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Publication Number: FHWA-HRT-08-035
Date: March 2008

LTPP Computed Parameter: Moisture Content

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FOREWORD

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

Notice

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.

Quality Assurance Statement

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.

4. Title and Subtitle

LTPP Computed Parameter: Moisture Content

5. Report Date

January 2008

6. Performing Organization Code

7. Author(s)

D. Zollinger, S. Lee, J. Puccinelli, and N. Jackson

8. Performing Organization Report No.

1236.10

9. Performing Organization Name and Address

Nichols Consulting Engineers
1885 South Arlington Avenue
Suite 111
Reno, NV 89509-3370

Texas A & M
Zachry Department of Civil Engineering
503E CE/TTI Building
College Station, TX 77843

10. Work Unit No. (TRAIS)

11. Contract or Grant No.

DTFH61-02-D-00139

12. Sponsoring Agency Name and Address

Office of Infrastructure R&D
Federal Highway Administration
6300 Georgetown Pike
McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report

July 2005 to September 2007

14. Sponsoring Agency Code

15. Supplementary Notes

Contracting Officer's Technical Representative (COTR): Larry Wiser, Long Term Pavement Performance Team

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.

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.

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


Metric Conversion Chart


TABLE OF CONTENTS

CHAPTER 1. INTRODUCTION

CHAPTER 2. BACKGROUND AND LITERATURE REVIEW

CHAPTER 3. RESEARCH APPROACH

CHAPTER 4. COMPUTER PROGRAM DEVELOPMENT

CHAPTER 5. PARAMETER COMPUTATION AND QUALITY REVIEW

CHAPTER 6. LTPP DATABASE DELIVERY

CHAPTER 7. DATA OBSERVATIONS

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

REFERENCES

LIST OF FIGURES

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 8. Graph. Bounding of dielectric constant as a function of the computed volumetric moisture content (q ) using equation 28

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

LIST OF TABLES

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

LIST OF ACRONYMS AND ABBREVIATIONS

AASHTOAmerican Association of State Highway and Transportation Officials
ACasphalt concrete
FHWAFederal Highway Administration
IMSInformation Management System
LTPPLong Term Pavement Performance
QCquality control
SIDsystem identification method
SMPseasonal monitoring program
SPSSpecific Pavement Study
SWCCsoil-water characteristic curve
TDRtime domain reflectometry
TEMtransverse electromagnetic mode
TLEtransmission line equation
VMCvolumetric moisture content

 

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