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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 |
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Publication Number: FHWA-HRT-08-035 Date: March 2008 |
PDF version (872 KB)
The ability to accurately monitor subsurface soil parameters on a continuous basis is extremely beneficial in pavement design, evaluation, and performance prediction. The time domain reflectometry (TDR) data collected as part of the Long Term Pavement Performance seasonal monitoring program (SMP) can be used to estimate moisture content, conductivity, reflectivity, and density. This report provides valuable information on calculating these parameters utilizing TDR traces and documents the process of interpreting over 270,000 TDR traces taken at SMP sites across North America.
In situ data availability is critical to pavement engineering, particularly as the process moves toward mechanistic-empirical techniques. This study not only provides useful information from in-service pavements, but also provides a method that can be utilized by State highway agencies interested in monitoring subsurface conditions and analyzing their effect on pavement response.
Gary Henderson
Director, Office of Infrastructure Research and Development
This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the information contained in this document. This report does not constitute a standard, specification, or regulation.
The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.
The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.
TECHNICAL REPORT DOCUMENTATION PAGE
1. Report No. FHWA-HRT-08-035 |
2. Government Accession No. |
3. Recipient's Catalog No. |
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4. Title and Subtitle LTPP Computed Parameter: Moisture Content |
5. Report Date January 2008 |
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6. Performing Organization Code |
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7. Author(s) D. Zollinger, S. Lee, J. Puccinelli, and N. Jackson |
8. Performing Organization Report No. 1236.10 |
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9. Performing Organization Name and Address Nichols Consulting Engineers Texas A & M |
10. Work Unit No. (TRAIS) |
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11. Contract or Grant No. DTFH61-02-D-00139 |
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12. Sponsoring Agency Name and Address Office of Infrastructure R&D |
13. Type of Report and Period Covered Final Report July 2005 to September 2007 |
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14. Sponsoring Agency Code |
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15. Supplementary Notes Contracting Officer's Technical Representative (COTR): Larry Wiser, Long Term Pavement Performance Team |
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16. Abstract A study was conducted to compute in situ soil parameters based on time domain reflectometry (TDR) traces obtained from Long Term Pavement Performance (LTPP) test sections instrumented for the seasonal monitoring program (SMP). Ten TDR sensors were installed in the base and subgrade layers at each of the 70 SMP test sites monitored as part of the LTPP program. A comprehensive description of a new method developed as part of the study to estimate moisture content, dry density, reflectivity, and conductivity of the soil from TDR traces is provided in the report. This new method utilizes transmission line equations and micromechanics models calibrated to site-specific conditions for each site/layer combination. Background information on existing empirical methodologies used to estimate subsurface moisture content from TDR traces is also documented. The results were compared to previous methods as well as ground truth data to evaluate the ability of the new model to predict soil parameters. The transmission line equation and micromechanics method was found to provide accurate results and was used to interpret over 270,000 TDR records stored in the LTPP database. A computer program (MicroMoist) was developed to aid in the computation of soil parameters based on TDR trace data and calibration information. Details on the program are provided along with descriptions of the tables developed to store the computed values in the LTPP Information Management System database. |
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17. Key Words LTPP, SMP, TDR, moisture content, soil parameters, dry density, reflectivity, conductivity, transmission line equation, micromechanics, pavements |
18. Distribution Statement No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161. |
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19. Security Classification (of this report) Unclassified |
20. Security Classification (of this page) Unclassified |
21. No. of Pages 104 |
22. Price |
Form DOT F 1700.7 (8-72) Reproduction of completed pages authorized
CHAPTER 2. BACKGROUND AND LITERATURE REVIEW
CHAPTER 4. COMPUTER PROGRAM DEVELOPMENT
CHAPTER 5. PARAMETER COMPUTATION AND QUALITY REVIEW
CHAPTER 6. LTPP DATABASE DELIVERY
CHAPTER 8. RECOMMENDATIONS FOR FUTURE RESEARCH
CHAPTER 9. SUMMARY AND CONCLUSIONS
APPENDIX A. TRANSMISSION LINE EQUATION
APPENDIX B. CHARACTERIZATION OF ERROR IN THE SID
APPENDIX C. MICROMOIST USER'S MANUAL
Figure 1. Diagram. TDR probe for SMP
Figure 2. Graph. Typical TDR signal
Figure 3. Diagram. Illustration of instrumentation installation
Figure 4. Graph. Illustration of trace interpretation methods
Figure 5. Flowchart. Volumetric moisture model selection process
Figure 6. Diagram. Soil mixture with volume of soil solids equal to 1
Figure 7. Diagram. Coaxial line dimensions
Figure 9. Bar Chart. Errors in volumetric moisture content estimates (calibration validation)
Figure 10. Bar Chart. Errors of volumetric moisture contents on ground truth data
Figure 11. Bar Chart. Errors of laboratory estimated dry density on ground truth data
Figure 12. Bar Chart. Errors of volumetric moisture contents on ground truth data
Figure 13. Bar Chart. Errors of estimated dry density on ground truth data (field validation)
Figure 14. Photo. Interface of new program
Figure 15. Graph. Inflection points in TDR trace
Figure 16. Flowchart. Determination of inflection points
Figure 17. Flowchart. Calculation of dielectric constant, conductivity, and reflectivity
Figure 18. Flowchart. Calculation of moisture content and dry density
Figure 19. Graph. TDR traces of Section 308129, TDR No. 8
Figure 20. Diagram. Three separate phases of a soil element
Figure 21. Diagram. Profile of TDR and depth at each layer
Figure 22. Graph. Uninterpretable TDR trace
Figure 23. Graph. Incomplete TDR trace
Figure 24. Graph. Shift zone in LTPP section 091803, TDR sensor No. 7
Figure 25. Graph. Soil-water characteristic curve for sandy soil
Figure 26. Diagram. Diagrams of soil having different volume
Figure 27. Graph. Comparison of SWCC and VMC-DC trend
Figure 28. Graph. Sample plot of moisture content seasonal trend
Figure 29. Graph. Results from the apparent length approach for LTPP section 063042
Figure 30. Graph. Results from the TLE micromechanics method for LTPP section 063042
Figure 31. Graph. Results from the apparent length approach for LTPP section 313018
Figure 32. Graph. Results from the TLE micromechanics method for LTPP section 313018
Figure 33. Graph. Time-harmonic function V(t)
Figure 34. Graph. Electric field as a function of z direction at different times
Figure 35. Diagram. Coaxial line
Figure 36. Graph. Cylindrical coordinate system
Figure 37. Diagram. Coaxial line developed into a parallel-plate waveguide
Table 1. Instrumentation for SMP
Table 2. SMP core experiment sectioning category
Table 3. Coefficient for mixing model
Table 4. Third order polynomial Ka-soil model parameters
Table 5. Refined third order polynomial Ka-soil model parameters
Table 6. Comparison of volumetric moisture contents during TDR installation
Table 7. Calibrated and calculated values determined by micromechanics method
Table 8. Calibration of dielectric constants by transmission line equation
Table 9. Comparison of moisture contents
Table 10. Calibration of dielectric constants for Section 091803
Table 11. Comparison of moisture contents for Section 091803
Table 12. Overview of LTPP MicroMoist program
Table 13. Dry density adjustment of Section 331001 and 533813
Table 14. Calibrated values of Section 331001 and 533813
Table 15. Field names and description of MICROMOIST_SMP_TDR_AUTO table
Table 16. Field names and description of MICROMOIST_SMP_TDR_DEPTHS_LENGTH table
Table 17. Field names and description of MICROMOIST_SMP_TDR_CALIBRATE table
Table 18. Field names and description of MICROMOIST_SMP_TDR_AUTO_DIELECTRIC table
Table 19. Field names and description of MICROMOIST_SMP_TDR_AUTO_MOISTURE table
Table 20. Error codes used in the program
Table 21. Description of SMP_TDR_CALIBRATE table for the LTPP IMS Database
Table 22. Description of SMP_TDR_MOISTURE table for the LTPP IMS Database
AASHTO | American Association of State Highway and Transportation Officials |
AC | asphalt concrete |
FHWA | Federal Highway Administration |
IMS | Information Management System |
LTPP | Long Term Pavement Performance |
QC | quality control |
SID | system identification method |
SMP | seasonal monitoring program |
SPS | Specific Pavement Study |
SWCC | soil-water characteristic curve |
TDR | time domain reflectometry |
TEM | transverse electromagnetic mode |
TLE | transmission line equation |
VMC | volumetric moisture content |
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