Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296

Long Term Pavement Performance 

Computed Parameter: Frost Penetration

Publication No. FHWA-HRT-08-057 NOVEMBER 2008
FOREWORD

In-situ data availability is vital to pavement engineering. As the pavement design process moves 

toward mechanistic-empirical techniques, knowledge of seasonal changes in pavement structural 

characteristics becomes critical. Specifically, frost penetration information is necessary for 

determining the effect of freeze and thaw on pavement structural responses. This report describes 

a methodology for determining frost penetration in unbound pavement layers and subgrade soil 

using electrical resistivity, moisture, and temperature data collected for instrumented Long Term 

Pavement Performance (LTPP) Seasonal Monitoring Program (SMP) sites. The report also 

contains a summary of LTPP frost depth estimates and a detailed description of the computed 

parameter tables containing frost penetration information for LTPP SMP sites. 

The report will be of interest to highway agency engineers as well as researchers who will use 

the LTPP frost penetration data to improve pavement design and analysis procedures. In addition 

to the information from the LTPP in service pavements, a method for monitoring frost depth 

presented in this report can be utilized by State highway agencies interested in monitoring 

freeze-thaw conditions in unbound pavement layers. 

 

 Gary L. 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 use of 

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-08-057 

2. Government Accession No. 3. Recipient’s Catalog No. 

 

5. Report Date 

November 2008 

4. Title and Subtitle 

LTPP Computed Parameter: Frost Penetration

6. Performing Organization Code 

7. Author(s) 

O.I. Selezneva, Y.J. Jiang, G. Larson, and T. Puzin 

8. Performing Organization Report No. 

9. Performing Organization Name and Address 10. Work Unit No. 

Applied Research Associates, Inc. 

7184 Troy Hill Drive, Suite N 

Elkridge, Maryland 21075-7056 

11. Contract or Grant No. 

DTFH61-02-D-00138 

13. Type of Report and Period 

Safety Evaluation 

Final Report 

12. Sponsoring Agency Name and Address 

Office of Infrastructure Research and Development 

Federal Highway Administration 

6300 Georgetown Pike 

McLean, Virginia 22101-2296 14. Sponsoring Agency Code 

15. Supplementary Notes 

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

16. Abstract 

As the pavement design process moves toward mechanistic-empirical techniques, knowledge of seasonal changes in pavement 

structural characteristics becomes critical. Specifically, frost penetration information is necessary for determining the effect of 

freeze and thaw on pavement structural responses. This report describes a methodology for determining frost penetration in 

unbound pavement layers and subgrade soil using temperature, electrical resistivity, and moisture data collected for instrumented 

Long Term Pavement Performance (LTPP) Seasonal Monitoring Program (SMP) sites. The report also contains a summary of 

LTPP frost depth estimates and a detailed description of the LTPP computed parameter tables containing frost penetration 

information for 41 LTPP SMP sites. The frost penetration analysis methodology and the accompanying E-FROST program is used 

in-situ soil temperature as a primary source of data to predict frost depth in unbound pavement layers. In addition to temperature 

data, electrical resistivity and moisture data were used as supplemental data sources for the analysis when temperatures were close 

to the freezing isotherm. The Enhanced Integrated Climatic Model (EICM) was used to fill intermediate gaps in the measured soil

temperature data. 

17. Key Words: Pavements, LTPP, frost 

penetration, freeze state, ER, soil temperature, 

EICM, TDR, moisture. 

18. Distribution Statement 

No restrictions. This document is available to the public through the National 

Technical Information Service, Springfield, VA 22161. 

19. Security Classif. (of this report) 

Unclassified 

20. Security Classif. (of this page) 

Unclassified 

21. No. of Pages 

92 

22. Price 

Form DOT F 1700.7 (8-72) Reproduction of completed pages authorized
ii 
iii 

TABLE OF CONTENTS 

CHAPTER 1. INTRODUCTION.................................................................................................1

BACKGROUND ......................................................................................................................1

Importance of Frost Penetration Information ..................................................................... 1

Seasonal Monitoring Program ............................................................................................ 1

PROJECT OBJECTIVE AND SCOPE.................................................................................2

REPORT OVERVIEW ...........................................................................................................3

CHAPTER 2. REVIEW OF LTPP FROST PROCEDURES AND ASSESSMENT OF 

PREVIOUS ESTIMATES.............................................................................................................5

LTPP SMP DIRECTIVES AND EXPERIMENT DESIGN................................................5

Electrical Resistivity Measurements................................................................................... 6

Moisture Measurements...................................................................................................... 7

Temperature Measurements................................................................................................ 8

INITIAL LTPP FROST INTERPRETATION METHODOLOGY...................................8

PREVIOUS LTPP FROST ESTIMATES...........................................................................10

Limited ER Data Availability ...............................................................................................11

Fluctuations in ER Values ................................................................................................ 14

Noncontinuous Frost Regions........................................................................................... 16

LTPP DATA REVIEW CONCLUSIONS...........................................................................17

CHAPTER 3. REVIEW OF ADVANCES IN THE STATE OF KNOWLEDGE IN FROST 

PENETRATION ANALYSIS.....................................................................................................19

IN-SITU MOISTURE CONTENT FROM TDR MEASUREMENTS.............................19

Example Using Moisture Data in Frost Analysis ............................................................. 20

ENHANCED INTEGRATED CLIMATIC MODEL.........................................................21

Example Using EICM Model to Predict Missing Temperature........................................ 22

CHAPTER 4. ENHANCED METHODOLOGY FOR LTPP FROST 

DETERMINATION ....................................................................................................................25

OVERVIEW...........................................................................................................................25

DETERMINATION OF FREEZING ISOTHERM...........................................................25

DETERMINATION OF FREEZE STATE.........................................................................26

Freeze-Thaw Processes..................................................................................................... 26

Freeze State Assignment................................................................................................... 26

THERMODYNAMIC MODELING OF SUBSURFACE TEMPERATURES ...............27

Cautionary Note................................................................................................................ 28

LTPP FROST PENETRATION ANALYSIS PROCEDURE ...........................................28

Additional Analysis Rules ................................................................................................ 30

Data Normalization and Interpolation .............................................................................. 31

QUALITY CONTROL/QUALITY ASSURANCE PROCESS.........................................32

Spatial and Temporal Checks ........................................................................................... 32

Trend Reasonableness Check ........................................................................................... 33

Analysis Results Database Checks ................................................................................... 33
iv 

CHAPTER 5. IMPLEMENTATION OF THE ENHANCED FROST ANALYSIS 

METHODOLOGY ......................................................................................................................35

UPDATES TO FROST PROGRAM....................................................................................35

E-FROST Overview.......................................................................................................... 35

Enhancements to LTPP Frost Interactive Procedure ........................................................ 35

Changes from SMP II Experiment.................................................................................... 36

ENHANCED FROST ALGORITHM..................................................................................36

E-FROST Symbol Color Codes and Shapes for the Decision Tree.................................. 37

FROST PENETRATION ANALYSIS EXAMPLE............................................................38

Step 1. Prepare E-FROST Inputs Database ...................................................................... 39

Step 2. Generate an “AutoFrost” Freeze State Profile...................................................... 39

Step 3. Review ER, Moisture, and Temperature Trends .................................................. 40

Step 4. Generate and Review Frost Penetration Profile.................................................... 41

Step 5. Calculate Frost Depth Using Freeze State Information........................................ 42

Limitations of Transitional Freeze State Estimates .......................................................... 43

CHAPTER 6. LTPP DATA USED FOR FROST DETERMINATION.................................45

DATA REQUIRED FOR E-FROST ANALYSIS...............................................................45

DATA REQUIRED FOR EICM ANALYSIS .....................................................................46

ANALYSIS DATABASE SUMMARY ................................................................................47

CHAPTER 7. FROST PENETRATION ANALYSIS RESULTS...........................................49

DATA ANALYSIS SUMMARY...........................................................................................49

FROST OBSERVATIONS ...................................................................................................50

Severity of Frost Penetration ............................................................................................ 50

Frost Penetration Profile Characteristics .......................................................................... 52

Comparison with Historical Non-LTPP Frost Data.......................................................... 58

Comparison with Previous LTPP Frost Estimates............................................................ 60

LTPP FROST DATA TABLE DESCRIPTIONS ...............................................................60

CHAPTER 8. SUMMARY AND RECOMMENDATIONS ....................................................63

SUMMARY ............................................................................................................................63

RECOMMENDATIONS FOR FUTURE RESEARCH.....................................................63

Future E-FROST Development to Support M-E PDG Implementation........................... 63

Future LTPP Data Analysis Study of Pavement Responses under FWD Loading during 

Freeze-Thaw Conditions................................................................................................... 64

Future Development of In-Situ Frost Measurement Devices ........................................... 64

APPENDIX A. E-FROST USER’S GUIDE ..............................................................................65

APPENDIX B. EICM MODELING INPUTS...........................................................................77

REFERENCES.............................................................................................................................83
v 

LIST OF FIGURES 

Figure 1. Illustration. LTPP SMP instrumentation layout .............................................................. 6

Figure 2. Chart. Previous FROST decision tree ............................................................................. 9

Figure 3. Chart. Frost predictions for section 0114 in Montana................................................... 12

Figure 4. Chart. Comparison of ER, temperature, and moisture trends for section 0114 in 

Montana ........................................................................................................................................ 13

Figure 5. Chart. Frost predictions for section 1028 in Minnesota ................................................ 14

Figure 6. Chart. Frost predictions for section 0804 in South Dakota for 1994–1995 

winter season................................................................................................................................. 15

Figure 7. Chart. Comparison of ER, temperature, and moisture trends for section 0804 in 

South Dakota at 1.01 m (3.31 ft) depth......................................................................................... 16

Figure 8. Chart. Frost predictions for section 1026 in Maine....................................................... 20

Figure 9. Chart. Comparison of ER, temperature and moisture trends for section 1026 in 

Maine ............................................................................................................................................ 21

Figure 10. Chart. Measured and EICM predicted temperatures for section 6251 in 

Minnesota at 0.8 m (2.6 ft) depth before auto-correction............................................................. 23

Figure 11. Chart. Measured and EICM predicted temperatures for section 6251 in 

Minnesota at 0.8 m (2.6 ft) depth after auto-correction................................................................ 24

Figure 12. Chart. Frost depth and layers interpretation using E-FROST ..................................... 29

Figure 13. Equation. Normalized measurement ........................................................................... 31

Figure 14. Equation. Interpolated measurement........................................................................... 31

Figure 15. Chart. Enhanced FROST algorithm ............................................................................ 37

Figure 16. Chart. Example of temperature-based frost penetration profile for section 0804 

in South Dakota............................................................................................................................. 40

Figure 17. Chart. Example of ER, temperature, and moisture trends for section 0804 in 

South Dakota at 0.55 m (1.8 ft) depth........................................................................................... 41

Figure 18. Chart. Example of final frost penetration profile for SMP site 46-0804 for 

the winter of 1999 ......................................................................................................................... 42

Figure 19. Chart. Temperature and ER trends at 1.02 m (3.35 ft) for site 50-1002 

during winter season 2000–2001 .................................................................................................. 44

Figure 20. Picture. Locations of LTPP SMP sites analyzed in this study .................................... 49

Figure 21. Chart. Frost penetration profile showing multiple freeze-thaw cycles........................ 52

Figure 22. Chart. Frost penetration profile showing shallow freeze cycles in the fall 

followed by solid deep freeze with spring thaw ........................................................................... 53

Figure 23. Chart. Frost penetration profile showing solid freeze with partial spring thaw and 

refreeze.......................................................................................................................................... 54

Figure 24. Graph. Comparison of frost penetration depths .......................................................... 58

Figure 25. Screen capture. Opening screen in E-FROST ............................................................. 66

Figure 26. Screen capture. Tool buttons ....................................................................................... 66

Figure 27. Screen capture. Open database.................................................................................... 67

Figure 28. Screen capture. Locate the database containing SMP data ......................................... 68

Figure 29. Screen capture. Select data table for analysis.............................................................. 68

Figure 30. Screen capture. Frost linked to database with some tool buttons activated ................ 69

Figure 31. Screen capture. SMP Section window......................................................................... 70

Figure 32. Screen capture. Blank Frost Penetration Analysis screen ........................................... 71
vi 

Figure 33. Chart. Automatically generated frost penetration profile at SMP site 46-0804 

for the winter of 1999 ................................................................................................................... 72

Figure 34. Chart. Time series plot for SMP site 46-0804 for the winter of 1999 at 

analysis depth = 0.55 m (1.8 ft) .................................................................................................... 74

Figure 35. Chart. Final frost penetration profile for SMP site 46-0804 for the winter of 1999 ... 75

Figure 36. Screen capture. Create Frost Penetration Table option ............................................... 76
vii 

LIST OF TABLES 

Table 1. LTPP section with previous frost depths estimates ........................................................ 10

Table 2. Freeze state evaluations using different data sources ..................................................... 21

Table 3. Freeze-state characteristics ............................................................................................. 27

Table 4. Freeze state and frost depth chart symbol shape and color coding................................. 38

Table 5. Summary of data assembled for frost penetration analysis ............................................ 48

Table 6. Summary of frost determinations ................................................................................... 51

Table 7. Typical frost penetration profile characteristics for LTPP SMP sites ............................ 55

Table 8. Comparison of average frost depth for LTPP SMP sites................................................ 59

Table 9. Summary of information included in the revised table SMP_FREEZE_STATE .......... 61

Table 10. Summary of information included in the revised table 

SMP_FROST_PENETRATION .................................................................................................. 61

Table 11. Freeze state and frost depth chart color coding ............................................................ 73

Table 12. EICM inputs.................................................................................................................. 77

1

CHAPTER 1. INTRODUCTION 

BACKGROUND 

Importance of Frost Penetration Information 

Knowledge of frost penetration beneath the pavement structure is critical for many pavement 

design, analysis, and management applications. Problems caused by frost include the seasonal 

change in the bearing capacity of soils brought by freezing and thawing. As subsurface 

temperatures decrease, the moisture in the unbound pavement layers freezes into ice that binds 

the aggregate particles together. Frost penetration leads to an increase in the strength and 

stiffness of the unbound pavement layers and subgrade soil. The process of ice formation also 

draws moisture into the freezing zone. When the frost thaws in the spring, the moisture increase 

in the soil can lead to weakened support for the pavement structure. 

Another mechanical process associated with frost is the volumetric change in frost-susceptible 

soils, referred to as frost heave, which can lead to vertical differential movements of the road and 

subsequent poor performance. This heaving of roadbeds out of vertical alignment and breaking 

of the pavement surface often complicates highway maintenance. 

Over the years, the National Oceanic and Atmospheric Administration (NOAA)(1) and 

Environment Canada(2) have developed and published the climatic maps containing historical 

frost penetration values, as well as the number of freeze-thaw cycles in the form of contour 

maps. These maps provide frost depth estimates for natural (uncovered) land in the United States 

and Canada. The frost penetration conditions under pavements may be different from that of 

exposed land surfaces. In addition, deicing salts may have an effect on frost penetration as they 

eventually dissipate into the soil. 

Seasonal Monitoring Program 

To provide the transportation community with the data needed to understand the magnitude and 

impact of diurnal, seasonal, and annual variations in pavement properties and responses, 

including the effects of frost penetration beneath pavement section, the Federal Highway 

Administration (FHWA) Long Term Pavement Performance (LTPP) program selected a number 

of test sites throughout the United States and Canada for the Seasonal Monitoring Program 

(SMP). 

The original SMP (hereto referred as SMP I) included a total of 65 test sections and lasted from 

1992 to 1999. As a part of the SMP I experiment, 37 pavement test sections were instrumented 

with electrical resistivity (ER) probes to monitor the frost penetration in unbound pavement 

layers. In addition, these sections were instrumented with time domain reflectometry (TDR) and 

temperature probes. 

At the conclusion of SMP I, the LTPP team realized the need for additional monitoring of these 

sites and initiated the SMP II program. The objective of the SMP II monitoring was to continue 

providing the data needed to attain a fundamental understanding of the magnitude and impact of 

variations in pavement response and properties due to the separate and combined effects of 
2

temperature, moisture, and frost penetration. The SMP II included a total of 22 test sections and 

lasted from 2000 to October 2004. LTPP continued monitoring the ER trend as a part of the SMP 

II experiment at 12 test sites. 

To aid in the interpretation of the ER data, an interactive computer program called FROST was 

developed in the late 1990s, and the available data were analyzed (see FHWA-RD-99-088 for 

more information on FROST).

(3) FROST used ER data (voltage, contact resistance, and 

resistivity) in conjunction with soil temperature data to determine the depth of frost penetration 

in unbound layers for the SMP sections. 

The results of frost penetration analysis are stored in two computed parameter tables in the LTPP 

database as follows: 

• SMP_FREEZE_STATE. 

• SMP_FROST_PENETRATION. 

The SMP_FREEZE_STATE table characterizes the freeze state as frozen or nonfrozen at each 

ER measurement depth. This information is useful for understanding or reevaluating the process 

by which the results presented in table SMP_FROST_PENETRATION were derived. The data 

in table SMP_FROST_PENETRATION translate the freeze state at each measurement depth 

into starting and ending depths of frozen layer(s). The SMP_FROST_PENETRATION table is 

the end product of the data analysis to determine the boundaries of frozen layers within the 

pavement cross section. These computed parameters tables contain information necessary 

analyzing the changes in pavement structural responses due to the seasonal changes in pavement 

layer properties. 

These tables were updated twice with the new batches of the processed data: the first upload was 

based on the July 1999 version of the LTPP data for SMP I sections, and the second upload 

included SMP II sections based on the July 2001 version of the LTPP data. With the completion 

of monitoring measurements on the SMP sections in October 2004, there was a need to complete 

the interpretation of measurements not previously interpreted and to add the results to the 

database. In addition, through previous interpretation of SMP ER and soil temperature data, it 

became evident that the accuracy of the LTPP frost predictions could be improved by adding 

thermodynamic analysis capability to estimate missing temperature readings and by crossreferencing ER trends with moisture and temperature changes. 

PROJECT OBJECTIVE AND SCOPE 

The objective of the current project was to update and complete the interpretations of frost 

penetration using measurements collected at the instrumented SMP sites. To achieve this 

objective, the project team was charged to review and enhance LTPP procedures for frost 

penetration determination. The enhanced procedures were subsequently used to critically review 

and flag questionable previous frost estimates and to complete the interpretation of frost depth in 

the unbound layers for new data and to update previous estimates. 

The project was divided into two phases. The objectives of Phase I were to assess the existing 

LTPP frost penetration analysis methodology and frost penetration results, propose 
3

enhancements to the LTPP frost penetration analysis process, and develop a detailed research 

plan that would include the proposed enhancements for the frost penetration determination 

procedures. The objectives of Phase II were to implement these procedures in a software 

research tool, conduct frost penetration analysis, and develop new LTPP frost predictions using 

SMP data. 

REPORT OVERVIEW 

This final report documents the investigations performed during the study, describes the 

enhancements to the frost penetration analysis methodology developed, and summarizes the 

results of frost penetration estimates for LTPP SMP sections. Activities performed throughout 

the remainder of this report are discussed as follows: 

• Chapter 2. Review of LTPP Frost Procedures and Assessment of Previous Estimates. 

• Chapter 3. Review of Advances in the State of Knowledge in Frost Penetration Analysis. 

• Chapter 4. Enhanced Methodology for LTPP Frost Determination. 

• Chapter 5. Implementation of the Enhanced Frost Analysis Methodology. 

• Chapter 6. LTPP Data Used for Frost Determination. 

• Chapter 7. Frost Penetration Analysis Results. 

• Chapter 8. Summary and Recommendations. 

In addition, the following two appendices are provided with the report: 

• Appendix A. E-FROST User’s Guide. 

• Appendix B. List of Inputs to the EICM Program. 

5

CHAPTER 2. REVIEW OF LTPP FROST PROCEDURES AND ASSESSMENT OF 

PREVIOUS ESTIMATES 

LTPP SMP DIRECTIVES AND EXPERIMENT DESIGN 

To obtain a better understanding of the early LTPP frost depth determination procedures, the 

LTPP reports, SMP directives, software, and other literature relating to detection of frost in 

unbound pavement layers were obtained and reviewed in detail. In addition, a coordination 

meeting took place between the Data Analysis Technical Support (DATS) team, FHWA/LTPP 

team and regional service centers, and Technical Support Services Contract (TSSC) 

representatives. The review included SMP installation/de-installation reports, the procedures and 

equipment used to collect data needed for the interpretation of LTPP ER and TDR data, and the 

quality control (QC) procedures used to evaluate the SMP data prior to upload into the database, 

all of which include the following documents: (See references 3, 4, 5, 6, 7, 8, and 9.) 

• Determination of Frost Penetration in LTPP Sections, Report No. FHWA-RD-99-088. 

• FHWA, LTPP Seasonal Monitoring Program: Instrumentation Installation and Data 

Collection Guidelines, Report No. FHWA-RD-94-110. 

• FHWA, LTPP Guidelines for SMP Phase II Equipment and Instrumentation Installation, 

SM-35. 

• FHWA, LTPP SMP Phase II Monitoring, SM-31. 

• LTPP Seasonal Monitoring Program SMP II Equipment Installation/De-Installation 

Reports prepared by LTPP Regional Contractor Offices for individual sites. 

• Computed Parameters: Freeze/Thaw Monograph for LTPP. Publication No. 

FHWA-RD-98–177. 

• FHWA, LTPP Information Management System, IMS Quality Control Checks. 

In the SMP I experiment, 37 test sites were instrumented to measure ER, moisture content, and 

temperature in the unbound pavement layers (base and subbase) and the upper layers of 

subgrade. The LTPP SMP instrumentation layout is shown in figure 1. The techniques, 

equipment, and schemes of data collection under the SMP are described in detail in the LTPP 

Seasonal Monitoring Program: Instrumentation Installation and Data Collection Guidelines,

Report No. FHWA-RD-94-110.(4) This section of the report provides a summary of how 

temperature, moisture, and ER data are collected and their relevance to frost penetration in 

pavement layers. 
6

Figure 1. Illustration. LTPP SMP instrumentation layout.(4)

Electrical Resistivity Measurements 

The electrical resistivity probes used in the initial SMP program were developed by the U.S. 

Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL). The 

probes were installed to monitor the freeze state in the unbound pavement layers and the top 

subgrade layers. Each resistivity probe consists of 36 metal wire electrodes spaced 51 mm 

(2 inches) apart on a solid polyvinyl chloride (PVC) rod 1.9 m (73 inches) long. The top of the 

resistivity probe was installed approximately 50 mm (2 inches) below the bottom of the lowest 

bound pavement layer. The weakness with this multiplexer was that there was no reference to 

check the voltage outputs recorded. 

In the SMP II experiment, the CRREL multiplexer was replaced with an ERB20 multiplexer, 

manufactured by ABF Manufacturing, Inc. This multiplexer provides an input voltage at the start 

of each cycle and reference voltage through a 100k resistor at the completion of the cycle. 

The electrical resistivity technique is based on the fact that the bulk resistivity of a soil increases 

dramatically when the soil freezes. Electricity is conducted exclusively by the pore water 

contained in the soils because the soil minerals and air voids are nonconductive. The electrical 
7

resistivity of frozen water is much higher than that of liquid water, and this difference is used to 

differentiate between frozen and unfrozen soil. However, if water content is low, or if the water 

phase is discontinuous, the difference in electrical resistivity between the frozen and unfrozen 

soil is difficult to detect reliably. 

For SMP I, the automated and manual resistivity profiles were collected at the time of the Falling 

Weight Deflectometer (FWD) data collection to evaluate changes in layer stiffness based on the 

soil properties. As a result, only limited ER measurements were taken at the time of FWD data 

collection for the majority of LTPP sites: once a month or less every other year for SMP I sites 

and six months a year for SMP II noncontinuous sites. During the SMP II experiment, more 

extensive ER data were collected at selected continuous monitoring sites. 

The challenge working with ER data is that the majority of data were not collected continuously, 

except at a few SMP II sites that were set up for continuous monitoring. Sparse measurements 

make it difficult to capture the beginning and ending of freezing and thawing periods. Changes in 

ER equipment and measuring techniques also created challenges when comparing the values 

collected during the SMP I and SMP II experiments. 

For the SMP I experiment, ER data were stored in the following tables: 

• SMP_ERESIST_AUTO. 

• SMP_ERESIST_MAN_CONTACT. 

• SMP_ERESIST_MAN_4POINT. 

Since the launch of the SMP II program, the collection, processing, and storage of ER data for 

SMP II sites has been modified. The SMP II ER data are collected using different continuous 

automatic equipment and are stored in the following tables: 

• SMP_ERESIST_ABF_REF_VA— Applied voltage and resistance voltage values 

measured on the internal reference resistor used in ABF multiplexer. 

• SMP_ERESIST_AUTO_ABF—Resistance voltage and computed resistance for ABF 

type resistivity probe. 

The sites that were moved from the SMP I experiment to the SMP II experiment have ER data 

collected prior to 2000 in the old ER data tables and ER data collected after 1999 in the new data 

tables. In addition, manually collected ER data are stored in the tables used in SMP I. 

Moisture Measurements 

The volumetric moisture content (VMC) is determined using TDR probes placed at 

approximately 10 depths in the unbound base, subbase (if present), and subgrade layers. The 

VMC represents a ratio of the volume of water to the total volume (soil solids + water + voids). 

The probe closest to the pavement surface was installed at the mid-height of the highest unbound 

layer unless that layer was more than 300 mm (12 inches) thick, in which case the probe was 

installed 150 mm (6 inches) below the top of the layer regardless of thickness. The next seven 

probes were installed at 150-mm (6-inch) depth intervals, and the two deepest probes were 
8

installed at 300-mm (12-inch) depth intervals, thereby placing the deepest probe approximately 

1.8 m (6 ft) below the top of the highest unbound pavement layer. 

The data collected with the TDR instrumentation are used to determine the dielectric constants 

for the soil. The volumetric moisture content is then computed using regression equations 

relating the dielectric constant to moisture content, which are discussed in Report No. FHWARD-99-115.(10) The results from the recently completed LTPP data analysis study LTPP 

Computed Parameter: Moisture Content, Report No. FHWA-HRT-08-030,(22) contain computed 

volumetric moisture content values estimated based on the dielectric constant and properties of 

soil using calibrated micromechanics equation. These results are included in the LTPP table 

MP_TDR_MOISTURE. 

Since the dielectric constant for ice is significantly different than that for water, the water 

contents measured by the TDR probes during the frozen periods may reflect the presence of ice. 

Like the ER data, the majority of TDR data were not collected continuously, except at a few 

SMP II sites that were set up for continuous monitoring. Sparse measurements make it difficult 

to capture the beginning and ending of freezing and thawing periods. 

Temperature Measurements 

The temperature profile is measured by thermistors installed at 18 depths through pavement 

structure. The thermistors are permanently installed in a 0.25-m (10-inch) diameter hole located 

near the section end. The first three thermistors are embedded in the surface bound layer, and the 

rest are embedded in the base, subbase, and subgrade layers. The five thermistors closest to the 

pavement surface are spaced 75 mm (3 inches) apart. The rest are spaced 150 mm (6 inches) 

apart. Data from the first five thermistors are recorded hourly. Daily temperature statistics, 

including maximum, minimum, average temperature, and times of maximum and minimum 

temperature, are recorded for all thermistors in table SMP_MRCTEMP_AUTO_DAY_STATS. 

Subsurface temperature measurements are taken every day, providing a complete picture of 

temperature changes in subsurface layers throughout the year. Seasonal temperature trends can 

be used to correlate temperature, moisture, and ER data. From these correlations, it is possible to 

establish freezing and thawing temperatures, freezing isotherm, and the freeze state of the soil for 

a given SMP section. 

INITIAL LTPP FROST INTERPRETATION METHODOLOGY 

Previous LTPP frost penetration methodology is documented in FHWA, Determination of Frost 

Penetration in LTPP Sections, Report No. FHWA-RD-99-088.(3) This report was reviewed in 

detail to obtain a thorough understanding of the procedures used to generate the existing LTPP 

computed parameter tables with regard to frost depth in unbound pavement layers. The previous 

method used to determine SMP_FREEZE_STATE and SMP_FROST_PENETRATION is 

shown in the flowchart in figure 2. 
9

Figure 2. Chart. Previous FROST decision tree. 

Upon review of the SMP I and II experimental designs and LTPP frost analysis methodology, the 

following shortcomings and potential future improvements were identified: 

• Evaluations of frost penetration were made only for the dates when ER measurements 

were taken. With the exception of a few SMP II sites, these early measurements were 

taken once a month or less frequently. Thus, ER data were insufficient to establish the 

frost penetration profile for the whole freeze season. 

• ER time-series trends were difficult to interpret due to frequent unexplained fluctuations 

in ER values and sometimes counterintuitive trends (i.e., low ER in winter and high ER 

in summer). At the same time, temperature trends appeared to be very reliable and 

correlated well with changes in air temperature and with the Enhanced Integrated 

Climatic Model (EICM)-based subsurface temperature changes with time. 

• Subsurface temperatures were considered in the frost analysis only when ER data were 

available. However, these temperatures were available for nearly every day of the year. 

More extensive use of the temperature data could have improved the accuracy of frost 

estimates. 

• Moisture content data were not included in the FROST interactive procedure. Use of 

moisture data could improve the determination of the freeze state, especially at the 

beginning of the freezing and thawing periods. 

T > 0 oC 

T <= 0 oC 

Missing 

 No Freeze 

Freeze 

 No Freeze 

Freeze 

Cold winter 

month? 

At least one ER 

measure above 

threshold?

No No Freeze 

No

Yes

Yes

Normalized 

Electrical 

Resistivity 

Average 

Temperature 

Month of 

the Year 
10

PREVIOUS LTPP FROST ESTIMATES 

Previously estimated frost information stored in the SMP_FREEZE_STATE and 

SMP_FROST_PENETRATION tables was reviewed during the study. The estimates were 

available for 37 SMP I sections and 12 SMP II sections and are listed in table 1 for the period 

from 1994 to 2001. 

Table 1. LTPP section with previous frost depths estimates. 

STATE_CODE SHRP_ID SMP I SMP II State 

4 1024 Y Arizona 

8 1053 Y Colorado 

9 1803 Y Connecticut 

16 1010 Y Idaho 

18 3002 Y Indiana 

20 4054 Y Kansas 

23 1026 Y Maine 

24 1634 Y Maryland 

25 1002 Y Massachusetts 

27 1018 Y Minnesota 

27 1028 Y Minnesota 

27 4040 Y Minnesota 

27 6251 Y Y Minnesota 

30 0114 Y Y Montana 

30 8129 Y Montana 

31 0114 Y Y Nebraska 

31 3018 Y Y Nebraska 

32 0101 Y Y Nevada 

32 0204 Y Nevada 

33 1001 Y New Hampshire 

36 0801 Y Y New York 

36 4018 Y New York 

39 0204 Y Ohio 

39 0901 Y Y Ohio 

42 1606 Y Y Pennsylvania 

46 0804 Y Y South Dakota 

46 9187 Y South Dakota 

48 1077 Y Texas 

49 1001 Y Utah 

49 3011 Y Utah 

50 1002 Y Y Vermont 

56 1007 Y Wyoming 

83 1801 Y Y Manitoba 

83 3802 Y Manitoba 

87 1622 Y Ontario 

89 3015 Y Y Quebec 

90 6405 Y Saskatchewan 
11

The primary method of reviewing the LTPP frost estimates was by examining the ER, moisture, 

and temperature data collected as part of the SMP study and then comparing the trends observed 

in these data with freeze estimates obtained from the LTPP database. During the review, the 

following potential data problems and drawbacks of previous methodology were identified: 

• Limited ER data availability. 

• Unexplained fluctuations in ER values. 

• Questionable noncontinuous frost regions. 

• Noninclusion of moisture data. 

• Underutilization of temperature and moisture data. 

The results of review are discussed in detail in the following subsections. 

Limited ER Data Availability 

The sparse ER data put limitations on the accuracy and validity of the frost estimates. The 

example in figure 3 demonstrates the limitation of the frost penetration estimates attributed to 

limited ER data availability. The example shows a comparison between frost predictions based 

on ER and temperature data for SMP II section 0114 in Montana for the 2000–2001 winter 

season. The frost penetration profile based on ER probe measurements is laid over the freeze 

state predictions based on subsurface temperature profile, as shown in the graph’s legend. Blue 

“Freeze” cells indicate temperatures below -1 o

C. Grey “No Freeze” cells indicate temperatures 

above 0 oC. Yellow cells indicate temperatures between 0 o and -1 oC. Burgundy cells indicate a 

freeze state based on ER data. 

As can be seen from the plot, ER data were collected almost daily during November 2000. Frost 

predictions show agreement between temperature-based and ER-based predictions for this 

period. However, no ER data were collected again until January 8, 2001. As a result, the LTPP 

database contains no frost penetration predictions for December 2000, while temperature data 

strongly suggest a freeze state up to 1 m (3.28 ft) in depth, as indicated by the blue region. After 

data collection on January 8, 2001, no ER measurements are reported until mid March 2001, 

completely missing the spring thaw period. 

Figure 4 shows a comparison of ER, temperature, and moisture trends for the same site, as 

evaluated 0.52 m (1.71 ft) below the pavement surface. ER and moisture data are reported on the 

left axis. ER data are normalized between 0 and 1 to provide better means for analysis of 

seasonal fluctuations. Temperature data are reported in degrees (o

) Celsius on the right axis. The 

following can be observed from this figure: 

• All three types of measurements show an “as-expected” trend—as temperature falls 

below 0 o

C, ER values increase and moisture values decrease. 

• Spring thaw is clearly defined by a sharp increase in moisture values. 

• Temperature and moisture data are more complete compared to ER data, providing a 

better indication of freezing conditions in this case. 
12

Figure 3. Chart. Frost predictions for section 0114 in Montana. 
13

Figure 4. Chart. Comparison of ER, temperature, and moisture trends for section 0114 in 

Montana. 

Figure 5 shows frost predictions for SMP I site 1028 in Minnesota. While most ER-based frost 

predictions (marked as “Previous Freeze” on the plot) follow the temperature-based frost 

predictions, it is evident that ER-based frost estimates are more questionable when temperatures 

are between 0 o

C and -1 oC (see yellow section of the plot). The state of soil may be in transition 

between frozen and unfrozen for these temperatures. 
14

Figure 5. Chart. Frost predictions for section 1028 in Minnesota. 

Fluctuations in ER Values 

Review of the ER data pointed to the instability in ER trends—ER values may go down during 

freezing temperatures and up during hot summer months, although the opposite trend is 

expected. Because the previous methodology relies heavily on the ER data, such ER trends may 

result in inaccurate frost estimates. 

Figure 6 illustrates the failure to predict frost penetration at lower depths where soil temperature 

remained below -1 o

C for extended periods of time. The reasons for inaccurate frost predictions 

include subjectivity when establishing an ER threshold value and unexplained dips in ER values 

during the cold season. Figure 7 shows changes in ER, moisture, and temperature values with 

time at a depth of 1.01 m (3.31 ft). Examination of the temperature data in figure 7 indicates that 

freezing at that depth occurred during mid to late December. The freezing process was 

accompanied by a constant temperature around 0 o

C for several days while heat loss took place. 

After that period, the soil temperature fell below 0 o

C, indicating a freeze state. The soil 

remained frozen until mid March, when temperatures rose above 0 oC and moisture content 

increased. Moisture content values decreased sharply between December and April, also 

indicating a “Freeze” condition. 
15

Figure 6. Chart. Frost predictions for section 0804 in South Dakota for 1994–1995 winter 

season. 

The example in figure 7 shows high fluctuations in resistivity values taken in February and then 

in early March 2005. The ER values differ by over 80 percent, although temperature and 

moisture data indicate that the soil remained frozen for both dates. 

Further data review indicates that the accuracy of ER predictions had improved once the same 

sections became part of the SMP II continuous monitoring experiment. However, ER-based 

determination of frost penetration for temperatures just below the freezing point remained 

challenging. 

Freezing state missed 

by ER measurements 
16

Figure 7. Chart. Comparison of ER, temperature, and moisture trends for section 0804 in 

South Dakota at 1.01 m (3.31 ft) depth. 

Noncontinuous Frost Regions 

There were eight sites with noncontinuous frost regions found in the LTPP database during the 

data review task. Each case with noncontinuous frost regions was reviewed. The following 

reasons were found that might have affected judgment when assigning noncontinuous frost 

regions: 

• Missing subsurface temperature—decisions were based solely on ER measurements. 

• Subsurface temperatures close to 0 o

C—soil may be in a transition state. 

• Drop in ER values relative to surrounding dates—sometimes ER values drop even when 

surrounding temperatures remain below freezing. 

In all cases, assignments of freeze or no freeze conditions were highly subjective. Other 

noncontinuous frost layers could form as a result of thawing and refreezing of the top layers 

while a deep frozen layer remained in place until the end of the freezing period. Identifying areas 

of noncontinuous frost regions is difficult using either ER or temperature data. ER measurements 

can be ambiguous at the freezing isotherm. Temperature data are not adequate to identify 

noncontinuous frost regions because nonfrozen water between two frozen zones would be very 

near to 0 °C. 

Expected high 

winter ER values

Unexpected low 

winter ER values

Expected low 

spring ER values
17

To remove some subjectivity in these assignments, moisture content analysis could be added to 

the frost analysis algorithm. 

LTPP DATA REVIEW CONCLUSIONS 

Two conclusions have been drawn from reviewing the existing LTPP frost data. The first 

conclusion is that the previous values for SMP_FREEZE_STATE and 

SMP_FROST_PENETRATION are not describing the actual freeze conditions in the subsurface 

layers accurately. This conclusion is primarily derived from examining the previously derived 

LTPP frost data. The reasons are as follows: 

• ER measurements for SMP I and SMP II noncontinuous sites are sparse and do not 

provide enough data to determine the length of the freeze period or freezing-thawing 

changes that take place during the winter season. 

• In some cases, ER data are erratic and counterintuitive (high values in summer and low 

in winter or high/low values in one of three collected ER values). 

• The existing interpretation methodology does not utilize changes in moisture content. 

• Frost predictions were made only for the dates with ER data; dates with subsurface 

temperatures below freezing were not included in the analysis if ER measurements were 

not obtained on the same dates. 

• Many difficulties arise in determining freeze conditions around the freezing isotherm 

when soil transitions between freeze and no-freeze states. 

The second conclusion is that a more accurate determination of the freeze state of the soil is 

possible by using subsurface temperature and moisture data in addition to ER measurements 

more extensively and by incorporating thermodynamic modeling to fill the gaps in measured 

temperature data. Thermodynamic modeling also could be useful for analyzing heat and moisture 

transfer processes that take place in subsurface layers, as well as assisting the analyst with frost 

predictions. 

19

CHAPTER 3. REVIEW OF ADVANCES IN THE STATE OF KNOWLEDGE IN FROST 

PENETRATION ANALYSIS 

Relevant literature was reviewed during Phase I of the project and is summarized in this chapter. 

The review included several published documents. (See references 10, 11, 12, 13, 14, 15, 16, 17, 

18, 19, 20, and 21.) 

To improve the accuracy of frost predictions for the instrumented LTPP sections, alternative 

approaches to detection of frost in unbound pavement layers were investigated, including 

thermodynamic modeling of time-based changes in subsurface temperatures and changes in 

TDR traces. 

The key outcomes of this background review included the following recommendations to 

improve the accuracy of frost predictions for the instrumented LTPP sections: 

• Enhance current frost penetration methodology and accompanying FROST interactive 

program by integrating in-situ moisture content data from TDR measurements in frost 

penetration prediction and cross-reference changes in temperature, ER, and moisture to 

determine freeze state. 

• Place more emphasis on analysis subsurface temperatures as these data were found to be 

most complete and reliable when comparing to ER and moisture data from SMP sections. 

• Use thermodynamic modeling integrated into EICM to fill the gaps in measured 

subsurface temperatures. 

Details are discussed in the following sections. 

IN-SITU MOISTURE CONTENT FROM TDR MEASUREMENTS 

Another viable method to identify frost regions is to use TDR data to identify the presence of ice 

by a decrease in moisture content when the soil is frozen. This method is detailed by Benson and 

Bosscher.(13) 

Moisture content in the unbound pavement layers and subgrade soil affects frost severity due to 

the physical phenomenon of moisture migration in response to freezing. Even when the 

temperatures fall below the freezing point of the contained water, frozen soil may contain both 

frozen and unfrozen water in varying proportions depending on temperature depression, specific 

surface area, and salt content. The presence of unfrozen water provides the opportunity for 

moisture to migrate vertically, resulting in formation and thickening of ice lenses. Ice lenses 

represent horizontal layers of solid ice that form below the ground surface, separating the soil 

above from the soil below to form noncontinuous frost regions. Ice lenses may damage the 

pavement structure due to the large vertical displacements known as frost heaves.(18) As the pore 

water freezes, the volumetric moisture content drops to a very low level wherever a frost 

condition exists and therefore serves as a cross-reference for frost depth analysis. (See references 

15, 16, 17, 18, and 19.) 
20

Example Using Moisture Data in Frost Analysis 

The following example shows how moisture content (MC) data can improve the accuracy of 

frost predictions. As shown in figure 8, the SMP section 1026 in Maine experienced several 

periods of freeze-thaw during the 1994–1995 winter season. Light blue indicates that most 

subsurface temperature readings were taken between 0 oC and -1 oC, making freeze state 

prediction using ER values very challenging. At this temperature range, pore water may or may 

not have enough energy loss to freeze. Plus, soil salinity may affect the actual freezing isotherm 

value and depress it below 0 oC. 

ER measurements were taken on seven dates during that winter season, as shown in figure 9. On 

the same dates, TDR measurements were taken and moisture content was computed. Of the 

seven ER measurement dates, the freeze state of the soil was detected on only two dates (January 

and February measurements) based on the ER data. Based on the analysis of moisture content 

fluctuations, an additional measurement on March 6, 1995, indicated that the soil was in a frozen 

state. This date has corresponding low moisture content and subzero temperature values. A 

summary of freeze state determination using different data sources is shown in table 2. 

Figure 8. Chart. Frost predictions for section 1026 in Maine. 
21

Figure 9. Chart. Comparison of ER, temperature and moisture trends for section 1026 in 

Maine. 

Table 2. Freeze state evaluations using different data sources. 

Date: 11/14/94 12/12/94 1/17/95 2/14/95 3/6/95 3/20/95 4/3/95 5/1/95 

ER: NF NF F F NF NF NF NF 

MC: NF NF F N/A F F/TR NF NF 

T: NF NF TR F F TR NF NF 

ENHANCED INTEGRATED CLIMATIC MODEL 

The Integrated Climatic Model (ICM) was developed in the late 1980s to simulate temporal 

variations in the temperature, moisture, and freeze-thaw conditions internal to the pavement and 

their impact on key pavement material properties.(14) In FHWA-HRT-04-079,(17) this program 

was recognized as the most comprehensive model addressing the effects of climate on 

pavements. As its name suggests, the EICM is an enhanced version of the ICM. It was used as 

the basis for considering seasonal variations in the Mechanistic-Empirical Pavement Design 

Guide (M-E PDG). 
22

The EICM consists of three models addressing different aspects of climatic effects on the 

pavement: 

• Climatic-Materials-Structures (CMS) model, developed at the University of Illinois.(19)

• Infiltration and Drainage (ID) model, developed at the Texas Transportation Institute.(20)

• Frost Heave and Thaw Settlement Model, developed by the CRREL.(21) 

The EICM provides the capability to simulate temperature, moisture, and freeze-thaw conditions 

internal to the pavement structure as a function of time. The accuracy of the predictions depends 

greatly on a proper selection of boundary conditions, climatic parameters, and material 

properties. 

The EICM engages a coupled heat moisture finite element/difference model. It models heat flow 

by considering climatic and solar inputs at the surface along with the deep ground constant heat 

source. These thermal boundary conditions are used in conjunction with the moisture content of 

the subpavement soils to model heat flow, the freezing state of the soil, and frost penetration 

accurately. The model is coupled in the sense that changes in moisture content affect the thermal 

properties of the unbound layers—an increase in the moisture content increases the heat capacity 

and thermal conductivity of the material. Moisture content in the unbound layer is affected by the 

thermal conditions when freezing occurs. The drying process in the unbound layer causes 

moisture to move to the freezing zone.

This tool could be particularly useful for modeling subsurface temperatures when temperature 

data are not available for some dates or depths. 

Example Using EICM Model to Predict Missing Temperature 

The EICM analysis algorithm provides enhanced options to fill in the gaps in partial or 

incomplete measured subsurface temperature data, including a temperature auto-correction 

option. The analysis starts with inputting pavement and unbound layer data from the LTPP 

database and historical climate measurements into the EICM program. After the initial program 

run, the EICM temperature predictions are compared to the measured temperature data. The 

detailed examination of the measured and predicted data gives further guidance on how the 

inputs can be refined. For example, the unbound materials may model as being wetter or drier 

than the initial inputs suggest. Adjustments to the moisture content present in the profile can be 

achieved by varying inputs into the soil water characteristic curves (SWCC) of each unbound 

layer or by adjusting the depth of the water table. These small refinements can bring the 

predicted and measured values into agreement. 

The auto-correction option is used to further improve predictions. Using this option, the 

temperature profile for each SMP site is modeled and calibrated against available partial field 

measured data on a daily basis, with the initial temperature profile being the previous day’s 

temperature reading. For each time step where temperature is known, the measured value will 

supersede and overwrite the predicted temperature, causing the measured and predicted 

temperatures to track exactly in line with one another. 
23

When measured data are missing for a time period, the EICM model will start in perfect 

agreement with measured data at the beginning of the time period. As the model steps through 

time increments, it no longer has measured data to correct to, and the predicted output represents 

the only understanding of what the temperature is. However, because of the agreement that was 

achieved in the initial modeling and accurate initial profile (corrected by the measured data), the 

EICM is capable of accurately bridging short gaps in the data. When measured data are once 

again available, it is possible to observe the error in the prediction and again correct the predicted 

data with LTPP measured data. Figure 10 illustrates the comparison between the model 

predictions and the LTPP field data before auto-calibration, and figure 11 illustrates the 

comparison after auto-correction calibration. 

-20

-10

0

10

20

30

40

9/1/96

9/16/9610/1/96

10/16/9610/31/9611/15/9611/30/9612/15/9612/30/96

1/14/971/29/972/13/972/28/973/15/973/30/974/14/974/29/975/14/975/29/976/13/976/28/977/13/977/28/978/12/978/27/979/11/979/26/97

Date

Temperature (C)

Predicted by EICM (before auto-correction) Measured

Figure 10. Chart. Measured and EICM predicted temperatures for section 6251 in 

Minnesota at 0.8 m (2.6 ft) depth before auto-correction. 
24

-20

-10

0

10

20

30

40

9/1/96

9/16/9610/1/96

10/16/9610/31/9611/15/9611/30/9612/15/9612/30/96

1/14/971/29/972/13/972/28/973/15/973/30/974/14/974/29/975/14/975/29/976/13/976/28/977/13/977/28/978/12/978/27/979/11/979/26/97

Date

Temperature (C)

ICM Measured

Figure 11. Chart. Measured and EICM predicted temperatures for section 6251 in 

Minnesota at 0.8 m (2.6 ft) depth after auto-correction. 
25

CHAPTER 4. ENHANCED METHODOLOGY FOR LTPP FROST DETERMINATION 

OVERVIEW 

The following outline the basis of the enhanced LTPP frost penetration methodology: 

• Include all three subsurface measurements (temperature, moisture, and electrical 

resistivity) collected by LTPP SMP program in freeze state determination. 

• Place more emphasis on using subsurface temperatures for prediction of frost penetration, 

as these LTPP data were found to be the most complete, consistent, and reliable. 

• Use the freezing isotherm as a threshold value to determine freeze or no-freeze state of 

the unbound materials. 

• Use analysis of moisture and electrical resistivity trends for temperatures close to the 

freezing isotherm value, where available, to evaluate temperature-based frost predictions 

and make corrections as necessary. 

• Use thermodynamic modeling to predict missing temperatures and to gain insights into 

the heat exchange processes in the unbound layers to aid in frost penetration 

determination. 

DETERMINATION OF FREEZING ISOTHERM 

In the LTPP frost penetration analysis, the freezing isotherm was used to define a threshold 

temperature value differentiating between the freeze and no-freeze states of unbound pavement 

layers. The official definition of frost condition provided by the National Snow and Ice Data 

Center (NSIDC) is the condition which exists when the temperature of earth-bound objects falls 

below freezing (0 o

C) (http://nsidc.org/cgi-in/words/letter.pl?F). However, based on the soil type 

and salinity, this temperature could have been depressed below 0 oC, making frost determination 

based on temperature alone questionable at low-freezing temperatures (0 o

Cto -1 oC). In such 

circumstances, changes in moisture and ER values were used to aid in freeze state determination. 

As soil temperature crosses over the freezing isotherm value, the following changes in moisture 

and ER values are expected: 

• Transition from a no-freeze to freeze state—sharp decrease in moisture at the end of 

transitional period in wet soils. ER values are low before the beginning of freezing and 

high once the complete freeze occurs; ER readings can be ambiguous during the 

transition period. Temperature drops below 0 o

C at the end of transition. 

• Transition from freeze to no-freeze state—increase in the moisture and sharp decrease in 

ER values at the end of the freezing period. Temperature rises above 0oC at the end of 

transition. 

Close examination of the LTPP data showed that no sites had strong or consistent evidence of the 

freezing isotherm being depressed below -1 o

C. Based on these observations and considering the 

NSIDC frost definition presented at the beginning of this section, 0 o

C was chosen as a default 

freezing isotherm for the analysis. 
26

To account for the possibility that the freezing isotherm could be below 0 oC, a step was added to 

the analysis procedure that required a manual review and assignment of a freeze state based on 

conclusions from temperature, ER, and moisture trends analyses for the periods of time with 

temperatures between 0 o

C and -1 oC. This provision allowed assignment of no-freeze or 

transitional conditions even when temperatures were below 0 o

C. 

DETERMINATION OF FREEZE STATE 

Freeze-Thaw Processes 

Frost forms in unbound pavement layers and subgrade when moisture is present in the soil and 

the temperature of the soil matrix falls below the freezing point of the contained water. When 

soil undergoes freezing or thawing, temperature stays constant at about the freezing/thawing 

point until the entire body of water is completely frozen or thawed. This physical process is 

known as the latent heat of fusion. The length of the constant temperature period varies with soil 

type, the amount of moisture in the soil, and the rate of change in air temperature. More saturated 

soils take longer to freeze. Granular materials are more likely to have a distinct freezing 

temperature, while fine-grained soils can have a considerable freezing range over which the soil 

water freezes. 

In the spring, sunshine and warm air temperatures result in a top-down thawing of the pavement 

system. The water released by the melting ice can be trapped by deeper, still frozen material, 

creating saturated or supersaturated conditions that weaken the pavement structure. The thawing 

process can take from several weeks to several months, depending on the type of soil and the 

ease with which the excess water can drain back to the water table. 

Freeze State Assignment 

Close examination of daily thermistor readings in conjunction with the observation of ER and 

moisture trends were used to determine the freeze state of the unbound materials. The first-order 

approximation of the freeze state of the soil was determined by analyzing changes in subsurface 

temperatures with respect to the 0 °C freezing isotherm. For each site with subsurface 

temperature measurements, a frozen state of the soil was assigned for dates and depths with 

temperatures below 0 °C freezing isotherm. A no-freeze state was assigned to the soil for dates 

and depths with temperatures above 0 °C freezing isotherm. 

Following this initial freeze state assignment, a more detailed analysis was conducted for the 

dates and depths with temperatures that fell in the range 0 ° to -1 °C. In this analysis, in addition 

to temperature readings, changes in ER and moisture values were analyzed over time and 

through the depths to determine the freeze state of the soil. If analysis of ER and moisture trends 

did not provide evidence supporting either transitional or no-freeze state, the freeze state 

previously assigned using the 0 °C freezing isotherm was not changed; otherwise, a new freeze 

state was assigned. Table 3 provides a summary of expected trends in temperature, moisture, and 

ER measurements to support assignment of different freeze state conditions. 
27

Table 3. Freeze state characteristics. 

Soil freeze 

state 

ER 

trend 

TDR 

trend Temperature trend Characterized by physical process 

Frozen High Low Below freezing 

isotherm 

Pore water is solid frozen. Ice lenses 

formed in frost-heave susceptible soils 

Unfrozen Low High 

Above freezing 

isotherm or above 

0 °C

Pore water is in a liquid state 

Transitional Unstable Rapid 

change 

Around freezing 

isotherm 

Pore water is transitioning between 

liquid and solid state or partially frozen 

Due to a limited availability of ER and moisture data for the dates of interest and sometimes due 

to inconclusive or unexplained ER and moisture trends, only a limited number of sites had the 

results of temperature-based freeze state prediction changed based on ER and moisture trend 

analysis, resulting in a limited number of transitional and no-freeze state assignments reported 

for temperatures at or below 0 °C. 

In addition, for some of the SMP I sites that had ER data available but no measured or predicted 

temperature and moisture data, freeze states were established based on the analysis of seasonal 

changes in ER trends. Freeze states were determined for the dates that corresponded to the 

historical winter months and had high ER values on a scale normalized from 0 to 1. 

THERMODYNAMIC MODELING OF SUBSURFACE TEMPERATURES 

Thermodynamic modeling of the pavement structure was included in the LTPP frost penetration 

analysis for two reasons. First, it provided means for small amounts of missing subsurface 

temperature data to be accurately interpolated from the measured data. Second, thermodynamic 

modeling based on measured temperatures was used to aid in understanding the physical 

processes that took place in the field. 

Thermodynamic modeling of the pavement structure was accomplished using EICM. The 

EICM’s temperature auto-correction option was used in the analysis of LTPP data. Using this 

option, the EICM-predicted temperature values for each day were auto-corrected based on actual 

measured thermistor readings. The temperature profile for each SMP site was modeled on a daily 

basis, with the initial temperature profile being the previous day’s temperature reading. If there 

were measured data for the following day, the EICM prediction were ignored. If measured 

temperature data were missing for the following day, temperature predictions considering all of 

the required inputs were made. 

Prior to this daily auto-correction, the site was modeled and the inputs were calibrated to give an 

accurate set of predictions using the following procedure: 

1. Select model inputs for a specific site from the LTPP construction history, materials, and 

testing tables, along with the collected climatic data. 

2. Run the model. 

3. Compare these predictions to the actual measured values. 
28

4. Calibrate the model by varying the initial parameters so that the EICM predicted 

temperature profile exactly matches the known measured profile. 

The secondary use of the EICM was to ensure that basic thermodynamic behavior was not 

violated in the course of determining frozen and thawed zones within the structure. For example, 

it is practically impossible for a soil to freeze to a depth of 2 m (6.56 ft) over a 24-hour period. 

The amount of heat released from freezing such a large quantity of water could not escape from 

the pavement or ground. 

Cautionary Note 

The thermodynamic modeling of subsurface pavement and soil layers can be an inexact science. 

Nonuniformity of materials, variable ground water tables, and other poorly defined inputs can 

cause considerable divergence between actual and predicted values. Careful modeling and 

selection of appropriate defaults can appreciably increase the prediction accuracy of 

thermodynamic programs but still will not yield accurate predictions for all cases. The autocorrection process is tedious and is based on the subjective analyst’s judgment in selection of 

unknown input parameters. Furthermore, the EICM requires an extensive list of site-specific 

inputs. Not all of the required input parameters were available in the LTPP database, and those 

that were available were not available for all SMP sites. 

LTPP FROST PENETRATION ANALYSIS PROCEDURE 

The flowchart in figure 12 shows the step-by-step process used to determine freeze state and 

layers for unbound pavement layers and subgrade for each LTPP site included in this study. 
29

Figure 12. Chart. Frost depth and layers interpretation using E-FROST. 

Pre-processing steps 

For each measurement depth with -1<= T <= 0 oC, using 

E-FROST: 

Check for records missing soil temperature in the analysis 

database 

Generate frost penetration profiles 

Review and QC frost 

estimates 

Manually re-interpret freezing state conditions, based on 

trend plot and EICM analyses, as needed 

Open E-FROST program and upload pre-processed data 

For each LTPP SMP site use E-FROST to generate 

AutoFrost profile using 0 o

C freezing isotherm 

Review temperature, ER, and moisture, trend plots to 

determine any transitional or no-freeze conditions for 

frozen layers identified on AutoFrost profile 

Prepare SMP_FREEZE_STATE table 

Compute frost penetration depth and prepare 

SMP_FROST_PENETRATION table 

Prepare submission data files 

QC generated tables 

Predict temperature 

using 

thermodynamic 

EICM model 

Pre-process raw electrical resistivity, soil temperature and 

moisture data and prepare analysis database 

Extract supporting LTPP data 

Add EICM predicted soil temperature to the analysis 

database 

Temperature gap? Yes No
30

Additional Analysis Rules 

Upon a detailed data review, it became apparent that not all of the data were available for every 

measurement date and depth, and some of the trends based on the in-situ data were difficult to 

interpret, leading to subjectivity in assignment of freeze states by the analyst. To minimize the 

subjectivity of the frost estimates and to provide uniformity of the analysis procedures, a set of 

guidelines was developed and followed by the data analyst. 

During the data analysis phase, the following rules were followed when data were sparse or some 

of the measurements were ambiguous: 

1. For each date and measurement depth that had at least subsurface temperature or ER data 

available, freeze state estimates were conducted using methodology presented earlier in 

the report. 

2. If subsurface temperature measurements and ER data were missing for a portion of the 

winter season and there were sufficient LTPP data to estimate missing temperatures from 

EICM analysis, these estimated temperatures were used to evaluate freeze state. The 

source of the temperature in the SMP_FREEZE_STATE table was specified as estimated 

from EICM. 

3. For measurement depths and/or dates where no in-situ data and no EICM-predicted 

temperature values were available to predict the freeze state, no freeze state 

determinations were made, even though frozen depths were reported for surrounding 

depths and/or dates. 

4. For some SMP I sites that had ER data available but no measured or predicted 

temperature and moisture data, freeze states were determined based on the analysis of 

seasonal changes in ER trends. Freeze states were determined for the dates that 

corresponded to the historical winter months and have high ER values on normalized 

scale from 0 to 1. 

5. If, for a particular date and depth, the soil temperature was above 0 o

C, the freeze state 

was reported as N-unfrozen. 

6. If, for a particular date and depth, the soil temperature was below -1 oC, the freeze state 

was reported as F-frozen. 

7. If, for a particular date and depth, the soil temperature was below 0 o

C, the moisture 

values were low, and ER values were high, the freeze state was reported as F-frozen. 

8. If, for a particular date and depth, the soil temperature was below 0 o

C, the moisture 

values were low, and no ER values were reported, the freeze state was reported as 

F-frozen. 

9. If, for a particular date and depth, the soil temperature was below 0 o

C, the ER values 

were high, and no moisture values were reported, the freeze state was reported as 

F-frozen. 

10. In the absence of moisture and ER data or when ER and moisture trends are inconclusive, 

the freeze state was reported as F-frozen for temperatures less or equal 0 o

C. 
31

11. If, for a particular depth, constant negative temperatures near 0 oC were observed over a 

few days, the freeze state was reported as T-transition and the following trends arose: 

• Constant negative temperature near 0 oC over a few days + continuous rapid increase 

in moisture + low ER at the end of transition (thawing process). 

• Constant negative temperature near 0 oC over a few days + continuous rapid decrease 

in moisture + high ER at the end of transition (freezing process). 

• Constant negative temperature near 0 oC over a few days + continuous rapid increase 

in moisture, No or ambiguous ER data (thawing process). 

• Constant negative temperature near 0 oC over a few days + continuous rapid decrease 

in moisture, No or ambiguous ER data (freezing process). 

Data Normalization and Interpolation 

To aid in the visual interpretation of the analysis results, electrical resistivity values were 

normalized on a scale from 0 to 1. Normalization was carried out for each analysis depth and 

construction event, which was identified by the change in the construction number. The 

following basic normalization formula was utilized: 

Max_Of_Actual_Measurement-Min_Of_Actual_Measurement

Actual_Measurement-Min_Of_Actual_Measurement Normalized_Measurement =

Figure 13. Equation. Normalized measurement. 

Where: 

 Normalized_Measurement = Normalized measurement 

 Actual_Measurement = Actual measurement 

 Min_Of_Actual_Measurement = Minimum actual measurement 

 Max_Of_Actual_Measurement = Maximum actual measurement 

Extracted LTPP temperature and moisture content data were interpolated to ER analysis depths 

established in earlier LTPP frost penetration studies(3) using the following linear interpolation 

formula: 

L

X edInterpolat _ Measuremen = Uppert _ Measuremen + (Lowert _ Measuremen −Uppert _ Measurement)

Figure 14. Equation. Interpolated measurement. 

Where: 

 Interpolated_Measurement = Interpolated temperature or MC value 

 Upper_Measurement = Temperature at upper thermistor or MC for upper 

TDR sensor 

 Lower_Measurement = Temperature at lower thermistor or MC for lower 

TDR sensor 
32

 X = Distance from the ER analysis depth to the upper 

thermistor or TDR sensor 

 L = Distance between the two thermistors or TDR 

sensors 

QUALITY CONTROL/QUALITY ASSURANCE PROCESS 

The results of data analysis were independently reviewed. During the review process, emphasis 

was placed on evaluating whether or not the results produced by the analyst followed the basic 

physical process of latent heat of fusion as described earlier in this chapter. In addition to 

reviewing the frost penetration profiles, trends in temperature, ER, and moisture changes were 

reviewed and correlated to evaluate the accuracy of analyst assigned freeze states. 

Spatial and Temporal Checks 

Frost penetration profiles were reviewed to evaluate the progression of frost penetration with 

time and depth and to check for any potential data gaps or presence of intermediate unfrozen 

layers. The following two checks were used to QC the initial freeze state assignments for all the 

cells in frost penetration plot except the boundary cells (boundary cells belong to the first frozen 

depth layer, the last frozen depth layer, the first and the last date with frost for each depth): 

Spatial check for a given date is as follows: 

• If a layer above (= depth i-1) was determined as frozen, a layer below (= depth i+1) was 

determined as frozen, and the temperature remained < = 0 o

C, then the layer in between 

(= depth i) is likely to be frozen and should be assigned as freeze.

• If a layer above was determined as no-freeze (= depth i-1), a layer below (= depth i+1) 

was determined as no-freeze, and the temperature remained near 0 o

C, then the layer in 

between (= depth i) is likely to be no-freeze and should be assigned as no-freeze. 

Temporal check for a given depth is as follows: 

• If the freeze state for a date before was determined as frozen, the freeze state for a date 

after was determined as frozen, and the temperature remained < = 0 o

C for all three dates,

then the freeze state for the date in between is likely to be frozen and should be assigned 

as freeze.

• If the freeze state for a date before was determined as no-freeze, the freeze state for a date 

after was determined as no-freeze, and the temperature remained near 0 oC for all dates,

then the freeze state for the date in between is likely to be no-freeze and should be 

assigned as no-freeze.
33

Trend Reasonableness Check 

ER, moisture, and temperature time-series plots were reviewed to evaluate reasonableness of ER 

and moisture changes with respect to temperature changes. The expected trends for ER and 

moisture changes are described as follows: 

• Moisture: Expect to see a drop in moisture at the beginning of freeze period, as 

temperatures drop below 0 oC; low moisture values during frozen period; and rise in 

moisture during thawing, as temperatures climb above 0 oC. 

• ER: Expect to see rise in ER at the beginning of freeze period, as temperatures drop 

below 0 oC; high ER values during freeze period; and drop in ER during spring thaw, as 

temperatures climb above 0 oC. 

If and when the moisture and/or ER trends did not follow the expected trends described above, 

freeze assignment was based on temperature values with 0 oC used as freezing isotherm. 

Analysis Results Database Checks 

Finally, the results of the analysis compiled in the LTPP computed parameter tables were 

reviewed to assure data completeness, data integrity, and proper formatting. 

35

CHAPTER 5. IMPLEMENTATION OF THE ENHANCED FROST ANALYSIS 

METHODOLOGY 

UPDATES TO FROST PROGRAM 

Using the data analysis methodology presented in chapter 4, the existing FROST interactive 

procedure was updated to enhance the analysis algorithm, to address changes from SMP II 

experiment, and to assure compatibility with current database technology. The updated 

supporting research tool was named E-FROST to differentiate with the previous version. 

E-FROST Overview 

The E-FROST research tool was developed to aid the data analyst in reviewing LTPP SMP data 

(temperature, ER, and moisture) and assigning freeze states based on the observed data trends. 

The primary functions of E-FROST are (1) to show time-series data from the in-situ 

measurements (ER, temperature, and moisture), (2) to generate and graphically represent frost 

penetration profiles, and (3) to create a frost penetration table containing frost penetration depths 

for different dates for which in-situ measurements were taken. The E-FROST user’s guide with 

detailed instructions and examples is provided in appendix A. 

Enhancements to LTPP Frost Interactive Procedure 

Several improvements were made to the existing FROST interactive procedure to help determine 

the freeze state. To improve accuracy in frost penetration predictions in subsurface layers, the 

FROST algorithm was modified to include all available temperature, moisture, and ER data in 

the frost penetration analysis. The E-FROST graphic user interface was updated to provide 

means for review of daily temperature, moisture, and ER data plotted on the same plot. This 

feature enables the analyst to conduct comprehensive trend analysis of changes in temperature, 

ER, and moisture data in order to determine the freeze state of the soil at any date and depth that 

had in-situ measurements collected by LTPP. 

The AutoFrost option was added to generate the initial frost penetration profile based on 

subsurface temperature values. This feature uses an objective measure, such as temperature at 

water freezing point, as a threshold value to determine the initial frost penetration profile instead 

of an arbitrary threshold value selected by the analyst, as was used in the previous FROST 

algorithm. 

The EICM software was used for thermodynamic modeling of temperature distribution in 

subsurface layers, as appropriate, to fill the gaps in the field data and to aid the analyst in the 

examination of heat transfer processes based on the in-situ temperature data for the site. EICMestimated subsurface temperature data was included in the E-FROST database so that it can be 

displayed on the interactive trend plots for the sites with missing or limited measured 

temperature data. 
36

Changes from SMP II Experiment

The original FROST program was developed to process data from the SMP I experiment. 

Introduction of the SMP II experiment led to the development of the new LTPP database tables 

to store ER data and resulted in a significant increase in the quantity of data to process for each 

site. 

Introduction of the SMP II experiment also resulted in a different ER table structure and a 

significant increase of data to be processed for each SMP II site. E-FROST accounts for these 

changes. To cope with massive amounts of data, the program provides the analyst with options to 

review the data for the selected time intervals instead of displaying data for all dates on a single 

plot. The program routines and preprocessing database were updated to ensure database 

compatibility with Microsoft® Access 2000 or later, which is needed to facilitate preprocessing 

of the new SMP II data. 

ENHANCED FROST ALGORITHM 

The decision tree algorithm for the E-FROST program is presented in figure 15. 
37

Figure 15. Chart. Enhanced FROST algorithm. 

E-FROST Symbol Color Codes and Shapes for the Decision Tree 

Upon execution, E-FROST creates a temperature-based first order approximation of frost 

penetration profile for each SMP site using the AutoFrost analysis option. The profile consists of 

a grid with the horizontal axis displaying different SMP dates on a daily scale and the vertical 

T 

available?

Freeze 

T < -1 oC

Thermodynamic 

modeling of T 

using EICM 

Normalized 

Electrical 

Resistivity

No

Subsurface 

Temperature, 

T

Manually review of ER, 

TDR, and T trends and to 

determine freeze state 

% Moisture 

Content 

from TDR 

EICM Inputs: 

Climate, layers, 

material 

Yes

Generate AutoFrost 

profile based on 

subsurface 

temperatures using 

0 oC isotherm

T > 0 oC

No

Yes

Yes

No

No Freeze Transition 

Manually review frost 

penetration profile and 

make freeze state 

adjustments as necessary
38

axis displaying different analysis depth based on ER probe depths. Each cell is color-coded to 

provide information about the freeze state at a given date and given depth (see table 4). 

Table 4. Freeze state and frost depth chart symbol shape and color coding. 

Color 

code 

Symbol 

shape 

Assigned 

freeze state 

Subsurface 

temperature Analyst’s action 

Blue Rectangle Freeze T < -1 o

C

Assigned automatically; however, the analyst 

has an option to change the state to transitional 

(pink) or no-freeze (white) upon data review 

White Rectangle No freeze T > 0 o

C

Assigned automatically; however, the analyst 

has an option to change the state to transitional 

(pink) or freeze (blue) upon data review 

Light 

blue Triangle Review T < 0 o

C and 

T > -1 oC 

Assigned automatically; however, the action is 

required from analyst to manually review the 

data and change the state to freeze, no-freeze, or 

transitional 

Pink Diamond Transitional Near freezing 

isotherm 

This color is assigned upon analyst review of all 

supporting data when it is not clear whether soil 

is frozen or not (partially frozen case) 

The E-FROST algorithm automatically assigns the state of subsurface freeze condition at each 

electrode location using the following rules: 

• The 0 oC freezing isotherm value is used as the low boundary to define the no-freeze 

state. No-freeze is automatically assigned to all points with temperatures above 0 oC 

(white cells). 

• A value of -1 oC is used as an upper boundary to define the freeze state. Freeze is 

automatically assigned to all points with temperatures below -1 o

C (blue cells). 

• All data that fall between the two boundaries are flagged for manual review by the 

analyst to determine the appropriate freeze state based on ER, temperature, and moisture 

trend analysis (light blue triangles). 

Based on the assigned freeze state, different actions will be required. No actions are required for 

blue or white cells. If E-FROST assigns the cell as “Review” (light blue triangle), the analyst 

must review the data and change the freeze state as appropriate. To aid in this decision, 

E-FROST creates a time-series plot of ER, temperature, and moisture content changes. The plot 

appears on the screen once the analyst clicks on the light blue triangle cell. Similar plots can be 

brought up for review by clicking on any other cell on the frost penetration profile chart. 

FROST PENETRATION ANALYSIS EXAMPLE 

The following example demonstrates the frost penetration analysis procedure to determine the 

freeze state and layers for unbound pavement layers and subgrade for LTPP site 0804 in 
39

South Dakota. This site was chosen for the example because it contains the most comprehensive 

temperature, ER, and moisture data and provides means for cross-comparison of changes in all 

three measurement types. The plots provided in this example were generated using E-FROST. 

Step 1. Prepare E-FROST Inputs Database 

ER, temperature, and moisture content data were obtained from the LTPP tables, which are 

specified in chapter 6. When measured subsurface temperatures were not available, temperature 

values were estimated using the EICM thermodynamic model; EICM inputs are listed in 

appendix B. An example of how temperature gaps could be filled out by EICM predictions using 

the thermodynamic model was shown in figure 11 (chapter 3). 

Extracted LTPP data were preprocessed to obtain normalized ER values at calculated analysis 

depths and to interpolate temperature and moisture content data to those depths. Preprocessed 

electrical resistivity, temperature, and moisture content data were assembled in the analysis 

database table required to run E-FROST. 

Step 2. Generate an “AutoFrost” Freeze State Profile 

An automatic frost penetration profile was generated based on thermistor readings with the 0 o

C 

isotherm used as a threshold value to differentiate freeze states. In the example shown in figure 

16, all data points with temperature readings above 0 oC are shown using white squares with grey 

borders. These data points correspond to no-freeze states. All data points with temperature 

readings below -1 oC are shown using blue squares. These data points correspond to freeze 

states. Data points with temperature readings between data 0 oC and -1 oC are shown using light 

blue triangles. These data points require manual review, as they may represent a(n) frozen, 

unfrozen, or transitional state of soil. 
40

Figure 16. Chart. Example of temperature-based frost penetration profile for section 0804 

in South Dakota. 

Step 3. Review ER, Moisture, and Temperature Trends 

Temperature, ER, and moisture content time-series trends were examined to verify the freeze 

state of soil assigned by the AutoFrost option, especially when temperatures were close to 0 o

C. 

This was done by reviewing and correlating changes in temperature with changes in ER and 

moisture trends. E-FROST was used to graph temperature, ER, and moisture changes with time 

for each winter season and each measurement depth. 

Upon data review, the state of soil was assigned to every date at every depth using trends 

described in table 3 as guidance. For the example shown in figure 17, the no-freeze state was 

assigned to dates prior to December 15 because the temperature readings, although close to 0 oC, 

never crossed the 0 axis. The state of the soil between December 16 and 24 was assigned as 

freeze as the data show a rapid drop in temperature values below 0 oC, followed by a decrease in 

moisture content. A transitional state of soil was assigned to December 25–27 and 30–31. Even 

though the temperature reading remained below 0 oC for these dates, there was a significant 

increase in moisture content, indicating thawing. The state of the soil for December 28 and 29 

was assigned as no-freeze, as temperature values for these dates were above 0 oC. The state of the 

soil from January 1, 1999, to February 21, 2000, was assigned as freeze, as the trends in all three 
41

types of measurements (temperature, moisture, ER) indicated the possibility of frost—sharp 

decrease in moisture, sharp increase in ER, and temperature drop below 0 oC. For February 22, 

2000, the no-freeze state was assigned based on observed trends in all three measurements: 

temperature rapidly rising above 0 oC, sharp decrease in ER, and sharp increase in moisture. 

Figure 17. Chart. Example of ER, temperature, and moisture trends for section 0804 in 

South Dakota at 0.55 m (1.8 ft) depth. 

Step 4. Generate and Review Frost Penetration Profile 

Upon the completion of trend analysis at each of the 35 measurement depths and assignment of 

freeze states by the analyst, the E-FROST algorithm displays color-coded frost penetration 

profiles for review and quality assurance, as shown in figure 18. 

Because of many less-than-ideal scenarios in the field data, the data interpretation process can be 

subjective. If the freezing condition at a particular point is in disagreement with the surrounding 

points (e.g., the point shows freezing while the soil above and below shows a no-freeze state), 

then the freeze state of that point may be changed by the analyst or QA reviewer to agree with 

that of the surrounding soil. 
42

Figure 18. Chart. Example of final frost penetration profile for SMP site 46-0804 for the 

winter of 1999.

Step 5. Calculate Frost Depth Using Freeze State Information 

Using freeze state information at each measurement depth, frost depths were computed for each 

date using E-FROST. Frost depth calculations were based on the interpreted freeze states 

(F-frozen and T-transitional or partially frozen). 

For each date, frost depths were computed based on the interpreted freeze states (F-frozen and 

T-transitional or partially frozen) using the following algorithm: 

• Starting (top) depth of a frozen layer was determined as the first measurement depth from 

the pavement surface where “F” freeze state was determined on frost penetration plot 

(shown in figure 18). 

• Ending (bottom) depth of a frozen layer was determined as the last measurement depth 

from the pavement surface where “F” freeze state was determined on frost penetration 

plot. 

• If, for a given date, a no-freeze state “N” was found within the vertical array of freeze 

states “F,” then multiple freeze layers were reported for that date. In these cases, the 
43

bottom of the first frozen layer was determined as the last measurement depth with freeze 

state “F” before the intermediate no-freeze ”N” layer. The top of the second frozen layer 

was determined as the first measurement depths with freeze states “F” after the 

intermediate no-freeze ”N” layer. 

• No frozen depths or layers were estimated for depths and dates without measured 

temperature and ER data. 

Freeze state information was added to SMP_FREEZE_STATE, and frost depth information was 

added to the SMP_FROST_PENETRATION table. 

Limitations of Transitional Freeze State Estimates 

During temperature data analysis, there were multiple cases when temperatures were around 0 oC 

over a period of several days, pointing to a possibility of a transitional freeze state. However, 

these temperature trends were not consistently observed from one depth to another or for 

different years. Therefore, without supporting data (ER, moisture, soil salinity) or in cases of 

inconclusive supporting data trends, it was not possible to make definite conclusions whether or 

not the soil was in a transitional state. 

Analysis of the sites that had similar temperature trends and had supporting ER and moisture 

data revealed that, although temperature values may indicate possible transitional state, low 

moisture and high ER values during the same period may provide evidence that soil may be in a 

freeze or no-freeze state. The following example demonstrates subjectivity of transitional state 

assignment based on temperature data alone. The temperature trend shown in figure 19 indicates 

the possibility of a transitional state of soil during the months of January and February 2001 

based on temperatures just below 0 oC over an extended period of time. However, high ER 

values during the same period indicate that the state of soil is likely to be frozen. No moisture 

data are available for the same analysis period. 

As a result of this limitation, the majority of freeze state estimates developed in this analysis 

study fall in either frozen or unfrozen categories. No transitional states were assigned based on 

the analysis of the temperature data alone, as that approach was found to be too subjective in 

absence of other supporting information (moisture, ER, soil salinity). When supporting ER and 

moisture data were available, a more detailed trend analysis was conducted resulting in a limited 

number of transitional state assignments. 
44

Figure 19. Chart. Temperature and ER trends at 1.02 m (3.35 ft) for site 50-1002 during 

winter season 2000–2001. 
45

CHAPTER 6. LTPP DATA USED FOR FROST DETERMINATION 

During Phase I of the project, the research team assessed the availability of the LTPP data 

needed to support the enhanced algorithm for evaluation of frost penetration. This assessment 

included data utilized by the existing FROST procedure and the LTPP data that will be utilized 

by the enhanced FROST procedure. The results of the assessment are summarized in this section. 

DATA REQUIRED FOR E-FROST ANALYSIS 

The following LTPP database tables containing subsurface temperature, electrical resistivity, and 

moisture data were used to determine frost penetration under bound pavement layers: 

• SMP_ERESIST_AUTO_ABF—Contains new ER measurements (VOLTAGE and 

RESISTANCE) for SMP II sections. 

• SMP_ERESIST_AUTO—Contains automated electrical contact voltage data for each 

electrode number. 

• SMP_ERESIST_MAN_4POINT—Contains manually collected four point electrical 

contact resistance measurements: 

o Voltage reading between voltage electrodes. 

o Electrical current reading between current electrodes. 

o Computed electrical resistivity. 

• SMP_ERESIST_MAN_CONTACT—Contains manually collected two point electrical 

contact resistance measurements: 

o Voltage reading between electrodes. 

o Electrical current reading between electrodes. 

o Computed contact resistance between two electrodes. 

• SMP_ERESIST_DEPTHS—Contains depth from the pavement surface for each 

electrode. 

• SMP_MRCTEMP_AUTO_DAY_STATS—Contains daily pavement subsurface 

temperature for the thermistors in the MRC thermistor probe closest to the surface. 

• SMP_MRCTEMP_DEPTHS—Contains the installed thermistor depth. 

• SMP_ERESIST_ABF_REF_VA—Contains background information related to ER 

measurements using ABF equipment for SMP II sections (this table is not be used 

directly in the ER data processing). 

• SMP_TDR_AUTO_MOISTURE—Contains computed volumetric moisture content in 

percentile form. 

• SMP_TDR_MANUAL_MOISTURE—Contains volumetric moisture content in 

percentile form based on most probable value of apparent length interpreted from manual 

TDR trace. 
46

• SMP_TDR_DEPTHS_LENGTH TDR_DEPTH— Contains depth from pavement surface 

to TDR probe in meters. 

Data from 1993 to 2001 were used to reinterpret previous frost estimates, and data from 2001 to 

2004 were used to develop new frost estimates. 

DATA REQUIRED FOR EICM ANALYSIS 

In applying the EICM, the project team used section-specific data where they were available and 

pertinent to subsurface temperature prediction. The actual climatic measurements, layer, and 

material information collected at the site were used as inputs to the EICM. These measurements 

are included in the following tables: 

• INV_ID—Contains longitude, latitude and elevation information. 

• INV_GRADATION—Contains information about particle sizes. 

• TST_L05B— Contains information about number of layers, layer and material type and 

layer thickness. 

• TST_UG04_SS03—Contains information about plasticity index. 

• TST_SS11—Contains hydraulic conductivity and initial water content information. 

• TST_UG09—Contains hydraulic conductivity information. 

• SMP_ATEMP_RAIN_DAY—Contains daily air temperature and rainfall statistics. 

• SMP_ATEMP_RAIN_HOUR—Contains hourly ambient air temperature and rainfall. 

• SMP_DRY_DENSITY—Contains subgrade dry density measurements. 

• SMP_ELEV_AC_DATA—Contains AC surface elevation measurements. 

• SMP_ELEV_PCC_DATA—Contains PCC surface elevation measurements. 

• SMP_GRAV_MOIST—Contains pavement subsurface gravimetric moisture content. 

• SMP_MRCTEMP_AUTO_DAY_STATS—Contains daily pavement subsurface 

temperature statistics. 

• SMP_WATERTAB_DEPTH_MAN—Contains automated data on the depth to ground 

water table. 

• CLM_VWS_TEMP_DAILY—Contains daily temperature data. 

• CLM_VWS_WIND_DAILY—Contains daily wind data. 

• AWS_DAILY_DATA—Contains daily temperature and wind data. 

Default or assumed values were used for some of the required data elements that were not 

included in the LTPP database. The climatic data from the National Climatic Data Center for a 

specified longitude and latitude were used where section-specific weather data were not 

available. These climatic data are integrated in the EICM program. EICM inputs are provided in 

appendix B. 
47

ANALYSIS DATABASE SUMMARY 

The data from the LTPP tables discussed above were assembled in the analysis database. All 

records were organized by LTPP site, date, and measurement depth. For each analysis site and 

date, up to 35 records containing ER, temperature, and moisture data were prepared—one for 

each analysis depth. 

One of the issues in processing electrical resistivity, moisture, and soil temperature data was that 

these data elements are measured at different depths. Therefore, data manipulation was required 

to correlate various electrical resistivity, soil temperature, and moisture values. To preserve the 

same interpretation depths as were used in the previous LTPP frost studies,(3) linear interpolation 

was used to obtain soil temperature and moisture values at the ER interpretation depth. In the 

previous LTPP frost studies, ER interpretation depth was defined as a middepth between two 

neighboring electrodes, resulting in 35 analysis depths for 36 electrodes included in the 

resistivity probe. 

Only dates that had either ER or temperature data were included in the analysis database. 

Records for the months with the minimum monthly temperature above +1 o

C and with no ER 

data were not included in the analysis database because no freeze conditions are possible when 

temperatures are above +1 o

C. 

EICM-predicted temperatures were added to the database to fill in the gaps in measured 

temperature data. EICM predictions were provided only for the sites that had sufficient sitespecific EICM inputs. Only gaps of less than one month were filled with EICM predicted 

temperature values. Source of temperature data was specified in the analysis database to 

differentiate between measured and predicted temperature data. 

Table 5 summarizes the number of records that were assembled in the analysis database for each 

of the 41 LTPP SMP sites included in the frost study. As can be seen, measured temperature data 

were the most complete data element, corresponding to the largest number of records in the 

analysis database. 
48

Table 5. Summary of data assembled for frost penetration analysis. 

State 

code 

SHRP 

ID 

Years 

with 

data 

Days 

with 

data 

Minimum 

date 

Maximum 

date 

Number 

of ER 

data 

records 

Number 

of 

measured 

temperature

records 

Number 

of EICMmodeled 

temperature

records 

Number 

of 

volumetric 

moisture 

records 

4 (AZ) 1024 4 22 9/14/1995 11/19/1998 770 490 0 561 

8 (CO) 1053 5 285 7/1/1993 9/26/1997 1,320 9,286 0 587 

9 (CT) 1803 5 277 8/19/1993 10/16/1997 1,375 9,102 0 1,042 

16 (ID) 1010 5 355 10/1/1993 6/26/1997 1,235 10,596 1,157 1,031 

18 (IN) 3002 4 250 9/8/1995 9/28/1998 412 8,273 0 280 

20 (KS) 4054 4 117 8/25/1995 11/19/1998 694 3,671 0 477 

23 (ME) 1026 5 466 9/16/1993 10/21/1997 1,324 15,801 0 888 

24 (MD) 1634 4 142 5/12/1995 4/8/1998 978 4,445 0 823 

25 (MA) 1002 2 83 9/1/1993 10/26/1994 490 2,625 0 227 

27 (MN) 1018 7 568 8/24/1993 9/8/1997 1,569 19,022 0 628 

27 (MN) 1028 5 835 9/9/1993 9/10/1997 1,352 28,844 0 691 

27 (MN) 4040 5 629 9/22/1993 9/9/1997 1,420 20,448 1,088 767 

27 (MN) 6251 10 1,486 9/15/1993 10/8/2003 2,110 50,401 774 1,128 

30 (MT) 0114 5 896 7/16/2000 9/22/2004 7,876 30,038 0 26,000 

30 (MT) 8129 6 326 8/12/1992 10/1/1997 1,728 10,194 0 498 

31 (NE) 0114 7 441 8/8/1995 7/11/2002 1,203 13,382 0 637 

31 (NE) 3018 9 724 8/11/1995 12/31/2003 1,446 22,852 1,922 825 

32 (NV) 0101 6 355 11/6/1996 3/19/2003 4,267 10,399 0 4,889 

32 (NV) 0204 2 67 12/1/1996 9/9/1997 239 2,234 0 196 

33 (NH) 1001 5 417 10/14/1993 10/22/1997 1,219 14,078 0 652 

34 (NJ) 0504 3 170 2/11/2002 3/13/2004 1,915 3,924 0 0 

34 (NJ) 0505 3 186 2/11/2002 4/7/2004 2,695 3,925 0 0 

34 (NJ) 0506 3 179 2/1/2002 4/7/2004 1,610 2,579 1,285 0 

34 (NJ) 0507 3 174 2/2/2002 4/7/2004 1,295 3,913 0 0 

34 (NJ) 0902 3 147 3/26/2002 4/7/2004 2,415 3,363 87 0 

36 (NY) 0801 10 913 8/23/1995 3/31/2004 15,408 29,258 1,713 11,141 

36 (NY) 4018 5 442 10/28/1993 10/14/1997 1,252 14,961 0 707 

39 (OH) 0204 2 45 3/18/1998 10/14/1999 504 1,290 0 282 

39 (OH) 0901 6 720 1/1/1998 10/16/2003 1,218 22,360 2,354 562 

42 (PA) 1606 8 656 8/10/1995 10/15/2003 1,715 21,950 0 1,410 

46 (SD) 0804 9 1,113 7/15/1994 12/16/2003 22,741 36,826 0 15,384 

46 (SD) 9187 4 344 7/19/1994 9/23/1997 827 9,759 1,928 629 

49 (UT) 1001 5 143 10/14/1993 9/24/1997 1,155 3,999 0 894 

49 (UT) 3011 5 281 8/3/1993 9/22/1997 1,338 9,367 0 765 

50 (VT) 1002 10 1,270 10/7/1993 11/30/2003 12,278 42,387 941 11,498 

56 (WY) 1007 5 393 8/11/1993 9/30/1997 1,285 13,147 0 989 

83 (MB) 1801 11 2,116 10/13/1993 11/10/2003 27,051 60,475 0 20,476 

83 (MB) 3802 6 458 10/15/1993 11/5/1998 1,150 13,268 0 643 

87 (ON) 1622 5 469 9/23/1993 10/30/1997 1,393 15,864 0 947 

89 (QC) 3015 9 1,605 9/30/1993 6/6/2001 1,635 55,570 0 1,044 

90 (SK) 6405 6 755 10/6/1993 5/31/1999 1,255 25,815 0 1,031 

Total Records 135,162 680,181 13,249 111,229 
49

CHAPTER 7. FROST PENETRATION ANALYSIS RESULTS 

DATA ANALYSIS SUMMARY 

Using the E-FROST research analysis tool, all previously processed sections with ER data were 

reprocessed using the enhanced analysis methodology presented in chapter 4, and new frost 

depths and layer estimates were determined. In addition to the reinterpretation of the previously 

processed data, all SMP II sections with ER data that had not been previously analyzed were 

analyzed using E-FROST, and new frost depths and layer estimates were prepared for the LTPP 

database upload. The analysis results, as well as the LTPP computed parameters developed under 

this project, were reviewed thoroughly. 

Frost penetration analysis was conducted for 41 LTPP sites from the SMP I and II experiments. 

The schematic location of LTPP sites used in the frost penetration analysis study is shown in 

figure 21. Data from 21,953 dates were analyzed, and frost penetration depths were estimated. 

There were between 2 and 11 years of data analyzed for the different LTPP sites. Detailed frost 

penetration results were reported in two LTPP computed parameters tables discussed later in this 

chapter. 

Figure 20. Picture. Locations of LTPP SMP sites analyzed in this study. 
50

FROST OBSERVATIONS 

Observations discovered during the project are described in this section. 

Severity of Frost Penetration 

Using the results of the frost penetration analysis, average and maximum frost depths were 

determined, along with the first and the last cold month with freeze conditions for each LTPP 

site with in-situ measurement data. This information could be used to assess the severity of frost 

penetration at different LTPP sites. 

Maximum freeze depth corresponds to the maximum frost depth for the year with the deepest 

frost penetration detected during the analysis. Maximum frost depth is used in the design to 

account for the worst case scenario. 

Average maximum freeze depth corresponds to the average of maximum frost depths based on 

all years used in the analysis and represents average or typical frost penetration conditions. 

The first and the last months with freeze conditions are based on the worst case scenario. These 

months were determined by reviewing frost data for all available years and selecting the earliest 

month at the beginning of the freeze period and the latest months at the end of the freeze period. 

A summary of frost determinations is provided in table 6. 

Frost penetration profiles generated for all Minnesota, Manitoba, and Saskatchewan sites and site 

4018 in New York indicate that frost penetration goes beyond the last interpretation depth. For 

Arizona site 1024 and Nevada site 0101, the first interpretation depth was lower than the 

expected frost penetration depth. These cases are noted by starred comments in table 6. 
51

Table 6. Summary of frost determinations. 

STATE 

CODE 

SHRP 

ID 

Number of 

years analyzed 

Average max 

freeze depth, m 

Maximum 

freeze depth, m 

First freeze 

month 

Last freeze 

month 

4 (AZ) 1024 4 * * -- -- 

8 (CO) 1053 5 0.336 0.374 DEC FEB 

9 (CT) 1803 5 0.544 0.794 JAN MAR 

16 (ID) 1010 5 0.763 0.864 NOV FEB 

18 (IN) 3002 4 1.036 1.213 DEC FEB 

20 (KS) 4054 4 1.056 1.056 JAN FEB 

23 (ME) 1026 5 1.107 1.819 NOV APR 

24 (MD) 1634 4 0.436 0.436 FEB FEB 

25 (MA) 1002 2 1.017 1.017 JAN MAR 

27 (MN) 1018 5 1.791 2.181*** NOV APR 

27 (MN) 1028 5 2.275 2.386*** NOV APR 

27 (MN) 4040 5 1.900 2.317*** NOV MAY 

27 (MN) 6251 10 2.126 2.308*** NOV APR 

30 (MT) 0114 5 1.165 1.256 NOV MAR 

30 (MT) 8129 6 0.793 1.082 NOV MAR 

31 (NE) 0114 7 0.844 1.173 DEC MAR 

31 (NE) 3018 9 1.289 1.679 DEC MAR 

32 (NV) 0101 6   — — 

32 (NV) 0204 2 0.612 0.612 DEC JAN 

33 (NH) 1001 5 0.954 1.394 DEC MAR 

34 (NJ) 0504 3 0.406 0.406 JAN FEB 

34 (NJ) 0505 3 0.458 0.458 JAN FEB 

34 (NJ) 0506 3 0.608 0.608 JAN FEB 

34 (NJ) 0507 3 0.455 0.455 JAN JAN 

34 (NJ) 0902 3 0.643 0.668 JAN FEB 

36 (NY) 0801 10 0.627 0.988 DEC MAR 

36 (NY) 4018 5 1.090 2.102** * DEC APR 

39 (OH) 0204 2 0.705 0.705 JAN JAN 

39 (OH) 0901 6 0.704 0.776 DEC FEB 

42 (PA) 1606 8 0.568 0.771 DEC MAR 

46 (SD) 0804 9 1.445 1.998 NOV APR 

46 (SD) 9187 4 1.243 1.827 NOV APR 

49 (UT) 1001 5 1.557 2.019 DEC DEC 

49 (UT) 3011 5 0.553 0.692 DEC FEB 

50 (VT) 1002 10 1.020 1.498 NOV APR 

56 (WY) 1007 5 0.741 0.999 NOV MAR 

83 (MB) 1801 11 2.033 2.13*** OCT MAY 

83 (MB) 3802 6 1.798 2.424*** NOV MAY 

87 (ON) 1622 5 1.194 1.743 NOV APR 

89 (QC) 3015 9 1.316 1.587 NOV MAY 

90 (SK) 6405 6 1.999 2.058*** OCT MAY 

1 m = 3.28 ft 

— No data available. 

* First interpreted depth at 0.38 m. 

** First interpreted depth at 0.51 m. 

*** Possibility of frost beyond the last interpreted depth. 
52

Frost Penetration Profile Characteristics 

Using frost estimates computed based on in-situ data, frost penetration profiles were analyzed for 

each of the 41 LTPP sites for all available years of data. The changes in frost profiles over the 

cold seasons (fall, winter, and spring) were examined for each available year. The review 

indicated that even for similar frost depths, the observed profiles varied from site to site and year 

to year. Hence, knowledge of the maximum frost depth without an understanding of seasonal 

changes in frost penetration profile would not be enough for accurate characterization of 

seasonal changes in pavement structural characteristics. 

Some of the commonly observed frost penetration profile characteristics were multiple freeze 

thaw cycles, shallow fall freeze with thaw followed by solid deep freeze with a spring thaw, and 

solid freeze with spring thaw and refreeze. Figure 21 through figure 23 show examples of each 

of these commonly observed frost penetration profiles. 

Figure 21. Chart. Frost penetration profile showing multiple freeze-thaw cycles. 
53

Figure 22. Chart. Frost penetration profile showing shallow freeze cycles in the fall 

followed by solid deep freeze with spring thaw. 
54

Figure 23. Chart. Frost penetration profile showing solid freeze with partial spring thaw 

and refreeze. 

Table 7 summarizes typical frost penetration characteristics observed for each SMP site. To 

describe frost penetration profile characteristics, frost depth was characterized as shallow, 

medium, or deep. A shallow frost depth was defined between 0 m and 0.6 m (0 ft and 1.97 ft); a 

medium frost depth was defined between 0.6 m and 0.9 m (1.97 ft and 2.95 ft); and a deep frost 

depth was defined for frost that penetrated 0.9 m (2.95 ft) or more. Since these definitions are 

subjective, the seasonal maximum frost depth is also reported in the table for each site. 

Furthermore, the depth of the top of the first unbound layer was different for each SMP site, 

which occasionally limited frost determination at shallow and medium depths where the first 

unbound layer was placed below the expected freeze depth. The information in table 7 could be 

used to infer the typical frost penetration characteristics for LTPP SMP sites. 
55

Table 7. Typical frost penetration profile characteristics for LTPP SMP sites. 

Frost profile description State 

or province 

State 

code 

SHRP 

ID 

#of 

years w/ 

data 

Fall 

(Sept 21–Dec 21) 

Winter 

(Dec 22–Mar 20) 

Spring 

(Mar 21–June 21) 

Arizona 4 1024 3 No Freeze* No Freeze* No Freeze* 

Colorado 8 1053 3 No Freeze 

Multiple Shallow FreezeThaw Cycles (up to 

0.37 m) 

No Freeze 

Connecticut 9 1803 4 No Freeze 

Shallow or Medium 

freeze-thaw (up to 

0.79 m) 

No Freeze 

Idaho 16 1010 3 

Possible Medium 

Freeze-Thaw 

Re-freeze 

(up to 0.66 m) 

Multiple Shallow or 

Medium Freeze-Thaw 

Cycles (up to 0.86 m) 

No Freeze 

Indiana 18 3002 2 Medium FreezeThaw 

Multiple Medium to Deep 

Freeze-Thaw Cycles (up 

to 1.21 m) 

No Freeze 

Kansas 20 4054 3 No Freeze 

Multiple Medium to Deep 

Freeze-Thaw Cycles (up 

to 1.06 m) 

No Freeze 

Maine 23 1026 4 

Shallow freeze-thaw 

re-freeze (up to 

0.55 m) 

Continuous Deep Freeze

(up to 1.82 m) 

Prolonged Deep Thaw

(up to 1.77 m) 

Manitoba 83 1801 9 

 Deep Freeze, 

possibly preceded by 

Shallow Freeze w/ 

Thaw (up to 1.72 m)

Continuous Deep Freeze

(up to 2.13 m)*** 

Deep Freeze, Shallow 

Thaw followed by Refreeze, Prolonged Deep 

Thaw (up to 2.13 m)*** 

Manitoba 83 3802 4 Deep Freeze 

(up to 1.31m) 

Continuous Deep Freeze

(up to 2.42 m)*** 

Deep Freeze, Shallow 

Thaw followed by Refreeze, Prolonged Deep 

Thaw (up to 2.42 m)*** 

Maryland 24 1634 4 No Freeze Shallow freeze-thaw 

(up to 0.44 m) No Freeze 

Massachusetts 25 1002 2 No Freeze 

Deep Freeze w/ Thaw, 

followed by Medium 

Freeze w/ Thaw 

(up to 1.02 m) 

No Freeze 

Minnesota 27 1018 4 

Medium to Deep 

Freeze 

(up to 1.83 m) 

Deep Freeze, Shallow 

Thaw followed by Refreeze (up to 2.18 m) 

Prolonged Deep Thaw

(up to 2.13 m) 

Minnesota 27 1028 3 

 Deep Freeze, 

possibly proceeded 

by Medium Freeze 

w/ Thaw. (up to 

1.83 m) 

Continuous Deep Freeze

(up to 2.39 m)*** 

Deep Freeze, Possible 

Shallow Thaw followed 

by Re-freeze, Prolonged 

Deep Thaw 

 (up to 2.39 m)*** 

Minnesota 27 4040 3 Deep Freeze 

 (up to 1.20 m) 

 Deep Freeze, Possible 

Shallow Thaw followed 

by Re-freeze 

(up to 2.32 m)*** 

 Prolonged Deep Thaw 

(up to 2.3 2m)*** 
56

Table 7. Typical frost penetration profile characteristics for LTPP SMP sites—continued. 

Frost profile description State 

or province 

State 

code 

SHRP 

ID 

#of 

years w/ 

data 

Fall 

(Sept 21–Dec 21) 

Winter 

(Dec 22–Mar 20) 

Spring 

(Mar 21–June 21) 

Minnesota 27 6251 8 Deep Freeze 

(up to 1.85 m) 

 Deep Freeze, Possible 

Shallow Thaw followed by 

Re-freeze (up to 2.31 m)*** 

 Prolonged Deep Thaw

(up to 2.31 m)*** 

Montana 30 0114 4 

Multiple 

Shallow/Medium 

Freeze-Thaw Cycles 

or Deep Freeze 

(up to 1.05 m) 

Multiple Medium/Deep 

Freeze-Thaw Cycles or 

Deep Freeze with Shallow 

Thaw and Re-freeze (up to 

1.26 m) 

Possible Deep Freeze 

and Thaw 

 (up to 0.95 m) 

Montana 30 8129 3 Medium Freeze 

(up to 0.83 m) 

Multiple Medium/Deep 

Freeze-Thaw Cycles 

(up to 1.08 m) 

No Freeze 

Nebraska 31 0114 6 

Medium Freeze w/ 

Thaw 

(up to 0.67 m) 

Multiple Medium/Deep 

Freeze-Thaw Cycles 

(up to 1.17 m) 

No Freeze 

Nebraska 31 3018 8 Possible Deep Freeze

(up to 1.2 2m) 

 Deep Freeze 

(up to 1.68 m) No Freeze 

Nevada 32 0101 5 No Freeze** No Freeze** No Freeze** 

Nevada 32 0204 1 No Freeze Multiple Shallow FreezeThaw Cycles (up to 0.61 m) No Freeze 

New 

Hampshire 33 1001 4 

Possible Shallow 

Freeze w/ Thaw 

(up to 0.33 m) 

Multiple Medium/Deep 

Freeze-Thaw Cycles or 

Single Deep Freeze 

(up to 1.39 m) 

Possible Thaw 

(up to 1.19 m) 

New Jersey 34 0504 3 No Freeze 

Multiple Shallow FreezeThaw Cycles 

(up to 0.41 m) 

No Freeze 

New Jersey 34 0505 3 No Freeze 

Multiple Shallow FreezeThaw Cycles 

(up to 0.46 m) 

No Freeze 

New Jersey 34 0506 2 No Freeze Medium Freeze-Thaw 

(up to 0.61m) No Freeze 

New Jersey 34 0507 3 No Freeze Shallow Freeze-Thaw (up 

to 0.46 m) No Freeze 

New Jersey 34 0902 3 No Freeze 

Multiple Shallow/Medium 

Freeze-Thaw Cycles (up to 

0.67 m) 

No Freeze 

New York 36 0801 7 

Multiple Shallow 

Freeze-Thaw Cycles

(up to 0.48 m) 

Multiple Shallow to Deep 

Freeze-Thaw Cycles or 

Single Deep Freeze 

(up to 0.99 m) 

Possible Multiple 

Shallow Freeze-Thaw 

Cycles (up to 0.28 m) 

New York 36 4018 4 No Freeze 

Multiple Shallow to Deep 

Freeze-Thaw Cycles or 

Single Deep Freeze (up to 

2.10 m)*** 

Possible Shallow 

Freeze-thaw or 

Prolonged Deep Thaw

(up to 2.10 m)*** 
57

Table 7. Typical frost penetration profile characteristics for LTPP SMP sites—continued. 

Frost profile description State 

or province 

State 

code 

SHRP 

ID 

#of 

years w/ 

data 

Fall 

(Sept 21–Dec 21) 

Winter 

(Dec 22–Mar 20) 

Spring 

(Mar 21–June 21) 

Ohio 39 0204 2 No Freeze Medium Freeze-Thaw 

(up to 0.71 m) No Freeze 

Ohio 39 0901 6 

Possible Medium 

Freeze 

(up to 0.57 m) 

Multiple (B) Shallow to 

Medium Freeze-Thaw 

Cycles (up to 0.78 m) 

No Freeze 

Ontario 87 1622 4 

Multiple Shallow 

Freeze-Thaw Cycles

(up to 0.42 m) 

Single Deep Freeze or 

Multiple Deep FreezeThaw Cycles 

(up to 1.74 m) 

Possible Shallow FreezeThaw, Prolonged Deep 

Thaw 

(up to 1.69 m) 

Pennsylvania 42 1606 8 

Multiple Shallow 

Freeze-Thaw Cycles

(up to 0.42 m) 

Multiple Shallow to 

Medium Freeze-Thaw 

Cycles (up to 0.77 m) 

No Freeze 

Quebec 89 3015 6 

Shallow to Medium 

Freeze-Thaw 

followed by Deep 

Freeze (up to 1.03 m)

 Deep Freeze, Shallow 

Thaw followed by Refreeze 

(up to 1.54 m) 

 Prolonged Deep Thaw, 

Possible Deep Freeze 

(up to 1.59 m) 

Saskatchewan 90 6405 3 

Shallow FreezeThaw, followed by 

Deep Freeze 

(up to 1.80 m) 

Continuous Deep Freeze

(up to 2.06m)*** 

Deep Freeze, Multiple 

Shallow Thaw & deep 

Re-freeze periods, 

Prolonged Deep Thaw 

(up to 2.06 m)*** 

South Dakota 46 0804 7 

Medium FreezeThaw, followed by 

Medium to Deep 

Freeze 

(up to 1.24 m) 

Deep Freeze, Possible 

Shallow Thaw followed 

by Re-freeze 

(up to 2.00 m) 

Deep Freeze, Possible 

Shallow Thaw followed 

by Re-freeze, Prolonged 

Deep Thaw 

(up to 1.95 m) 

South Dakota 46 9187 2 

Multiple shallow 

Freeze-Thaw Cycles 

followed by Medium 

to Deep Freeze 

(up to 1.02 m) 

Deep Freeze, Multiple 

Shallow Thaw followed 

by Re-freeze Cycles 

up to 1.83 m) 

Medium to Deep Freeze, 

Shallow Thaw & 

Re-freeze periods, 

Prolonged Thaw 

(up to 1.63 m) 

Utah 49 1001 3 Mid Depth to Deep 

Freeze (up to 2.02 m) No Freeze No Freeze 

Utah 49 3011 3 No Freeze Period 

Multiple Shallow to 

Medium Freeze-Thaw 

Cycles (up to 0.69 m) 

No Freeze 

Vermont 50 1002 8 

Multiple Shallow to 

Medium FreezeThaw Cycles 

(up to 0.64 m) 

Multiple Shallow to Deep 

freeze-thaw cycles, 

Possible Continuous 

Deep Freeze (up to 

1.50 m) 

Possible Deep Thaw 

(up to 1.40 m) 

Wyoming 56 1007 3 

Multiple Shallow 

Freeze-Thaw Cycles 

(up to 0.49 m) 

Multiple Shallow to Deep 

Freeze-Thaw Cycles (up 

to 1.00 m) 

No Freeze 

1 m = 3.28 ft 

* First interpreted depth at 0.38 m. 

** First interpreted depth at 0.51 m. 

*** Possibility of frost beyond the last interpreted depth. 
58

Comparison with Historical Non-LTPP Frost Data 

The computed maximum frost penetration depths were compared to the historical frost 

penetration values, as published in the climatic maps developed by NOAA(1) and Environment 

Canada.(2) Data from the historical maps were interpolated to the LTPP site locations. The results 

of the comparison are shown in figure 24. 

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0.00 0.50 1.00 1.50 2.00 2.50 3.00

LTPP Predicted Frost Depth, m

Historical Frost Depth, m 

US Sites

Canadian Sites

Line of Equality

AD-2*Standard Deviation

AD+2*Standard Deviation

Average Difference (AD)

1 m = 3.28 ft 

Figure 24. Graph. Comparison of frost penetration depths. 

The graph in figure 24 shows a good overall agreement between LTPP and historical maximum 

frost depth predictions. Some of the differences can be attributed to the fact that, while 

comparisons are provided for the same region, the historical values are not site-specific and that 

local variations are possible due to factors such as soil type, moisture content, altitude, and land 

development. In addition, for Canadian sites, some inaccuracies could result from estimation of 

frost depth from the freezing index data provided on the climatic map. For the three Canadian 

sites shown in the upper-right corner on the graph, LTPP frost penetration profiles indicate the 

possibility of frost beyond the last interpreted depth; however, the full frost depth cannot be 

established as no LTPP measurements are available at these lower depths. 

The extreme frost predictions for U.S. sites provided on the NOAA map are based on longer 

monitoring period than the LTPP frost predictions; hence, covering more seasons where extreme 

conditions could occur. Table 8 contains data used in the analysis. 
59

Table 8. Comparison of average frost depth for LTPP SMP sites.

STATE_CODE SHRP_ID Number of 

years analyzed 

LTPP maximum 

freeze depth, m 

Historic 

maximum freeze 

depth, m 

4 (AZ) 1024 4 * 0.250 

8 (CO) 1053 5 0.374 0.875 

9 (CT) 1803 5 0.794 1.167 

16 (ID) 1010 5 0.864 1.125 

18 (IN) 3002 4 1.213 0.875 

20 (KS) 4054 4 1.056 0.750 

23 (ME) 1026 5 1.819 1.792 

24 (MD) 1634 4 0.436 0.390 

25 (MA) 1002 2 1.017 1.240 

27 (MN) 1018 5 2.181*** 1.917 

27 (MN) 1028 5 2.386*** 2.042 

27 (MN) 4040 5 2.317*** 2.245 

27 (MN) 6251 10 2.308*** 2.250 

30 (MT) 0114 5 1.256 1.500 

30 (MT) 8129 6 1.082 1.500 

31 (NE) 0114 7 1.173 1.000 

31 (NE) 3018 9 1.679 1.031 

32 (NV) 0101 6 ** 0.600 

32 (NV) 0204 2 0.612 0.500 

33 (NH) 1001 5 1.394 1.531 

34 (NJ) 0504 3 0.406 0.750 

34 (NJ) 0505 3 0.458 0.750 

34 (NJ) 0506 3 0.608 0.750 

34 (NJ) 0507 3 0.455 0.750 

34 (NJ) 0902 3 0.668 0.750 

36 (NY) 0801 10 0.988 1.208 

36 (NY) 4018 5 2.102*** 1.208 

39 (OH) 0204 2 0.705 0.875 

39 (OH) 0901 6 0.776 0.875 

42 (PA) 1606 8 0.771 0.938 

46 (SD) 0804 9 1.998 1.667 

46 (SD) 9187 4 1.827 1.688 

49 (UT) 1001 5 2.019 0.625 

49 (UT) 3011 5 0.692 0.833 

50 (VT) 1002 10 1.498 1.625 

56 (WY) 1007 5 0.999 1.475 

83 (MB) 1801 11 2.13*** 2.670 

83 (MB) 3802 6 2.424*** 2.670 

87 (ON) 1622 5 1.743 1.710 

89 (QC) 3015 9 1.587 2.130 

90 (SK) 6405 6 2.058*** 2.790 

1 m = 3.28 ft 

* First interpreted depth at 0.38 m. 

** First interpreted depth at 0.51 m. 

*** Possibility of frost beyond the last interpreted depth. 
60

Comparison with Previous LTPP Frost Estimates 

When comparing the results of the current frost penetration data analysis to the previous results, 

the following improvements can be noted: 

• The new methodology resulted in the development of the complete frost penetration time 

histories for LTPP SMP I and II sites instead of previously reported freeze depth 

snapshots based on ER measurement dates. Frost penetration information for the 

previously analyzed periods increased over 8 times by the addition of results for the 

14,903 dates that previously were not included in the analyses. 

• Analysis of frost penetration histories led to the discovery of multiple freeze-thaw periods 

or of freeze-thaw periods during late fall or early spring characteristic for several LTPP 

sites, as discussed in this chapter. This information was not previously available. This 

new information is important for understanding and tracking of seasonal changes in 

pavement structural responses. 

• Analysis based on cross-referenced ER, moisture, and temperature data provided means 

far more informed and less subjective determinations of frost penetration for the LTPP 

sites compared to the previous estimates. ER and moisture data used in freeze state 

analysis are provided in the LTPP SMP_FREEZE_STATE table. Additionally, moisture 

data used in the analysis can be found in the LTPP SMP_TDR_MOISTURE table. 

• Major differences with the previous LTPP frost information are the availability of frost 

predictions for longer freeze seasons, the availability of data on fall and spring partial 

thaw and refreeze and multiple freeze-thaw cycles for some sites, and deeper frost 

estimates for some sites. 

LTPP FROST DATA TABLE DESCRIPTIONS 

As a result of this data analysis effort, two tables were created for inclusion in the LTPP 

database. The proposed computed parameter tables (CPT) are based on the existing LTPP frost 

CPT tables with changes and additions made as a result of the current frost penetration analysis 

study. 

These tables have the same names as in the previous LTPP database releases and are defined as 

follows: 

• SMP_FREEZE_STATE—Contains the interpreted soil freeze state (F-frozen, N-nofrozen, and T-transitional or partially frozen) based on the soil temperature and electrical 

resistivity data and supplemented by the soil moisture data trend analysis. Caution: Only 

a limited number of transitional states were determined based on the methodology used in 

LTPP Frost study. 

• SMP_FROST_PENETRATION—Contains the interpreted frozen layers and frost 

depth information, based on the interpreted freeze states (F-frozen and T-transitional or 

partially frozen) in table SMP_FREEZE_STATE. Caution: No frozen depths or layers 

were reported for depths and dates without sensor measurements. Use the 

SMP_FREEZE_STATE table to identify dates and depths that have no data. 
61

These new tables contain freeze state interpretations for all the available temperature and ER 

data collected during the SMP I and II experiments. As such, the intent of these tables is to 

replace the existing SMP_FREEZE_STATE and SMP_FROST_PENETRATION tables. 

Summaries of the information included in the CPT frost tables are provided in table 9 and table 10. 

Table 9. Summary of information included in the revised table SMP_FREEZE_STATE. 

Data element or parameter DESCRIPTION 

STATE code State code 

SHRP ID SHRP identification code 

SMP date Date corresponding to SMP data collection 

Interpretation depth number Depth number where freeze state is interpreted, increasing from top downward. 

Interpretation depth 

Middepth between electrodes used in the freeze state interpretation, measured for 

pavement surface; two consecutive electrodes are used in voltage and contact 

resistance measurements and four in resistivity. 

Interpreted freeze state 

Interpreted freeze state at the interpret depth: F-Freeze, N-No-freeze, T-Transitional 

(or partial freeze). 

Interpretation basis 

Code indicating the basis for freeze state interpretation: 

1. Freeze state based on temperature data using 0 o

C freezing isotherm, not forced. 

2. Freeze state determined by the analyst after reviewing the temperature, electrical 

resistivity, and moisture data trends. 

3. Temperature data is not available. Freeze state determined by the analyst from 

ER and moisture. 

Normalized resistivity 

Electrical resistivity of the soil at the measurement depth, relative to the extreme 

values measured at that depth. 

Normalized resistance 

Electrical resistance of the soil at the measurement depth, relative to the extreme 

values measured at that depth. 

Normalized voltage 

Voltage drop of the soil at the measurement depth, relative to the extreme values 

measured at that depth. 

Soil temperature 

Average soil temperature of the day, calculated at the interpretation depth. This 

could either be based on interpolation of measured values, or derived using EICM. 

Temperature source 

Source of the temperature data used in freeze state interpretation: (1) based on 

measured, (2) derived using EICM. 

Table 10. Summary of information included in the revised table 

SMP_FROST_PENETRATION. 

Filed name DESCRIPTION 

STATE code State code 

SHRP ID SHRP identification code 

SMP date Date corresponding to SMP data collection 

Frozen layer Code for interpreted frozen layer number. A value of zero indicates no frozen layers. 

Top depth number 

Serial number for the starting depth (top) of a frozen layer, increasing from pavement 

surface downward. 

Bottom depth number 

Serial number for the ending depth (bottom) of a frozen layer, increasing from pavement 

surface downward. 

Freeze from Starting (top) depth (meter) of a frozen layer, measured from the pavement surface. 

Freeze to Ending (bottom) depth (meter) of a frozen layer, measured from the pavement surface. 

63

CHAPTER 8. SUMMARY AND RECOMMENDATIONS 

SUMMARY 

A comprehensive review of the previous LTPP frost penetration analysis methodology and an 

assessment of frost depth estimates provided in the LTPP database were conducted, followed by 

recommendations for improvements. As a result of these recommendations, an enhanced 

methodology and the accompanying E-FROST research analysis tool were developed for 

determination of frost penetration in unbound pavement layers and subgrade soil for LTPP SMP 

sections. 

The enhanced methodology uses electrical resistivity, moisture, and soil temperature data 

collected for instrumented SMP sections to predict frost depth in unbound pavement layers. In 

addition, the EICM model was used to fill in the gaps in the measured soil temperature data. 

Using the enhanced analysis methodology and E-FROST, in-situ data were analyzed to 

determine freeze conditions and frost depths in the unbound pavement layers. The results of the 

frost penetration analysis for LTPP SMP sections were assembled in the LTPP computed 

parameter tables described in this report. 

The results presented in this report demonstrate how frost penetration beneath the pavement 

structure was predicted for LTPP SMP sites using a combined empirical and mechanistic 

technique. This technique utilizes data from LTPP in-situ measurements and thermodynamic 

modeling. 

Study findings stress the importance of using all three different types of in-situ measurements for 

accurate frost penetrations prediction: temperature, electrical resistivity, and moisture content. 

The EICM has proven useful for filling in the gaps of measured subsurface temperatures and for 

understanding the thermodynamic processes that occur in pavement layers. This information 

could help practitioners and researchers design seasonal monitoring field experiments and 

analyze field data to determine frost penetration under pavement layers. 

RECOMMENDATIONS FOR FUTURE RESEARCH 

Future E-FROST Development to Support M-E PDG Implementation 

The E-FROST research tool developed during this study could be very useful for analysis of 

seasonal changes in unbound pavement layers. In the future, this tool could become particularly 

useful for implementation of the M-E PDG, which emphasizes estimating seasonal changes in 

pavement layer moduli. 

We recommend that LTPP consider further development of this tool into an LTPP software 

product similar to the LTPP profile viewer software so that the pavement research and practicing 

community at large can have easy access to ER, temperature, and moisture data, as well as frost 

penetration profiles for LTPP SMP sites. In addition, data from FWD tests can be added to this 
64

software to relate changes in mechanistic properties of pavement layers and in pavement 

responses and to cross reference this information with frost penetration data. 

Future LTPP Data Analysis Study of Pavement Responses under FWD Loading during 

Freeze-Thaw Conditions 

During spring thaw, sunshine and warm air temperatures result in a top-down thawing of the 

pavement system. The water released by the melting ice can be trapped by deeper, still-frozen 

material, creating saturated or supersaturated conditions that weaken the pavement structure. The 

change in pavement strength could be observed by FWD measurements. 

The database tables developed under this study provide detailed information about the periods 

and the depth of freeze-thaw based on continuous temperature, ER, and moisture data analyzed. 

This information could be utilized to cross reference with and analyze FWD data collected 

during the thaw periods to capture the conditions of the supporting layers during the weakest 

period and to correlate these conditions with pavement responses. This task can be accomplished 

through mechanistic modeling of pavement responses under FWD loading based on the 

inventory, climatic, testing, and FWD data from the LTPP database. 

The result of the proposed study could contribute to understanding pavement deterioration, as 

triggered by seasonal changes in pavement layer moduli and could be utilized in the development 

of spring load restrictions. 

Future Development of In-Situ Frost Measurement Devices 

One of the challenges in LTPP frost penetration analysis was the interpretation of the data from 

ER measurement devices, as the following describes: 

• ER measurements were expected to be high during cold winter months when 

temperatures plunge below ground water freezing point. However, a number of ER 

readings during warm summer months (with temperatures high above 0 oC) were found 

to be as high as readings during cold winter months. These were unexpected trends. 

• LTPP collected in-situ data to evaluate three types of ER parameters: voltage, resistance, 

and resistivity. All three parameters are expected to follow a similar trend when soil goes 

through freeze and thaw cycles. However, it was not uncommon that the data showed 

opposite trends, or one of the trends would be nearly flat (indicating no changes in the 

soil freeze state). This inconsistency was unexpected. 

We highly recommend that LTPP promote the need for future research and development of 

in-situ frost measurement devices. Perhaps the next generation of such devices would have 

multifunctional sensors capable of monitoring temperature and moisture changes in the soil, in 

addition to electrical resistivity measurements, and use output of all three types of measurements 

to determining frost penetration. 
65

APPENDIX A. E-FROST USER’S GUIDE 

INTRODUCTION 

This guide is designed to familiarize new users with the E-FROST user interface and analysis 

options. The guide includes screen captures to help the user navigate through the software 

screens. 

E-FROST was designed to view time-series data from the in-situ measurements (ER, 

temperature, and moisture) used in frost penetration analysis, to generate and view frost 

penetration profiles, and to create frost penetration table documenting frost penetration depths 

for different dates for which in-situ measurements were taken. 

E-FROST INSTALLATION AND REMOVAL 

Complete the following steps to install E-FROST: 

1. Make sure that all other applications are closed and that the E-FROST installation 

CD-ROM has been inserted into the CD-ROM drive. 

2. From the Windows Start menu, select Run. 

3. In the Run dialog box, type “(CD drive):setup.exe,” where (CD drive) is the letter 

assigned to your CD-ROM drive. 

4. Follow the simple instructions in the installation program. When installation is completed, 

E-FROST program will be available from the Start menu. 

Complete the following steps to remove E-FROST: 

1. Click the Start button and choose the Settings option. 

2. Select Control Panel. 

3. From the Control Panel, double-click the Add/Remove Programs icon. 

4. Once within that dialog box, click the Install/Uninstall tab. 

5. Select E-FROST from the list of programs; then click the Add/Remove button. 

6. A final warning will ask if the user want to delete E-FROST from your computer. If this 

is the case, click Yes to remove all E-FROST files. 
66

STARTING E-FROST 

To start the program, click on E-FROST program name available from the Windows Start menu. 

Main Form 

When the E-FROST program is opened, a blank form with file menu and inactive tool buttons in 

the top left corner of the interface appears as shown figure 25. 

Figure 25. Screen capture. Opening screen in E-FROST. 

There are four tool buttons in E-FROST that help navigate between screens and provide different 

program functions. These tool buttons are located on the left side of the screen and are shown in 

figure 26. Each button’s function is described below the figure. 

Figure 26. Screen capture. Tool buttons. 
67

Select Sections

The Select Sections tool button allows the user to choose a site for analysis from a list that is 

linked to the database. 

Frost Graph

The Frost Graph tool button shows the frost graph after all missing temperature data and all 

temperature data between -1 o

C and 0 oC have been reviewed. The Frost Graph button will be 

inactive until all review has taken place and the frost graph has been finalized. 

Auto Frost

The Auto Frost tool button displays the frost graph with the original data set from the database 

before any review has taken place. 

Exit

The Exit tool button safely closes the E-FROST program. 

Load Database 

To run E-FROST analyses, the analysis database needs to be loaded first. The analysis database 

contains preprocessed temperature, ER, and moisture data for the SMP sites. To load a database, 

click File > Open Database, as shown in figure 27. A dialog box appears, prompting the user to 

open the database, as shown in figure 28. After locating and selecting the database, click the 

Open button located in the bottom right portion of the dialog box. 

Figure 27. Screen capture. Open database. 
68

Figure 28. Screen capture. Locate the database containing SMP data. 

Select Analysis Table 

Once the analysis database is uploaded, the E-FROST analysis table selection window will 

appear as shown in figure 29. 

Figure 29. Screen capture. Select data table for analysis. 

Select the table with the SMP site data, which is EFrostAll_QC and click OK to complete the 

database linking process. Once the database is connected to the program, the Select Sections and 

Exit user buttons will become active (figure 30). 
69

Figure 30. Screen capture. Frost linked to database with some tool buttons activated. 

Select SMP Site 

To select an SMP site for analysis, click the Select Sections tool button. A Section Selection 

window will appear containing a list of available SMP sections for analysis, as shown in 

figure 31. Click an SMP section name and then click OK. In the following example SMP site 

46-0804-1 was selected for analysis. The last digit in section ID represents LTPP construction 

number. 
70

Figure 31. Screen capture. SMP Section window. 

E-FROST ANALYSIS OPTIONS 

Frost Penetration Analysis Form 

A blank Frost Penetration Analysis form becomes visible once an SMP site is selected for 

analysis, as shown in figure 32. If more than 2 years of data (730 days) are available for the site, 

a warning message will appear to prompt the user to select a shorter time period. The MinDate 

and MaxDate fields on the form indicate the range of the available data. Above the minimum and 

maximum dates are the text boxes where the user can enter date ranges for review. The user can 

move between different years of frost data by using the buttons to the right (to progress forward) 

or the left (to move backward) of the default user date range. The user can also manually enter 

the beginning and ending dates of interest by typing over the values in User Date boxes and 

clicking the Plot New button. 
71

Figure 32. Screen capture. Blank Frost Penetration Analysis screen. 

Review Auto Generated Frost Profile 

Clicking on the Auto Frost tool button results in a generation of temperature-based frost 

penetration profile, as shown in figure 33. In this example, the automated frost penetration 

profile was generated for SMP Site 46-0804 for the winter season of 1999–2000. The profile 

consists of a grid with the horizontal axis displaying different SMP dates on a daily scale and the 

vertical axis displaying different analysis depth based on ER probe depths. Each cell is colorcoded to provide information about freeze state at a given date and at a given depth, as indicated 

in table 11. In addition, black “X”s are used to indicate data points missing temperature data. 
72

Figure 33. Chart. Automatically generated frost penetration profile at SMP site 46-0804 for 

the winter of 1999. 
73

Table 11. Freeze state and frost depth chart color coding. 

Color 

code Shape Assigned freeze state 

Subsurface 

temperature Analyst’s action 

Blue Rectangle Freeze T < -1 o

C

Assigned automatically; however, the analyst 

has an option to change the state to transitional 

(pink) or no-freeze (white) upon data review 

White Rectangle No freeze T > 0 o

C

Assigned automatically; however, the analyst 

has an option to change the state to transitional 

(pink) or freeze (blue) upon data review 

Light 

blue Triangle Review T < 0 o

C and 

T > -1 oC 

Assigned automatically; however, the action is 

required from analyst to manually review the 

data and change the state to freeze, no-freeze, or 

transitional 

Pink Diamond Transitional Near FR 

This color is assigned upon analyst review of all 

supporting data when it is not clear whether or 

not soil is frozen (partially frozen case) 

The AutoFrost algorithm automatically assigns the state of subsurface freeze condition at each 

electrode location using the following rules: 

• The 0 o

C freezing isotherm is used as the low boundary to define the no-freeze state. Nofreeze is automatically assigned to all points with a temperature above 0 o

C (white cells). 

• A value of -1 oC is used as an upper boundary to define the freeze state. Freeze is 

automatically assigned to all points with a temperature below -1 oC (blue cells). 

• All data that fall between two boundaries are flagged for manual review to determine the 

appropriate freeze state based on ER, temperature, and moisture trend analysis (light blue 

triangles). 

Review Time Series Data 

The light blue triangles on the AutoFrost profile graph indicate that the analyst must review the 

data and change the freeze state in the analysis table as appropriate. To aid in this analysis, 

E-FROST creates a time-series plot of ER, temperature, and moisture content changes. The plot 

is brought up to the screen once the analyst clicks on the light blue triangle cell. Similar plots can 

be brought up for review by clicking on any other cell on the frost penetration profile chart. 

To review temperature, ER, and moisture time-series trends for a selected measurement depth, 

(1) identify measurement depth on left vertical axis in the frost penetration profile plot, then 

(2) click on any cell in the automated frost penetration graph for a selected depth value depth to 

bring up the time series graph (see the example shown in figure 34). Use the “<” and “>” buttons 

next to the No. label on the form to review the time series at different depths, or select the 

desired depth from the dropdown menu. 
74

Figure 34. Chart. Time series plot for SMP site 46-0804 for the winter of 1999 at analysis 

depth = 0.55 m (1.8 ft). 

Review Revised Frost Penetration Profile 

Upon completion of the trend analysis and assignment of freezing conditions, an updated frost 

penetration plot can be reviewed by clicking on the Frost Graph tool button, as shown in 

figure 35. 
75

Figure 35. Chart. Final frost penetration profile for SMP site 46-0804 for the winter of 

1999. 

View Previously Processed Data 

After the analysis of all sites is complete and all frost penetration profiles are finalized, the user 

can select any previously analyzed SMP site and view the frost penetration profiles at that site. 

To view previously processed data, click the Select Sections tool button and select an SMP site. 

Next, click the Frost Graph tool button to see the final frost penetration profile of the selected 

site. From the Frost Graph screen, the user can click on any cell to view the time series graph at 

selected depth. To view automatically generated frost penetration profile, click the Auto Frost 

tool button. To exit the program, click Exit on the tool bar. 

GENERATE FROST PENETRATION TABLE 

To generate the frost penetration table FrostPen, click File > Create Frost Penetration Table, as 

shown in figure 36. 
76

Figure 36. Screen capture. Create Frost Penetration Table option. 
77

APPENDIX B. EICM MODELING INPUTS 

Table 12. EICM inputs. 

Site_ID 16_1010 23_1026 27-4040 27_6251 31_3018 34_0506 34_0902 36_0801 39_0901 46_0804 46Start Year 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996 1Start Month Sept. Sept. Sept. Sept. Sept. Sept. Sept. Sept. Sept. Sept. SLength Analysis Period (day) 3195 3287 3287 3287 3287 3287 3287 3287 3287 3287 3Time Increment Output (hour) 1 1 1 1 1 1 1 1 1 1 Time Increment Calculation (hour) 

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Latitude (degrees. minutes ) 

43.4 44.34 47.18 47.27 40.4 40.17 40.43 43.21 40.38 45.56 4

Longitude (degrees. minutes) 

-112.07 -70.17 -93.43 -94.54 -99.2 -74.51 -74.1 -77.55 -83.07 -100.25 -1

Short-wave absorptivity 0.8 0.75 0.8 0.9 0.8 0.8 0.8 0.95 0.8 0.8 Upper limit freezing (°F) 32 32 32 32 32 32 32 32 32 32 Lower limit freezing (°F) 30.2 30.2 30.2 30.2 30.2 30.2 30.2 30.2 30.2 30.2 3Pavement Layer 1Material Asphalt Asphalt PCC Asphalt PCC Asphalt Asphalt Asphalt Asphalt Asphalt AsThickness (inches) 5.2 9.8 8.1 9 11.9 9.7 12.4 4.9 19.7 7.2 Number of elements 5 10 8 9 12 10 12 5 20 7 Thermal Conductivity (BTU/hr-ft-°F) 

0.67 0.67 1 0.67 1 0.67 0.67 1.5 1.5 0.67 0

Heat capacity (BTU/lb-°F) 0.22 0.22 0.2 0.22 0.2 0.22 0.22 0.22 0.22 0.22 0Unit Weight (pcf) 148 148 150 148 150 148 148 148 148 148 
78

Table 12. EICM inputs—continued. 

Site_ID 16_1010 23_1026 27-4040 27_6251 31_3018 34_0506 34_0902 36_0801 39_0901 46_0804 46Pavement Layer 2Material Asphalt Thickness (inches) 5.7 Number of elements 6 Thermal Conductivity (BTU/hr-ft-°F) 

0.67 

Heat Capacity (BTU/lb-°F) 

0.22 

Unit Weight (pcf) 148 Soil Layer 1Material A-1-a A-1-a A-1-a A-1-a A-1-a A-1-a A-1-a A-1-a A-1-a A-1-a AThickness (inches) 12 17.6 6 10.2 5.6 10 5 8.4 6 12 Number of Elements 12 17 6 10 5 10 5 9 6 12 Porosity 0.25 0.25 0.25 0.3 0.25 0.25 0.25 0.25 0.25 0.25 Saturated permeability (ft/hr) 

0.0583 0.0583 0.0583 0.0583 0.0583 0.0583 0.0583 0.0583 0.0583 0.0472 0

Dry unit weight (pcf) 127 127 127 127 127 127 127 127 127 127 Dry thermal conductivity (BTU/hr-ft-°F) 

0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 

Dry heat capacity (BTU/ft3-°F) 

0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 
79

Table 12. EICM inputs—continued. 

Site_ID 16_1010 23_1026 27-4040 27_6251 31_3018 34_0506 34_0902 36_0801 39_0901 46_0804 46Initial VMC (%) 15.26 15.26 15.26 2 15.26 15.26 15.26 15.26 15.26 15.26 Fredlund–af 7.2555 7.2555 7.2555 7.2555 7.2555 7.2555 7.2555 7.2555 7.2555 7.05034 6.Fredlund–bf 1.234 1.234 1.234 1.234 1.234 1.234 1.234 1.234 1.234 1.28391 1.Fredlund–cf 0.83152 0.83152 0.83152 0.83152 0.83152 0.83152 0.83152 0.83152 0.83152 0.83784 0.Fredlund–hr 117.4 117.4 117.4 117.4 117.4 117.4 117.4 117.4 117.4 152.2 1Plasticity Index (PI) 1 1 1 1 1 1 1 1 1 152.2 D60 (mm) 10.82 10.82 10.82 10.82 10.82 10.82 10.82 10.82 10.82 10.82 1Passing #4 (%) 44.7 44.7 44.7 44.7 44.7 44.7 44.7 44.7 44.7 44.7 Passing #200 (%) 8.7 8.7 8.7 8.7 8.7 8.7 8.7 8.7 8.7 8.7 Soil Layer 2Material A-2-4 A-2-4 A-2-7 A-2-4 A-2-4 A-2-4 A-1-a A-2-4 A-7-5 A-7-5 Thickness (inches) 300 300 300 300 300 300 5 300 12 300 Number of Elements 150 150 150 150 150 150 5 150 12 150 Porosity 0.27 0.29 0.14 0.29 0.26 0.27 0.25 0.27 0.39 0.38 Saturated permeability (ft/hr) 

0.0004.39 0.000792 1.55E-06 1 0.00364 0.000439 0.04 0.000439 4.28E-06 3.29E-06 1.9

Dry unit weight (pcf) 123.4 120.2 120.8 119.8 124 123.4 127 123.4 102 104.8 1Dry thermal conductivity (BTU/hr-ft-°F) 

0.8 0.8 0.8 3 0.8 0.8 0.8 0.8 0.8 0.8 

Dry heat capacity (BTU/ft3-°F) 

0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 

Initial VMC (%) 18.39 19.65 12 19.77 17.88 18.39 15.26 18.39 32.69 31.24 3Fredlund–af 9.28522 10.2125 76.5824 5.74545 5.85556 9.28522 7.2555 9.28522 125.312 117.641 10
80

Table 12. EICM inputs—continued. 

Site_ID 16_1010 23_1026 27-4040 27_6251 31_3018 34_0506 34_0902 36_0801 39_0901 46_0804 46Fredlund–bf 0.643865 0.3 0.926038 1.95497 1.8823 0.643865 1.234 0.643865 0.57723 0.621817 0.Fredlund– cf 3.09113 3.72724 0.42491 0.71916 1.08956 3.09113 0.83152 3.09113 0.10524 0.15556 0.Fredlund–hr 189.6 100 500 100 110 189.6 117.4 189.6 500 500 Plasticity Index (PI) 2 0 14 0 1 2 1 2 24 19 D60 (mm) 0.3216 0.3216 5.73 2 0.3477 0.3216 10.82 0.3216 0.02798 0.02798 0.Passing #4 (%) 87.2 87.2 55.4 87.2 87.2 87.2 44.7 87.2 94 94 Passing #200 (%) 22.4 22.4 27.4 10 5 22.4 8.7 22.4 70.5 70.5 Soil Layer 3Material A-2-4 A-7-5 Thickness (inches) 300 300 Number of Elements 150 150 Porosity 0.27 0.39 Saturated permeability (ft/hr) 

 0.000439 4.28E-06 

Dry unit weight (pcf) 123.4 102 Dry thermal conductivity (BTU/hr-ft- °F) 

 0.8 0.8 

Dry heat capacity (BTU/ft3-°F) 

 0.22 0.22 

Initial VMC (%) 18.39 32.69 Fredlund–af 9.28522 125.312 Fredlund–bf 0.643865 0.57723 Fredlund–cf 3.09113 0.105242 
81

Table 12. EICM inputs—continued. 

Site_ID 16_1010 23_1026 27-4040 27_6251 31_3018 34_0506 34_0902 36_0801 39_0901 46_0804 46Fredlund–hr 189.6 500 Plasticity Index (PI) 2 24 D60 (mm) 0.3216 0.02798 Passing #4 (%) 87.2 94 Passing #200 (%) 22.4 70.5 Deep ground temperature (°F) 

51 48.1 40.88 40.55 51.43 53.74 55.25 47.85 54 44.87 4

1 inch = 25.4 mm 32 °F = 0 °C (Deduct 32, then multiply by 5, then divide by 9). Note: For soil layers, The Fredlund Soil Water Characteristic Curve model is used to relate soil suction to water content. Fredlund para

of psi. Parameters of bf and cf are unitless. Parameter af is a measure of air entry, the soil suction at which the soil becomes less than 10

Parameters bf and cf determine the rate of change of moisture content versus suction as it transitions from saturated to unsaturated (no f

slope of the curve after free water is removed. 

83

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HRDI-13/11-08(1m)E Recycled

Recyclable