature of pavement structures are needed for future LTPP analysis and research. This study documents the first detailed review of the LTPP pavement temperature data elements. The report assesses the completeness and quality of the data, identifies anomalies in the data, and concludes with recommends for remedial action for these anomalies.

The stiffness, or modulus, of AC is extremely sensitive to temperature. Routine deflection test results usually are adjusted to represent the deflection at a standard temperature or some other reference temperature, or the back-calculated modulus must be adjusted to the modulus expected at some selected seasonal temperature. Several procedures have been developed to adjust for temperature; however, most of these have been based on limited data.

Although the stiffness, or modulus, of PCC is not as temperature sensitive, the deflections measured on jointed PCC pavements are affected by the temperature gradient present in the slab because of "curling" and "warping" effects. Generally, curling occurs during nighttime and early morning when the temperature gradient in the PCC is positive from top to bottom (warmer at the bottom). Warping generally occurs between late morning and early evening when the temperature gradient in the PCC is negative from top to bottom (warmer at the top from solar radiation). The PCC temperatures also have a major effect on joint load transfer because of thermal expansion or contraction of the concrete panels and the corresponding effect on joint openings.

For these reasons, it is important that the Information Management System (IMS) contain correct and useable pavement temperature data. The temperature dataset generally has been collected in the Long Term Pavement Performance (LTPP) program according to protocols established for pavement monitoring. LTPP temperature measurements generally are conducted in conjunction with falling-weight deflectometer (FWD) deflection testing. Three procedures are used to measure pavement temperature:

  • Infrared (IR) sensors mounted on a FWD measure surface temperatures. One temperature reading is made through the FWD's automated software at each deflection test location.
  • Manual in-depth pavement temperature measurements from holes drilled at each end of the test section to specified depths in the pavement. The in-depth temperatures are measured manually with a hand-held digital thermometer. The digital thermometer has a probe that is placed in the bottom of each hole. A small amount of heat transfer liquid (mineral oil or glycol) is placed in the bottom of the hole to transfer the pavement temperature to the probe.
  • For selected Seasonal Monitoring Program (SMP) sections, permanent placement of thermistors at pavement subgrade. Onsite data loggers read the temperature from each of the thermistors and record the average temperatures hourly. Data from the SMP provides more detailed information on daily and seasonal variations in pavement temperatures.

It is difficult to distinguish how well or poorly the three temperature measurements correlate with one another, which one produces the most accurate data, or what the degree of variation is among the three methods.


The principal objective of this study is to provide the best data possible for future LTPP analysis and research. The study attempted to estimate the precision and bias of the temperature measurement variables.


The data that have been uploaded into Level E of the Information Management System (IMS) database have passed broad screening criteria. For this project, we evaluated for comparative reasonableness all of the manual and IR temperature data that have reached Level E. For example, a number of fields that contain numbers and temperatures should fall within a reasonable range. The quality control range listed in the data dictionary for the manual temperature is -11.1 °C to 50 °C (12 °F to 122 °F). We evaluated the data for errors, biases, and missing observations.

The following paragraphs provide more detail on the three pavement temperature measurement methods.

Infrared Surface Pavement Temperature

As 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. The FWD field data files are returned to the regional coordination office where the files are filtered into the IMS using FWDSCAN, a quality control software used to check the FWD data for completeness and readability.

Manual In-Depth Pavement Temperatures

Temperatures are measured at two locations, generally about a meter before and after the test section. The temperature measuring protocol is contained in the FWD field operation manual.(1) 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. In composite sections, the three depths apply to the concrete, and two additional holes are placed to get asphalt temperatures at 25 mm from the top and bottom of the asphalt overlay. Heat transfer fluid is placed in the bottom of each hole, and a tip-reading temperature probe is placed into the liquid (about 10 mm to 12 mm of mineral oil or glycol to prevent evaporative cooling and freezing). The temperature is read with a digital thermometer that displays the temperature to a resolution of -18 °C (0 °F). 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, and the sky cover. The data on forms are recorded manually in the database in the regional coordination office.

Seasonal Monitoring Program Pavement Temperatures

All Seasonal Monitoring Program (SMP) sites are fitted with temperature, moisture, and weather instrumentation.(2) The temperature instrumentation in the pavement consists of 300-mm stainless steel tubes or rods fitted with three thermistors, one at each end and one in the middle. The rods, which are placed in slots cut into the pavement, are angled so that the top of the rod is 25 mm below the surface and the bottom of the rod is 25 mm above the bottom of the asphalt or concrete. A data logger monitors the thermistors and the weather instruments, reading the thermistors every minute. A data logger records the average hourly reading at the end of each hour. While the thermistor data are not time-specific, they do provide a good characterization of the diurnal and seasonal temperature variations. A review of the thermistor data was a lower priority for this project because these data already are evaluated as part of the SMP data screening and filtering. The thermistor data for the first two rounds of SMP testing were compared with both the manual and IR data by Lukanen et. al.(3) in an earlier study.


Chapter 2, "Data Extraction and Processing," describes the data fields used and how the data were evaluated. Chapter 3, "Errors Found and Responses," describes the type of errors found and the extent of the errors by error type. Chapter 4, "Recommendations," offers recommendations for the correction of data errors and minimization of such errors in the future.

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