CRREL REPORT 96-14

Material Testing and Initial

Pavement Design Modeling

Minnesota Road Research Project

Susan R. Bigl and Richard L. Berg September 1996
Abstract: Between January 1990 and December 1994,

a study verified and applied a Corps of Engineersdeveloped mechanistic design and evaluation method

for pavements in seasonal frost areas as part of a

Construction Productivity Advancement Research

(CPAR) project between the Minnesota Department of

Transportation (Mn/DOT) and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL).

The study involved four primary components. Mn/DOT

constructed a full scale pavement test facility adjacent

to Interstate 94, referred to as the Minnesota Road Research Project (Mn/ROAD). CRREL performed extensive laboratory tests on the base and subgrade materials from Mn/ROAD to characterize them and their

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Cover: Aerial view of Minnesota Road Research Project (Mn/ROAD).

behavior under seasonal frost conditions. Laboratory tests provided the input parameters necessary for

the study’s third component, modeling with the CRREL

Mechanistic Pavement Design and Evaluation Procedure. The modeling effort was conducted in three

phases, which investigated the effects of freeze season

characteristics, water table position, asphalt model

and subgrade characteristics on the predicted performance of selected Mn/ROAD test sections. Delays in

construction on the Mn/ROAD facility prevented the

completion of the study’s fourth component—using

performance data from Mn/ROAD to validate the mechanistic pavement design and evaluation procedure. The

report details results from the other three components.
CRREL Report 96-14

Material Testing and Initial

Pavement Design Modeling

Minnesota Road Research Project

Susan R. Bigl and Richard L. Berg September 1996

Prepared for

MINNESOTA DEPARTMENT OF TRANSPORTATION

Approved for public release; distribution is unlimited.

US Army Corps


of Engineers

Cold Regions Research &


Engineering Laboratory
PREFACE

This report was prepared by Susan R. Bigl, Research Physical Scientist, Civil

and Geotechnical Research Division, Research and Engineering Directorate, U.S.

Army Cold Regions Research and Engineering Laboratory (CRREL), Hanover,

New Hampshire, and by Dr. Richard L. Berg, formerly a Research Civil Engineer at

CRREL.

This work was funded through Agreement 64632, Task Order 1 with the Minnesota Department of Transportation (Mn/DOT) and a Construction Productivity

Advancement Research (CPAR) project between Mn/DOT and CRREL.

The authors thank George Cochran of the Minnesota Road Research Project and

Dr. Vincent Janoo of CRREL for technically reviewing the manuscript of this

report.

The soils testing information reported here is the result of work done by a team of

personnel who work in the Soils Laboratory at CRREL. Their efforts are greatly

appreciated. Jeffrey Stark, Soils Laboratory Manager, coordinated and initiated the

work, and designed some new devices to aid molding and processing frozen samples.

Rosanne Stoops conducted the grain-size analysis, Atterberg limits, specific gravity,

and organic content tests. Richard Roberts conducted the frost susceptibility tests

and some of the compaction tests. Charles Smith determined the remaining compaction curves. Jonathan Ingersoll conducted the hydraulic property tests—moisture

retention and hydraulic conductivity. Dr. Patrick Black determined the unfrozen

moisture content characteristics. The resilient modulus testing was done by a team

of CRREL personnel whose efforts we greatly appreciate. Arthur Peacock, Brian

Charest, and David Carbee were all involved in molding, freezing, and milling the

specimens. Glenn Durell and Dale Bull conducted the resilient modulus testing.

Brian Charest characterized the water content and density subsequent to resilient

modulus testing.

The contents of this report are not to be used for advertising or promotional

purposes. Citation of brand names does not constitute an official endorsement or

approval of the use of such commercial products.

ii
CONTENTS

Page

Preface ............................................................................................................ ii

Executive summary ........................................................................................ vi

Introduction .................................................................................................... 1

Model description ........................................................................................... 3

FROST ....................................................................................................... 4

TRANSFORM ........................................................................................... 4

NELAPAV ................................................................................................. 5

CUMDAM ................................................................................................. 6

Material testing ............................................................................................... 8

Physical characteristics .............................................................................. 11

Hydraulic properties ................................................................................... 11

Frost susceptibility ..................................................................................... 13

Unfrozen water content .............................................................................. 16

Resilient modulus ....................................................................................... 17

Performance predictions ................................................................................. 26

Phase 1 ....................................................................................................... 26

Phase 2A..................................................................................................... 34

Phase 2B ..................................................................................................... 36

Phase 3 ....................................................................................................... 37

Discussion/recommendations ......................................................................... 42

Conclusions .................................................................................................... 44

Literature cited ................................................................................................ 44

Abstract........................................................................................................... 46

ILLUSTRATIONS

Figure

1. Location of Mn/ROAD ........................................................................ 1

2. Schematic layout of Mn/ROAD .......................................................... 1

3. Mainline asphalt test sections ............................................................... 2

4. Grain size distribution in tested specimens of Mn/ROAD base

materials ........................................................................................... 2

5. Mainline concrete test sections ............................................................. 3

6. Flow chart of mechanistic design procedure ........................................ 4

7. Comparison of asphalt moduli computed with Schmidt and

Ullidtz models .................................................................................. 5

iii
Page

8. Stress dependence of resilient modulus in station 1206 clay subgrade

material ............................................................................................. 6

9. Comparison of grain size distribution of substitute materials and

specifications for equivalent Mn/ROAD bases ................................ 11

10. Grain size distribution in the subgrade materials ................................. 12

11. Moisture retention test results ............................................................... 14

12. Tension vs. hydraulic conductivity curves ........................................... 15

13. Temperature vs. gravimetric unfrozen water content curves................ 17

14. Frozen and unfrozen modulus data compared with calculated

moduli from predictive equations..................................................... 23

15. Resilient modulus vs. degree of saturation of never-frozen 1206

subgrade material illustrating the effect of dry density .................... 25

16. Resilient modulus vs. degree of saturation illustrating effect of

stress parameter ................................................................................ 25

17. Distribution of seasonal freezing index with time at Buffalo,

Minnesota ......................................................................................... 26

18. Pavement structure of Mn/ROAD test sections simulated ................... 27

19. Example output from FROST for Mn/ROAD test section ML5-F4

with a 2-m (6-ft ) water table............................................................ 30

20. Seed moduli output by TRANSFORM for Mn/ROAD test section

ML5-F4 with a 2-m (6-ft ) water table ............................................. 30

21. Deflection and strain calculated by NELAPAV for Mn/ROAD test

section ML5-F4 with a 2-m (6-ft ) water table................................. 31

 22. Cumulative damage for case f4w6 with “normal” subgrade ................ 33

 23. Cumulative damage for case f2w9 ....................................................... 33

 24. Cumulative damage for case f4w6 with “1232” subgrade ................... 33

 25. Cumulative damage for case r5w6 ....................................................... 34

26. Frost and thaw penetrations predicted by FROST for freeze

seasons in Phase 2B environmental sensitivity study ...................... 36

 27. Distribution of freezing indices and water table depths in 21-yr

Phase 3 series.................................................................................... 38

 28. Predicted results from simulation of full depth section during

freeze season 1983–1984, starting on 1 October.............................. 40

 29. Predicted results from simulation of full depth section during

freeze season 1985–1986, starting on 1 October.............................. 40

30. Distribution of accumulative damage during seasons .......................... 42

TABLES

Table

1. Results of regression analyses—test soils from Mn/ROAD................. 6

2. Models currently available in NELAPAV............................................ 8

3. Cumulative damage models used ......................................................... 9

4. Laboratory tests performed on Mn/ROAD materials ........................... 10

iv
5. Physical properties of Mn/ ROAD materials ........................................ 12

6. Compaction test results—Mn/ROAD materials ................................... 13

7. Coefficients for hydraulic properties in the form of Gardner’s

equations........................................................................................... 13

8. Frost susceptibility test results .............................................................. 16

9. Constants for unfrozen moisture content equations .............................. 16

10. Resilient modulus samples tested ......................................................... 19

11. Stress conditions of resilient modulus tests in current study ................ 21

12. Stress conditions of resilient modulus tests—previous study............... 21

13. Test sections simulated, and maximum frost heave/frost penetration predictions ................................................................................. 27

14. Material parameters input to FROST for Mn/ROAD test section

simulations........................................................................................ 28

15. Predicted applications to failure from Phase 1 simulation series of

 flexible pavement tests sections ...................................................... 32

16. Applications to failure from simulations of rigid test sections ............. 33

17. Predicted applications to failure from simulations of flexible

test sections run in Phase 2A series .................................................. 35

18. Performance predictions for F3 test section with water table at

2.4 m (8 ft ) ....................................................................................... 37

19. Results of 21-yr freezing index/water table series ................................ 38

20. Midfreeze season thaw index summations ........................................... 41

21. Average percentage of total yearly damage accumulated during

four seasons ...................................................................................... 41

v
EXECUTIVE SUMMARY

This report describes a study to verify and apply a mechanistic design and

evaluation method for pavements in seasonal frost areas that was conducted as a

Construction Productivity Advancement Research (CPAR) project between the

Minnesota Department of Transportation (Mn/DOT) and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL). The study involved four

components.

1. Mn/DOT constructed a full-scale pavement test facility adjacent to Interstate

94, referred to as the Minnesota Road Research Project (Mn/ROAD). The project

includes 23 test cells, which are composed of fourteen asphalt- and nine concretesurfaced sections. Each cell is 153 m (500 ft) long with transitions of various lengths

separating the individual cells. The cells were designed to have a service life of

either five or ten years. The test road was opened to traffic in August of 1994.

2. CRREL performed extensive laboratory tests on the base and subgrade materials from the Mn/ROAD test cells to characterize them and their behavior under

seasonal frost conditions and to provide input necessary for modeling the materials.

Tests included those of physical properties (grain-size distribution, specific gravity,

Atterberg limits, organic content, hydraulic properties, and compaction) as well as

tests related to freeze/thaw processes (frost susceptibility and unfrozen moisture

content) (Bigl and Berg 1996a). Resilient modulus tests with a matrix of applied

confining and deviator stresses were also conducted on the Mn/ROAD materials at

several temperatures below freezing and at various moisture and density conditions

(Berg et al. 1996). All materials exhibited a two to three order of magnitude

increase in resilient modulus at subfreezing temperatures of –2°C and lower. When

unfrozen, the resilient modulus of all of the materials was stress dependent and also

increased as the degree of saturation decreased. For the materials where a variety of

densities were tested, modulus was also dependent on density.

3. Laboratory tests provided the input parameters necessary for the third component of the study, modeling with the CRREL Mechanistic Pavement Design and

Evaluation Procedure. It consists of four computer programs that compute soil and

pavement moisture and temperature conditions (FROST), resilient modulus and

Poisson’s ratio (TRANSFORM), stresses and strains in the pavement system

(NELAPAV), and cumulative damage (CUMDAM). Damage predictions are based

on equations that employ horizontal strain at the base of an asphalt layer, vertical

strain at the top of the subgrade, or horizontal stress at the base of a concrete layer.

The procedure was used to predict pavement performance of some of the Mn/

ROAD test sections. The modeling effort was conducted in three phases, which

investigated the effects of freeze season characteristics, water table position, asphalt

model and subgrade characteristics on the predicted performance of some Mn/

ROAD sections (Bigl and Berg 1996b).

The procedure predicted significantly different performance by the different test

sections and highly variable results depending on the performance model applied.

The simulated performance of the test sections was also greatly affected by the

subgrade conditions, e.g., density, soil moisture and water table depth. In general,

predictions for the full-depth asphalt sections indicate that they will not fail due to

vi
cracking, but two of the three criteria for subgrade rutting indicate failure prior to

the 5- or 10-yr design life of the sections. Conventional sections are predicted not to

fail due to subgrade rutting; however, sections including the more frost-susceptible

bases in their design are predicted to fail because of asphalt cracking relatively early

in their design life. Sections with non-frost-susceptible bases are predicted to fail

near the end of their design life.

4. The planned fourth component of the study, using performance data from Mn/

ROAD to validate the Mechanistic Pavement Design and Evaluation Procedure,

was not accomplished because construction and trafficking of the Mn/ROAD facility were much delayed from the originally intended schedule.

vii
Material Testing and Initial Pavement Design Modeling

Minnesota Road Research Project

SUSAN R. BIGL AND RICHARD L. BERG

Figure 1. Location of Mn/ROAD.

Figure 2. Schematic layout of Mn/ROAD.

Mn/ROAD. Figure 2 illustrates the layout of the

test sections. Only the new westbound I-94 test

cells were investigated as part of the CPAR project.

The mainline section of Mn/ROAD includes a 3-

mile (4.8-km), two-lane roadway over which westbound I-94 traffic is diverted. The project includes

23 test cells, which are composed of fourteen asphalt and nine concrete surfaced sections. Each

cell is 153 m (500 ft) long with transitions of

various lengths separating the individual cells. The

cells were designed to have a service life of either

five or ten years. A midpoint cross-over will allow

traffic to continue using the 10-year cells once the

5-year cells have failed.

INTRODUCTION

Between January 1990 and December 1994,

studies to verify and apply a Corps of Engineerdeveloped mechanistic design and evaluation

method for pavements in seasonal frost areas were

conducted as a Construction Productivity Advancement Research (CPAR) project between the Minnesota Department of Transportation (Mn/DOT)

and the U.S. Army Cold Regions Research and

Engineering Laboratory (CRREL). The project involved four components:

1. Laboratory tests on the pavement materials.

2. Predicting performance with the CRREL

Mechanistic Pavement Design Procedure.

3. Construction of the Minnesota Road Research

Project (Mn/ROAD).

4. Using performance data from Mn/ROAD to

validate the Mechanistic Pavement Design

and Evaluation Procedure.

Because construction and trafficking of the Mn/

ROAD facility was much delayed from the originally planned schedule, the model validation effort was not accomplished.

Mn/ROAD is located on Interstate 94 near

Monticello, Minnesota, approximately 40 miles

(64.4 km) northwest of the twin cities of Minneapolis/St. Paul. Figure 1 shows the location of
a. 5-yr design life. b. 10-yr design life.

Figure 3. Mainline asphalt test sections. In the figure, beneath the base materials, High/

Low refer to the asphalt penetration viscosity number; design compactive effort is indicated

by VH—very high, H—high, M—medium, and L—low.

Figure 4. Grain size distribution in tested specimens of Mn/ROAD

base materials.

Parameters included in the designs of the asphalt test sections are the thickness and characteristics of the asphalt surface and the presence, thickness and quality of base materials (Fig. 3). The

asphalt cement used was an 85/100 pen grade asphalt. The asphalt design included either of two

temperature susceptibilities: one with a low penetration viscosity number (PVN) is characteristically more compliant and the other with a high

PVN is more brittle. The design compactive effort

applied to the asphalt also varies from low to very

high, which resulted in varying asphalt cement

contents in the field.

The four granular base materials included in

the test sections were specified and manufactured

to include a range in frost susceptibility (Fig. 4).

The class 6 special is a relatively clean, non-frostsusceptible gravel with sand; the special bases,

100

80

60

40

20

0

Percent Finer by Weight

10 1.0 0.1 0.01 0.001

Grain Size (mm)

100

Gravel Sand

Silt or Clay C'rse Fine C'rse Medium Fine

4 10 40 200

U.S. Std. Sieve Size and No. Hydrometer

3 3/4

Class 3 Special 4

5

6

F-1 F-2 F-3 F-4 F-14 F-15 F-16 F-17 F-18 F-19 F-20 F-21 F-22 F-23

0

10

20

30

40

50

0

20

40

60

80

100

120

(cm) (in.)

Depth Below Pavement Surface

Low

H

Low

L Low

M

Low

VH High

VH

Low

H

Low

H

High

M

High

M

High

H

High

VH

Low

L

Low

H

Low

H

Asphalt Concrete Class 3 Special

Class 4 Special Class 5 Special Class 6 Special

Open Graded Base

5 Year Design Life 10 Year Design Life

2
class 5, class 4 and class 3, are all well-graded sands

with increasing amounts of finer size particles and

associated increasing frost susceptibility. Also included in one of the 10-yr sections is a porous

asphalt-stabilized open graded base. The subgrade

beneath all test sections is a sandy lean clay. Bigl

and Berg (1996a) and Berg et al. (1996) detail

properties of the various materials at the site.

In the concrete-surfaced test sections, parameters varied are the thickness of the concrete, panel

width and length, dowel diameter, thickness and

quality of underlying base materials, and presence of open-graded bases (Fig. 5). The concrete

paving surface is plain jointed concrete in all sections, with a constant thickness in the 5-yr and 10-

yr sections. Panel lengths vary from 4.6 to 7.3 m

(15 to 24 ft); panel widths are 7.3, 8.2, or 12.2 m

(24, 27 or 40 ft). Dowel diameters are 2.5, 3.2 or

3.8 cm (1, 1.25, or 1.5 in.). Base materials employed in the concrete sections are similar to those

used in the asphalt sections. The subgrade is also

a lean clay.

A number of different instrumentation types

were installed at Mn/ROAD to measure the environmental conditions at the test sections, the traffic loadings, and the engineering behavior of the

materials.

Stage 1 construction took place June 1990

through spring 1992. This effort, which included

swamp excavation and backfill, and grading of

the test roadway to the top of the base materials,

required moving about 765,000 m3 (1,000,000 yd3)

of material. Completion was significantly delayed

due to extremely wet weather during the 1990 and

1991 construction seasons.

Stage 2 construction, which included paving

and installation of instrumentation, occurred during the 1992 and 1993 construction seasons. An

extensive period of sensor calibration, nondestructive pavement testing and collection of baseline

data took place during winter 1993 and spring

1994. The test road was opened to traffic in August of 1994.

Three other reports have been prepared as part

of this study (Bigl and Berg 1996a,b and Berg et

al. 1996). This report summarizes the results of

the other three. If additional details are desired or

needed, the other reports should be used.

MODEL DESCRIPTION

A mechanistic pavement design procedure is

being developed for use in seasonal frost areas

and considers seasonal variations in pavement

strength such as:

a. 5-yr design life. b. 10-yr design life.

Figure 5. Mainline concrete test sections. In the figure, p refers

to panel length (ft), d—dowel diameter (in.), w—panel width (ft).

Supplemental steel rebar is included in the concrete of 5-year

section R-8.

R-10 R-11 R-12 R-13

5 Year Design Life

R-5 R-6 R-7 R-8 R-9

10 Year Design Life

0

10

20

30

40

50

0

20

40

60

80

100

120

(cm) (in.)

Depth Below Pavement Surface

Class 4 Special

Portland Cement

Concrete

Class 5 Special

Class 3 Special

Class 6 Special

p = 20

d = 1.00

w = 27

15

1.00

27

20

1.00

27

20

1.25

24

24

1.25

24

15

1.25

24

20

1.50

24

Open Graded Base

(with drain)

15

1.00

40

15

1.00

40

3
1. Large increases in base and subgrade

strengths when frozen.

2. Loss of base and subgrade strengths during

thawing periods when excess water weakens

the layers.

3. Changes in asphaltic concrete strength during

the year.

The mechanistic design procedure consists of four

computer programs FROST, TRANSFORM,

NELAPAV, and CUMDAM (Fig. 6). FROST predicts the amount of frost heave and thaw settlement of the pavement structure and conditions

throughout the depth of the structure (temperature, water content, pore water pressure, ice content, density) at a given time increment. TRANSFORM uses the output from FROST as input and

divides the pavement structure into “layers” based

on moisture or temperature conditions. Each layer

is then assigned a resilient modulus, Poisson’s ratio and density value. NELAPAV, a nonlinear layered elastic program, calculates stresses, strains

and deflections at specified locations within a pavement profile when a load is applied to the surface.

CUMDAM calculates the incremental and cumulative damage the pavement undergoes using several available damage models. The behavior is normally modeled for a one-year period, with output

on a daily basis. By assuming that the results from

a single year will be repeated annually, the number of applications to failure is estimated.

FROST

FROST is a one-dimensional coupled heat flow

and moisture flow model that predicts the amount

of frost heave and thaw settlement of a pavement

or soil profile with time. It also calculates temperatures, pore pressures, water contents, ice contents, and densities through the depth of the profile at each time increment. FROST was originally

developed in a cooperative study funded by the

Corps of Engineers, the Federal Highway Administration, and the Federal Aviation Administration

(Berg et al. 1980). Additional details are given in

Guymon et al. (1993) and in Bigl and Berg (1996 b).

TRANSFORM

TRANSFORM was developed at CRREL by

Chamberlain et al. (in prep.) and was modified extensively for this study. TRANSFORM uses daily

output files from FROST as input and produces

layered pavement systems where each layer is assigned a resilient modulus (Mr), Poisson’s ratio,

Figure 6. Flow chart of mechanistic design procedure.

Input

• Geometry

• Initial Conditions

• Boundary Conditions

• Material Characteristics

FROST

Output/Input

• Heave

• Frost/thaw Penetration

Additional Material

Characteristics TRANSFORM

Nodal Temperature,

Moisture & Density

• Load Configuration

• Evaluation Locations NELAPAV

Strains; Stresses

• Traffic

• PCC Parameters CUMDAM

• Physical and Elastic

 Properties of Sublayers

• Geometry

Cumulative

Damage

4
density and thickness. First, a modulus is calculated for each element; then, elements with moduli

not differing by more than 20% are combined in a

single layer. Output files from TRANSFORM are

in the format to be used as input files to NELAPAV.

Inputs to and outputs from the TRANSFORM program are discussed in more detail in Bigl and

Berg (1996b). The basic equations used to calculate resilient moduli are given here (Table 1).

Moduli of surface paving materials were calculated as follows. PCC (portland cement concrete)

had the Mr

 set at a constant value of 3.4 × 107 kPa

(5,000,000 lb/in.2). In the initial two simulation

series, the resilient modulus, Mr

 of asphalt concrete layers were calculated by the Schmidt (1975)

equation, which predicted very low summer values. In a third series of simulations, a second model

was used for predicting asphalt moduli when the

temperature was above 1°C (Ullidtz 1987), and

the Schmidt relationship was used when temperatures were below 1°C. Modulus values obtained

from the two models are compared in Figure 7.

In layers that represent an unstabilized base

course, subbase or subgrade material, TRANSFORM calculates the modulus using regression

equations developed from results of laboratory resilient modulus testing conducted on frozen and

thawed soil samples. The equations relate the frozen resilient modulus to temperature (through unfrozen water content), and the unfrozen resilient

modulus to degree of saturation, stress condition,

and (when available) to density (Table 1).

NELAPAV

The program NELAPAV, an acronym for nonlinear elastic layer analysis for pavements, computes stresses, strains, and displacements at any

point in an n-layered pavement system. The mainframe computer version of the program was developed for CRREL by Lynne Irwin of Cornell

University and Gregor Fellers of CRREL in 1980.

Further refinements such as a microcomputer version were developed by Lynne Irwin and Daniel

Speck at Cornell University in 1984 and 1985

(Irwin and Speck 1986). The program uses the

Chevron Layered Elastic Systems program

(CHEVLAY) to calculate the elastic stresses and

strains in a multiple layer system.

The primary reason NELAPAV was chosen is

because it allows the use of nonlinear (i.e., stressdependent) modulus values in the analysis. Modulus values for thawing and unfrozen fine-grained

soils are highly nonlinear as illustrated in Figure 8.

Table 2, from Yang (1988), illustrates the various

types of linear and nonlinear models currently

available for use in NELAPAV; however, models

2 and 7 are not currently incorporated in the rest

of the design procedure.

Daily output from NELAPAV includes 1) a repeat of the input information, 2) moduli of the

Figure 7. Comparison of asphalt moduli computed with Schmidt and Ullidtz

models.

–20 –10 0 10 20 30 40 50

107

106

105

104

Temperature (°C)

Schmidt

Ullidtz

Resilient Modulus

7 × 107

7 × 106

7 × 105

7 × 104

(kPa) (lb/in.2)

5
0 10 20

104

105

Resilient Modulus

w = 16.1%

γ = 105 lb/ft d 3

2 1

2

4

7

σ (lb/in. ) 3

7 x 10 4

7 x 10 5

(kPa) (lb/in. ) 2

(lb/in. ) 2

Deviator Stress

0 70 140 (kPa)

Figure 8. Stress dependence of resilient modulus in station

1206 clay subgrade material (from Bigl and Berg 1996a).

Table 1. Results of regression analyses—test soils from Mn/ROAD.

A. Frozen condition.

Std

Material Equation (Mr in lb/in.2)* n r2 error

Clay subgrade sample 1206 (565)

Frozen M fw r u . = , ()− 1 087 5 259 207 0.99 0.319

Frozen M fw r ug . = ,() − − 1 049 2 344 207 0.99 0.275

Frozen M fw r uv . = ,() − − 1 052 2 929 207 0.99 0.262

Clay subgrade sample 1232 (566)

Frozen M fw r u . = ( )− 905 4 821 244 0.98 0.378

Frozen M fw r u . = ( ) − − 846 2 16

g 244 0.98 0.423

Frozen M fw r uv . = ( ) − − 848 2 633 244 0.98 0.394

Class 3 “stockpile”

Frozen M fw r u . = , ()− 5 824 2 026 186 0.97 0.491

Frozen M fw r u . = ,() − − 5 488 1 076

g 210 0.97 0.507

Frozen M fw r uv . = ,() − − 5 542 1 249 186 0.97 0.467

Class 4 (taxiway A subbase)

Frozen M fw r u . = , ()− 2 826 5 220 69 0.92 0.835

Frozen M fw r ug . = ,() − − 1 813 1 733 85 0.93 0.885

Frozen M fw r uv . = ,() − − 1 652 2 813 69 0.91 0.916

Class 5 (dense graded stone)

Frozen M fw r u . = , ()− 11 320 2 036 28 0.97 0.404

Frozen M fw r ug . = ,() − − 8 695 1 2814 28 0.95 0.511

Frozen M fw r uv . = ,() − − 9 245 1 489 28 0.97 0.432

Class 6 “stockpile”

Frozen M fw r u . = , ()− 19 924 1 243 260 0.98 0.372

Frozen M fw r ug . = ,() − − 19 427 0 795 260 0.98 0.338

Frozen M fw r uv . = ,() − − 19 505 0 897 260 0.98 0.341

layers resulting from calculations, and 3)

stress conditions for all points specified.

For this study, the points specified were

located 0.01 in. above the bottom of the

asphalt or PCC and 0.01 in. below the top

of the subgrade. In the program, a 4090-kg

(9,000-lb) load was applied to a 15-cm

(5.91-in.) radius, which approximates the

area of a standard set of dual wheels or a

falling weight deflectometer ( FWD) testing plate.

CUMDAM

The program CUMDAM calculates

cumulative damage to the pavement structure, and was developed at CRREL. In

general form, the procedure used for

CUMDAM’s calculations is the linear

6
summation of cycle ratios, referred to as Miner’s

rule, which may be stated as:

n

N

D

i

i i

= i

∑ = 1 (1)

where ni = number of applications at strain level i

Ni = number of applications to cause failure at strain level i, based on damage

model predictions

D = total cumulative damage.

In this relation, failure occurs when D equals or

exceeds 1.0. Thus, for a section to last its design

life, the value of D cannot accumulate to 1.0 until

the design period expires.

The value ni relates to the design traffic, or

applications, in 8165-kg (18,000-lb) equivalent

standard axle loadings (ESALs). For the two initial modeling series of this study, traffic was anticipated to be 2,815,000 ESALs during a 5-yr

period. Loadings were applied on a daily basis at

a constant rate of 1542 ESALs per day. In the

Table 1 (cont’d).

B. Unfrozen condtion.

Std

Material Equation (Mr in lb/in.2) n r2 error

Clay subgrade sample 1206 (565)

Never frozen M fS f f r . . 3 . = , , () () () − − 1 597 000 2 63 14 42 0 257 γ σ 655 0.82 0.251

Clay subgrade sample 1232 (566)

Never frozen M fS f r . . = × . () () − − 1 518 1030 13 85

3

0 272 σ 451 0.95 0.328

Class 3 “stockpile”

Thawed M fS f r . . = , () () − 283 300 1 003

2

0 206 σ 408 0.86 0.520

Class 4 (taxiway A subbase)

Thawed M fS f r . . = × . () () − 8 946 108 3 026

2

0 292 σ 149 0.86 0.168

Class 5 (dense graded stone)

Thawed M fS f r . . = , () () − 382 400 0 8759

2

0 1640 σ 64 0.77 0.164

Class 6 “stockpile”

Thawed M fS f f r . .. = , () () () − 1 391 0 507 4 04

1

0 608 γ σ 492 0.79 0.232

Thawed M fS f e f r . . . () = , () () − 5 257 0 486 4 05 0 0193 γ 1 σ 492 0.76 0.249

Notes:

n = number of test points f(wu–v) = wu–v/wo

r2 = coefficient of determination wu–v = volumetric unfrozen water content

Mr = resilient modulus

f(S) = S/So σ = stress (lb/in.2)

S = degree of saturation (%) f1(σ) = J1/σo

So = 1.0 % f2(σ)=(J2/toct)/σo

f(γ) = γ

 d/ γ0 f3(σ) = τoct/σo

γ

 d = dry density (Mg/m3) σo = 1.0 lb/in.2

γ

 0 = 1.0 Mg/m3 J1 = bulk stress (lb/in.2)

f(wu) = wu–g/wt J1 = 3σ3 + σd

wu–g = gravimetric unfrozen water content J2 = 2nd stress invariant (lb/in.2)

wt = gravimetric total water content J2 = 3σ3

2

 + 2σ3σd

f w( ) u g − = wu–g/wo τoct = octahedral shear stress (lb/in.2)

wo = unit water content (1.0) τoct = ( ) 2 3 σd

*Output from equations can be converted to kPa by multiplying by 6.895.

7
third simulation series, the anticipated traffic was

revised to 3,300,000 ESALs during 5 years, applied at a rate of 1808 ESALs per day.

CUMDAM includes several damage models

previously developed for determining Ni

 (Table

3). Of the damage models for flexible pavements,

four are based on horizontal strain at the bottom

of the asphalt layer, and relate to damage effects

that result in fatigue pavement cracking. These

models were developed by the Asphalt Institute

(1982), Witczak (1972), the Corps of Engineers

(U.S. Army 1988), and Coetzee and Connor

(1990). Three other damage models for flexible

pavements are based on the vertical strain at the

top of the subgrade, and these relate to subgrade

rutting damage in the pavement. They were developed by the Asphalt Institute (1982), the Federal

Aviation Administration (Bush 1980), and the

Corps of Engineers (U.S. Army 1987). For rigid

pavements, CUMDAM uses the damage model

developed by the Corps of Engineers (U.S. Army

1990), which is based on the horizontal stress at

the base of the PCC.

The program assumes that all applications will

pass over the location being modeled. That is, the

damage is not reduced according to a pass-tocoverage algorithm to simulate the lateral wander

of the axle within the travel lane. It is recognized

that some of the equations are being applied outside the original assumptions used in their development; however, they are representative of cumulative damage models currently available and

are used for the initial analysis until more appropriate equations can be determined.

MATERIAL TESTING

CRREL conducted various laboratory tests on

base and subgrade materials from Mn/ROAD, with

Table 2. Models currently available in NELAPAV (from Yang 1988).

Model

no. Name Specification

0 Linear Mr

 = constant

1 Bulk stress M k k r = 1θ 2

2 Deviator stress M

k kk k

kk k k r d d

d d

( )

( ) = +− <+− ≥







2 31 1

24 1 1

σ σ

σ σ

3 Second stress invariant M kJ k

r oct = ( ) 1 2 τ 2

4 Octahedral shear stress M k k

r oct = 1τ 2

5 Vertical stress M k k r v = 1σ 2

6 Major principal stress M k k r = 1 1 σ 2

7 First stress invariant M kJ J k k k k r p oct c =+ + ( )( ) 1 10

2

1

2 2 1 τ 3 4

octahedral shear stress

and anisotropic

consolidation ratio

Notes:

θ = bulk stress

k1, k2, k3, k4 = constants

σd = deviator stress

σv = vertical stress

σ1 = major principal stress

J10 = first stress invariant due to overburden only

J1p = first stress invariant due to overburden and load

kc = anisotropic consolidation ratio

8
emphasis on tests to provide input to the Mechanistic Pavement Design Procedure (Table 4). Tests

to generally characterize physical properties included grain-size distribution, specific gravity,

Atterberg limits, organic content, hydraulic properties (moisture retention and hydraulic conductivity), and compaction. Tests more specifically

related to freeze/thaw processes were frost susceptibility and unfrozen moisture content at subfreezing temperatures. Resilient modulus values

were also determined in both the frozen and thawed

(or unfrozen) condition. Modeling materials with

the CRREL design procedure requires data from

the following tests: moisture retention, hydraulic

conductivity, unfrozen moisture content, and resilient modulus.

This report provides a brief summary of the

testing results; a complete presentation is found in

Bigl and Berg (1996a, b) and Berg et al. (1996).

The Mn/ROAD test sections include four base

A. Flexible pavement horizontal strain criteria

1) The Asphalt Institute (MS-1, 1982):

NC E a t

.

a . = × . (. ) [ ] − − − 18 4 4 325 10 3 3 291 0 854 ε

where Na = number of load applications to 45%

cracking

C = a function of the volume of the voids and

the volume of asphalt, 10z

z = 4.84 [(Vb/Vv + Vb) –0.69]

Vb = volume of the asphalt, percent (11%)

Vv = volume of the voids, percent (5%)

εt = tensile strain at the bottom of the asphalt

layer, in./in.

Ea = modulus of the asphalt layer, lb/in.2

2) Witczak (1972) (also Asphalt Institute MS-11):

N abq c d

a t = (/ ) 1 ε

where a = 1.86351 × 10–17

b = 1.01996

c = 4.995

d = 1.45

q = pavement temperature, °F

3) The Corps of Engineers (U.S. Army 1988):

N

E

a

( . log t . log a ) = − − 102 68 5 2 66 ε

4) Coetzee and Connor (1990):

NaEb c a ta = ε

where, when Ea ≥ 1,500,000 lb/in.2: a, b, c

= 3.364 × 106, –7.370, –4.470

and when Ea < 1,500,000 lb/in.2: a, b, c

= 6.565 × 106, –5.764, –3.640

B. Flexible pavement subgrade strain criteria

1) The Asphalt Institute (1982):

N m l s = − 10[ / (log log )] 1 v ε

where Ns = allowable traffic based on subgrade

strain

m = a constant (0.25)

l = a constant (2.8 × 10–2)

εv = vertical strain at the top of the subgrade,

in./in.

2) The Corps of Engineers (U.S. Army 1987):

N A B s = 10000 ( / ) v ε

where A = 0.000247 + 0.00245 log Es

B = 0.0658 Es

0.559

Es = subgrade resilient modulus, lb/in.2

C. Rigid pavement horizontal stress criteria

1) The Corps of Engineers (U.S. Army 1990):

N (df adon)/bdon h ] = − 10 [

where: Nh = allowable traffic based on horizontal

stress

df = Rcon/σh

Rcon = flexural strength of the concrete, lb/in.2

σh = horizontal stress at the base of the

concrete, lb/in.2

adon = 0.2967 + 0.002267 SCI

bdon = 0.3881 + 0.000039 SCI

SCI = surface condition index of the pavement

when failed

Table 3. Cumulative damage models used.

9
materials that were specified to include a range of

frost susceptibility. Of the four bases, the two extreme gradations (class 3 special and class 6 special) were tested for all properties. Testing of the

two intermediate base materials (class 4 special

and class 5 special) was accomplished after this

study was complete. Two subgrade samples received the full series of tests. They are referred to

with the project station number where they had

been collected—1206 and 1232*. Tests were also

conducted to determine general physical characteristics, unfrozen moisture, and frost susceptibility of two subgrade samples from stations 1171

and 1193. Since their properties were similar to

the 1232 and 1206 samples, respectively, they were

not tested for resilient modulus.

Because materials for the two intermediate bases

were unavailable when the initial laboratory testing for the pre-1993 modeling portions of this

study were conducted, their behavior was approximated using data from previously tested materials that most closely matched their specified

size gradations. A subbase from taxiway A at the

Albany, New York, airport most closely matched

the class 4 special subbase specifications; densegraded stone from Winchendon, Massachusetts,

most closely matched the class 5 special material

(Fig. 9). These materials are referred to here, respectively, as TAS and DGS.

Table 4. Laboratory tests performed on Mn/ROAD materials.

Physical properties

Grain Specific Atterberg Organic Hydraul Compact Frost Unfrozen Resilient

Material size gravity limits content prop. test suscept. moisture modulus

Subgrade

1171* oooo o o o o –

1193* oooo – o o o –

1206 oooo o o o o o

1232 oooo o o o o o

Class 3 sp

stockpile ooo– o o o o o

Class 4 sp

TAS† • • – – • –– – •

test strip F o – – P – o o F

Class 5 sp

DGS** ••• – • – • – •

stockpile F o – – F – F o P

Class 6 sp

stockpile oo–– o o o o o

Notes:

o work completed in this study

• data from other studies

P presently being conducted

F planned future work

– no plan to complete this cell in test matrix

“test strip” materials were taken from inplace test strip adjacent to Mn/ROAD

“stockpile” materials were furnished from stockpiles manufactured for the Mn/ROAD project

* Test results from this subgrade sample are in separate reports—see text.

† TAS, taxiway A subbase (substitute material for modeling)

** DGS, dense graded stone (substitute material for modeling)

*The original Mn/DOT sample numbers for the subgrade samples

were 563 for 1171, 564 for 1193, 565 for 1206, and 566 for 1232.

10
100

80

60

40

20

0

10 1.0 0.1 0.01 0.001

Grain Size (mm)

Gravel Sand

Silt or Clay C'rse Fine C'rse Medium Fine

Percent Finer by Weight

4 10 40 200

Hydrometer 3

4

U.S. Std. Sieve Size and No.

Mn DOT Class 4 Spec.

Albany, TW A

Subbase

100

80

60

40

20

0

10 1.0 0.1 0.01 0.001

Grain Size (mm)

Gravel Sand

Silt or Clay C'rse Fine C'rse Medium Fine

Percent Finer by Weight

4 10 40 200

Hydrometer 3

4

U.S. Std. Sieve Size and No.

Mn DOT Class 5 Spec.

Dense Graded

Stone

Figure 9. Comparison of grain size distribution of substitute materials and specifications for equivalent

Mn/ROAD bases.

b. Dense-graded stone, Winchendon,

Massachusetts/class 5 special base.

a.Taxiway A subbase, Albany, New York/

class 4 special base.

Physical characteristics

The general physical properties of the Mn/

ROAD materials were tested according to standard techniques (Table 5). Grain size gradations

of the base materials were shown in Figure 4; gradations of the subgrades classified them as sandy

lean clays (Fig. 10). Maximum density and optimum moisture content determined in compaction

testing are listed in Table 6.

Hydraulic properties

The moisture retention and hydraulic conductivity tests were conducted using the procedures

outlined in Ingersoll (1981). A typical test begins with a saturated sample that is dried incrementally to determine point values of moisture

content and pore pressure head. The laboratory

data are fitted with an equation in the form of

Gardner’s (1958) function using a least squares

11
Table 5. Physical properties of Mn/ROAD materials.

Organic

Specific Atterberg limits** content ††

Material Classification* gravity† LL PI (%)

Subgrade

1206 CL, Sandy lean clay 2.70 37.0 18.5 1.5

1232 CL, Sandy lean clay 2.71 26.4 10.9 0.7

Class 3

stockpile SW, Well-graded sand 2.69 17.0*** 1.2*** —

Class 4

TAS††† SM, Silty sand 2.73 — — —

Class 5

DGS††† GW, Well-graded gravel 2.81 23*** 3*** —

with sand

Class 6

stockpile GW, Well-graded gravel 2.74 — — —

* Classification: ASTM D422-63/ASTM D2487-83

† Specific gravity: ASTM D854-83

**Atterberg limits: ASTM D4318-84

†† Organic content: ASTM D2974-87, Method C; maximum furnace temperature 500°C

*** Minus no. 40 sieve fraction.

††† Substitute materials for modeling: TAS: taxiway A subbase; DGS: dense graded stone.

Figure 10. Grain size distribution in the subgrade materials.

approach to determine the best fit parameters

Aw and α (Table 7). The equation employed is

as follows:

θ θ u α

w p

=

+

0

A h 1 (2)

where θu = volumetric water content (%)

θ0 = soil porosity (%)

hp = pore pressure head (cm of water)

Aw = Gardner’s multiplier for the moisture characteristics

α = Gardner’s exponent for the moisture characteristics.

100

80

60

40

20

0

Percent Finer by Weight

10 1.0 0.1 0.01 0.001

Grain Size (mm)

100

Gravel Sand

Silt or Clay C'rse Fine C'rse Medium Fine

4 10 40 200

U.S. Std. Sieve Size and No. Hydrometer

3 3/4

Sample 1206

Sample 1232

12
Table 6. Compaction test results—Mn/ROAD materials.

Maximum Optimum

dry density water content Method

Material Mg/m3 (lb/ft3) (wt %) employed

Subgrade

1206 1.89 (117.8) 15.5 CE-55

1206 1.69 (105.5) 18.0 CE-12

1206 1.64 (102.1) 20.4 CE-5

1232 1.99 (124.4) 11.9 CE-55

Class 3 special

stockpile 2.11 (131.8) 7.6 CE-55

stockpile 1.98 (123.7) 11.0 CE-12

Class 4 special

stockpile 2.01 (126.0) 10.0 T-99*

Class 5 special

stockpile 2.12 (132.7) 8.1 T-99*

Class 6 special

stockpile 2.09 (130.4) 2.1 CE-55

stockpile 1.93 (120.8) 4.0 CE-12

Notes:

Tests conducted according to Army methods (MIL-STD621A):

CE-55 (similar to AASHTO T-180/Modified Proctor);

compactive effort: 2,630 kJ/m3 (55,000 ft-lb/ ft3)

CE-12 (similar to AASHTO T-99/Standard Proctor);

compactive effort: 575 kJ/m3 (12,000 ft-lb/ft3)

CE-5—compactive effort: 239 kJ/m3 (5,000 ft-lb/ft3)

*Results of Mn/DOT testing

Table 7. Coefficients for hydraulic properties in the form of Gardner’s

equations.

Moisture retention Hydraulic conductivity

Material Aw α AK β

Subgrade

1206 0.002399 0.7134 0.0005713 2.6395

1232 0.002260 0.6790 0.001885 1.8129

Class 3 special

stockpile* 0.1735 0.3239 1647.1 0.7207

Class 4 special

TAS† 0.1520 0.2690 6.59 × 10–5 2.9620

Class 5 special

DGS 0.4961 0.3660 3.912 1.3930

Class 6 special

blended** 1.0001 0.4444 1.0729 × 10–6 5.8979

* “Stockpile” materials were furnished from stockpiles manufactured for Mn/

ROAD

† Substitute materials for modeling: TAS: taxiway A subbase; DGS: dense

graded stone

** “Blended” materials were created by mixing separate size fractions

In a similar manner, point values of hydraulic

conductivity determined at various pore pressure

conditions were fit with a Gardner’s form equation using a least squares approach to determine

the best fit parameters AK and β (Table 7).

K k

A h

H s

K p

=

+

β 1 (3)

where KH = unsaturated hydraulic conductivity (cm/hr)

ks = saturated hydraulic conductivity

(cm/hr)

AK = Gardner’s multiplier for hydraulic conductivity

β = Gardner’s exponent for hydraulic conductivity.

Typical moisture retention and hydraulic conductivity test results are shown in Figures 11

and 12.

Frost susceptibility

Frost susceptibility tests were conducted

using the procedures described in Chamberlain

(1987). Frost susceptibility is determined by

subjecting a soil sample to two freezing cycles

and determining the heave rate during the first

13
 Sample 1206 (565)

 γ = 1.690 Mg/m

 G = 2.70

3 d

s

0

10

8

6

4

2

Tension (lb/in ) 2

0 10 20 30 40

200

400

600

800

Water Content (%)

Tension (cm water)

Weight

Volume

10 20 30 40

0

200

400

600

800

Water Content (%)

Tension (cm water)

Weight

Volume

0

10

8

6

4

2

Tension (lb/in ) 2

 Sample 1232 (566)

 γ = 1.837 Mg/m

 G = 2.71

3 d

s

 G = 2.69

 Class 3 (stockpile)

 γ = 2.029 Mg/m3 d

s

0

10

8

6

4

2

0 10 20 30

200

400

600

800

Water Content (%)

Tension (cm water)

Weight

Volume

Tension (lb/in. ) 2

0 10 20 30

0

200

400

600

800

Weight

Volume

Water Content (%)

Tension (cm water)

0

10

8

6

4

2

Tension (lb/in ) 2

 Taxiway A Subbase

 γ = 2.16 Mg/m3 d

 G = 2.72 s

0

10

8

6

4

2

Tension (lb/in ) 2

0 10 20 30 40

0

200

400

600

800

Weight

Volume

Water Content (%)

Tension (cm water)

Dense-graded Stone

 γ = 1.89 Mg/m3 d

 G = 2.80 s

 G = 2.79

 Class 6 (blended)

 γ = 1.839 Mg/m3 d

s

0

10

8

6

4

2

Tension (lb/in ) 2

0 10 20 30 40

200

400

600

800

Water Content (%)

Tension (cm water)

a. Subgrade sample 1206.

b. Subgrade sample 1232.

c. Class 3 stockpile.

d. Taxiway A subbase.

e. Dense-graded stone.

f. Class 6 blended.

Figure 11. Moisture retention test results. Dashed line represents Gardner’s equation approximation of

the extraction data.

14
0 100 200 300 400 500

Tension (cm water)

Hydraulic Conductivity (cm/hr)

10–1

10–2

10–3

10–4

10–5

10–6

Calculated

Extraction

Absorption

Sample 1206

G = 2.70

γ = 1.690 Mg/m3 d

Tension (kPa)

0 20 40

s

0 100 200 300 400 500

Tension (cm water)

Hydraulic Conductivity (cm/hr)

10–2

10–3

10–4

10–5

10–6

Calculated

Extraction

Absorption

Sample 1232

G = 2.71

γ = 1.837 Mg/m3 d

Tension (kPa)

0 20 40

s

0 100 200 300 400 500

Tension (cm water)

Hydraulic Conductivity (cm/hr) 10–1

10–2

10–3

10–4

10–5

100

101

Calculated

Extraction

Absorption

Class 3 Stockpile

G = 2.69

γ = 2.029 Mg/m3 d

Tension (kPa)

0 20 40

s

0 100 200 300 400 500

Tension (cm water)

10–1

10–2

10–3

10–4

10–5

100

101

Tension (kPa)

0 20 40

Hydraulic Conductivity (cm/hr)

Calculated

Extraction

Taxiway A Subbase

γ = 2.16 Mg/m3 d

G = 2.79 s

0 100 200 300 400 500

Tension (cm water)

10–1

10–2

10–3

10–4

10–5

100

101

Tension (kPa)

0 20 40

Hydraulic Conductivity (cm/hr)

Calculated

Extraction

Dense-graded Stone

γ = 1.89 Mg/m3 d

G = 2.80 s

0 100 200 300 400 500

Calculated

Extraction

Tension (cm water)

Class 6 Blended

G = 2.79

10–1

10–2

10–3

10–4

10–5

100

101

Tension (kPa)

0 20 40

γ = 1.839 Mg/m3 d

Hydraulic Conductivity (cm/hr)

s

a. Subgrade sample 1206.

b. Subgrade sample 1232.

c. Class 3 stockpile.

d. Taxiway A subbase.

e. Dense-graded stone.

f. Class 6 blended.

Figure 12. Tension vs. hydraulic conductivity curves. Solid line represents Gardner’s equation approximation of the extraction data.

15
8 hours of each cycle. The 8-hr heave rate is then

converted to an equivalent heave rate in millimeters/day. The heave rate from the two cycles can

vary significantly, especially if the soil contains

large amounts of clay. At the completion of the

test, a CBR test is run on the thawed sample to

determine an index of the thaw weakening of the

soil. The sample’s frost susceptibility classification is then determined using the criteria shown in

Chamberlain (1987). Results from these tests are

used as a relative index rather than a quantitative

predictor of behavior.

Table 8 summarizes the frost susceptibility test

results on the Mn/ROAD materials. The heave rate

value listed for the base materials is an average

determined from multiple samples. Of the two

clay subgrades, the 1206 sample had an overall

frost susceptibility ranked as very high; the 1232

subgrade ranked as high. The base materials had

test results with a range in frost susceptibility.

Class 6 special ranked as negligible and class 3

special ranked as high in frost susceptibility. Dense

graded stone, used as a substitute for the class 5

special ranked as medium, and Albany taxiway A

subbase, the substitute for the class 4 special,

ranked high in frost susceptibility.

Unfrozen water content

The variation of unfrozen moisture content with

temperature was determined using a pulsed nuclear

Table 8. Frost susceptibility test results.

1st Freeze cycle 2nd Freeze cycle CBR test

Hv rate Hv rate CBR Overall

Material (mm/day) Rating (mm/day) Rating (%) Rating†† rating

Subgrade

1206 9.3 High 16 High <1 V. high V. high

1232 1 V. low 7.5 Medium 2 High High

Class 3 special

stockpile* 10.5 High 14.5 High 5.5 Medium High

Class 4 special

TAS† 10.7 High 12.4 High 3.5 High High

Class 5 special

DGS† 3.7 Low 4.5 Medium 10 Low Medium

Class 6 special

blended** <1 Negl. <1 Negl. 29 Negl. Negl.

* “Stockpile” materials were furnished from stockpiles manufactured for Mn/ROAD

† Substitute material for modeling: TAS: taxiway A subbase; DGS: dense graded stone

** “Blended” materials were created by mixing separate size fractions

†† Frost susceptibility rating

Table 9. Constants for unfrozen moisture content equations (expressed as a

percentage).

Material α β

Subgrade

1206 11.085 –0.274

1232 8.121 –0.303

Class 3

stockpile* 1.497 –0.709

Class 4

TAS † 3.0** –0.25**

Class 5

DGS † 2.0** –0.4**

Class 6

stockpile

+ No. 30 0.232 –1.461

– No. 30 0.567 –1.115

* “Stockpile” materials were furnished from

stockpiles manufactured for Mn/ROAD

† Substitute material for modeling: TAS:

Taxiway A subbase; DGS: Dense graded

stone

**Estimated; no data available

magnetic resonance (NMR) technique (Tice et

al. 1982). The cooling curve data are presented

in Figure 13. The figure also include curves of

calculated values used to represent the data in

16
0

10

20

30

Temperature (°C)

Unfrozen Water Content (% dry wt)

Sample 1232

γ = 1.53 Mg/m3

–2 –4 –6 –8 –10 –12

d

0

2

4

6

8

10

Temperature (°C)

Unfrozen Water Content (% dry wt)

Class 3 Stockpile

γ = 1.97 Mg/m3

–2 –4 –6 –8 –10 –12

d

0

10

20

30

Temperature (°C)

Unfrozen Water Content (% dry wt)

Class 6 Stockpile

+ No. 30; γ = 1.70 Mg/m

- No. 30; γ = 1.85 Mg/m

Calculated

3

3

–1 –2 –3 –4 –5

d

d

a. Subgrade sample 1206.

b. Subgrade sample 1232.

c. Class 3 stockpile.

d. Class 6 stockpile.

Figure 13. Temperature vs. gravimetric unfrozen water content curves. Solid lines represent calculated

values used in the modeling.

the mechanistic procedure, produced with an equation in the form:

w

T

T

T u g 0; − =  −



 

 α  < °

β

0 C (4)

where wu–g = gravimetric unfrozen moisture content, %

T = temperature, °C

T0 = 1.0°C

α, β = constants.

Table 9 contains the constants determined for each

sample. Additional details about the procedure and

test results are in Bigl and Berg (1996a).

Resilient modulus

Laboratory resilient modulus tests were conducted using repeated-load triaxial test procedures,

the full details of which are described in Berg et

al. (1996) and in Cole et al. (1986, 1987). The

tests involve applying a confining pressure to a

cylindrical specimen within a cell, while subjecting the specimen to cyclical loading of a deviator

stress.

Test procedures—Mn/ROAD materials

The materials tested included the two extreme

gradations of base—class 6 special and class 3

special, and the 1206 and 1232 subgrade samples

that represent, respectively, the high- and low-heav0

10

20

30

Temperature (°C)

Unfrozen Water Content (% dry wt)

Sample 1206

γ = 1.23 Mg/m3

d

–2 –4 –6 –8 –10 –12

17
ing subgrades. Specimens of the base materials

and subgrade were tested in a frozen saturated

condition at three temperatures. The same base

material specimens were subsequently warmed to

above freezing and tested again at several moisture contents created by drawing a suction at the

base of the specimens. To obtain unfrozen data for

the subgrade materials, different specimens, referred to as “never frozen,” were molded to specific moisture conditions and tested at room temperature.

The specimen size used for the subgrades and

the class 3 subbase was 5.1 cm (2 in.) diameter and

12.7 cm (5 in.) long. The coarser class 6 material

was tested using specimens measuring 15.2 cm (6

in.) in diameter and 39.4 cm (15.5 in.) in length.

Specimens tested in the frozen/thawed conditions were first molded at the specified moisture/

density, which was usually at optimum as determined from the compaction testing. To approximate field conditions, subgrade specimens received

a compaction effort of 575 kJ/m3 (12,000 ft-lb/

ft3), while class 3 and class 6 special bases were

compacted with an effort equal to 2,630 kJ/m3

(55,00 ft-lb/ ft3) (Table 10). The specimens were

then frozen from the top downwards in a manner

similar to the procedure used in the frost susceptibility test (Chamberlain 1987).

For the 1206 subgrade, the “never frozen” specimens were prepared at 3 compactive efforts, with

moisture contents intended to be at optimum, 2%

above optimum, and 2% below optimum (Table 10).

Table 11a illustrates the sequence of stress conditions applied to the unfrozen specimens, whether

thawed or never frozen. We applied only the stress

combinations that would avoid excessive permanent strains in the specimens (5% decrease in axial

length), depending on the moisture condition and

estimated available strength. The frozen specimens

were tested holding the confining pressure constant at 69 kPa(10 lb/in.2) and varying the deviator stress (Table 11b). The cyclical deviator stress

was applied at each test point until the residual

axial strain remained a constant value, which occurred at about 70–100 applied cycles.

Test procedures—

previously tested materials

The methods used during the resilient modulus

testing of the materials substituted for the class 5

special and class 4 special bases were nearly identical to the methods of this study. Details of the

testing procedures for dense graded stone are described in Cole et al. (1986); the procedures for

Albany taxiway A subbase are in Cole et al. (1987).

Both materials were molded into 15-cm (6-in.)

diam. specimens in the laboratory from field

samples and then frozen from the top down at 2.5

cm (1 in.) per day with open system freezing.

Resilient modulus testing of the substitute materials differed from the procedure used for the Mn/

ROAD materials in two ways: 1) the substitute

materials were not saturated prior to freezing, and

2) the loading sequence was different (Tables 11

and 12). Neither of these variations is expected to

cause significant differences in modulus values.

Data analysis

For each set of applied deviator and confining

stresses, we recorded the resilient and permanent

axial and radial strains, and thus we can calculate

a resilient modulus and a resilient Poisson’s ratio.

The following data were then tabulated in a spreadsheet: confining stress, deviator stress, resilient

axial strain, resilient radial strain, density, and

moisture condition or temperature (Berg et al.

1996).

Linear regression analysis was performed on

the data from the resilient modulus testing of the

Mn/ROAD materials and the substitute materials

for class 4 special and class 5 special. Although

regression analysis had been performed on the

substitute materials for the class 4 and class 5

special subbases, new regression analyses were

performed using our current set of governing parameters. In the regression analysis, the resilient

modulus was the dependent variable. For the frozen condition, a function of the unfrozen water

content was the independent variable; for the

thawed/never frozen condition, various forms and

combinations of stress, density, and degree of saturation were the independent variables.

The frozen and unfrozen data were analyzed

separately. However, the nonlinear form of the

equation used to model the resilient modulus was

the same in both cases, as given by

M KP K r = ( ) 1 2 (5)

where K1 and K2 are constants and P is a governing parameter.

18
Table 10. Resilient modulus samples tested.

Subgrade 1206 Subgrade 1232

Dry density Water content Dry density Water content

No. Mg/m3 (lb/ft3) (% by wt) No. Mg/m3 (lb/ft3) (% by wt)

Never frozen Never frozen

5K Compactive effort * CE 55 Compactive effort

18A 1.77 (110.3) 13.7 14A 1.76 (109.8) 13.1

18B 1.72 (107.4 15.9 14B 1.78 (111.4) 12.9

18C 1.69 (105.3) 16.1 14C 1.78 (111.4) 13.0

21B 1.70 (106.4) 19.7 15A 1.78 (111.0) 14.4

21C 1.70 (106.1) 17.3 15B 1.77 (110.8) 14.1

15C 1.79 (112.0) 13.8

22A 1.69 (108.4) 19.0 15D 1.77 (110.3) 14.3

22B 1.73 (108.0) 19.1

22C 1.74 (108.6) 18.3 16A 1.76 (109.9) 15.7

16B 1.75 (109.0) 15.7

CE 12 Compactive effort 16C 1.76 (110.0) 15.6

16A 1.69 (105.6) 13.5 16D 1.77 (110.7) 15.5

16B 1.67 (104.4) 14.1

16C 1.89 (118.1) 14.3 18A 1.75 (109.3) 17.5

18B 1.75 (109.5) 17.5

18A 1.69 (105.4) 17.4 18C 1.76 (109.9) 17.5

18B 1.71 (106.9) 15.9 18D 1.76 (110.0) 17.2

18C 1.72 (107.3) 15.9

S1 1.70 (106.1) 20.5

20A 1.69 (105.8) 18.5 S2 1.68 (104.7) 21.3

20C 1.70 (106.1) 17.8 S3 1.70 (106.3) 20.3

CE 55 Compactive effort Frozen/thawed (saturated)

13A 1.74 (108.5) 11.0 CE 12 Compactive effort

13B 1.68 (105.1) 10.6 M4-1A 1.73 (107.8) 18.9

M4-1B 1.72 (107.5) 18.8

M4-2A 1.71 (106.6) 19.3

15A 1.88 (117.3) 13.9 M4-2B 1.72 (107.6) 18.3

15B 1.82 (113.9) 13.4

15C 1.85 (115.7) 13.5

M6-1A 1.69 (105.6) 18.9

17A 1.82 (113.9) 14.9 M6-1B 1.72 (107.1) 19.2

17B 1.86 (116.1) 14.9 M6-3A 1.68 (104.7) 19.4

17C 1.84 (114.9) 14.4 M6-3B 1.68 (104.7) 20.2

Frozen/thawed (saturated)

CE 12 Compactive effort

M5-1A 1.71 (106.5) 22.6

M5-1B 1.67 (104.1) 24.1

M5-2A 1.68 (104.6) 23.4

M5-2B 1.70 (106.0) 22.8

* 5K compactive effort = 5,000 ft-lb/ft3 (239 kJ/m3) applied in layers similar to the CE 12 and CE 55 test

methods.

19
Table 10 (cont’d). Resilient modulus samples tested.

Class 3 Subbase Class 6 Base Course

Dry density Water content Dry density Water content

No. Mg/m3 (lb/ft3) (% by wt) No. Mg/m3 (lb/ft3) (% by wt)

Thawed Thawed

CE 55 Compactive effort CE 55 Compactive effort

Class 3-1 2.11 (131.5) 7.2 Class 6-2 2.08 (130.0) 9.6

2.12 (132.1) 3.3 2.08 (130.0) 6.0

2.12 (132.3) 0.8

Class 6-3 2.06 (128.4) 10.1

Class 3-2R 2.13 (132.7) 5.1 2.06 (128.4) 8.9

2.12 (132.6) 3.2 2.09 (130.7) 7.3

2.12 (132.3) 0.8

Class 6-4 2.09 (130.6) 9.5

Class 3-3 2.09 (130.4) 8.3 2.09 (130.6) 7.5

2.10 (131.2) 6.7 2.14 (133.8) 7.2

2.10 (130.9) 2.1 2.14 (133.8) 6.5

2.10 (131.4) 1.4

Class 6-5 2.06 (128.7) 9.3

Class 3-4 2.08 (129.6) 9.3 2.06 (128.7) 7.1

2.09 (129.8) 7.9 2.05 (128.2) 5.1

2.09 (130.5) 4.0 2.05 (128.2) 4.8

2.10 (131.0) 2.4 2.10 (131.0) 2.4

Frozen Class 6-6 2.13 (133.1) 8.9

Class 3-1 2.06 (128.3) 7.6 2.18 (136.0) 4.9

Class 3-2 2.09 (130.7) 6.2 2.18 (136.0) 4.4

Class 3-3 2.03 (126.5) 9.3 2.14 (133.3) 1.6

Class 3-4 2.02 (125.8) 10.1 2.14 (133.8) 0.7

Class 6-9 2.10 (134.2) 8.2

2.08 (136.2) 7.0

2.06 (136.2) 6.1

2.09 (136.2) 5.4

2.17 (135.3) 4.0

2.17 (135.3) 1.4

2.18 (136.3) 0.5

Frozen

Class 6-1 2.10 (130.9) 9.4

Class 6-2 2.08 (130.0) 9.6

Class 6-3 2.06 (128.4) 10.1

Class 6-4 2.09 (130.6) 9.5

Class 6-6 2.13 (133.1) 8.9

Class 6-9 2.15 (134.2) 8.2

Frozen. In attempting to represent the frozen

data with the general form eq 5, we tried three

different governing parameters, all related to the

unfrozen water content of the material, wu. The

unfrozen water content expressed in gravimetric

form, wu–g, was determined as part of this study

(eq 4). The α and β constants characteristic of

each material are listed in Table 9.

The first governing parameter we tried was

wu–g, expressed as a decimal, which had been normalized to the total gravimetric water content in

the sample, wt, expressed as a decimal, also. The

20
resulting equation was as follows:

M Kw w K

r t = ( /) 1 − 2 u g . (6)

This governing parameter has a good physical basis. When the material is very cold and solidly frozen, there is very little unfrozen water and the

ratio wu–g/wt is a small number, << 1; and when the

material is just below the freezing point, wu–g/wt

approaches a value of 1. When this form of the

equation was used in the mechanistic design procedure (Bigl and Berg 199b), the calculated

amount of total water was often very high, and the

ratio of unfrozen water to total water was unreasonably small. Therefore, other relationships were

considered.

The final two forms that were used to represent

the unfrozen water content in the governing paTable 11. Stress conditions of resilient modulus

tests in current study.

Confining pressure Deviator stress Stress ratio

σ3, kPa (lb/in.2) σd, kPa (lb/in.2) (σ1/σ3)

a. Thawed or never-frozen specimens

48.3 (7.0) 48.3 (7.0) 2.0

48.3 (7.0) 34.5 (5.0) 1.7

48.3 (7.0) 27.6 (4.0) 1.6

48.3 (7.0) 20.7 (3.0) 1.4

48.3 (7.0) 13.8 (2.0) 1.3

48.3 (7.0) 6.9 (1.0) 1.1

48.3 (7.0) 3.4 (0.5) 1.1

27.6 (4.0) 48.3 (7.0) 2.8

27.6 (4.0) 34.5 (5.0) 2.3

27.6 (4.0) 27.6 (4.0) 2.0

27.6 (4.0) 20.7 (3.0) 1.8

27.6 (4.0) 13.8 (2.0) 1.5

27.6 (4.0) 6.9 (1.0) 1.3

27.6 (4.0) 3.4 (0.5) 1.1

13.8 (2.0) 34.5 (5.0) 3.5

13.8 (2.0) 27.6 (4.0) 3.0

13.8 (2.0) 20.7 (3.0) 2.5

13.8 (2.0) 13.8 (2.0) 2.0

13.8 (2.0) 6.9 (1.0) 1. 5

13.8 (2.0) 3.4 (0.5) 1.3

6.9 (1.0) 34.5 (5.0) 6.0

6.9 (1.0) 27.6 (4.0) 5.0

6.9 (1.0) 20.7 (3.0) 4.0

6.9 (1.0) 13.8 (2.0) 3.0

6.9 (1.0) 6.9 (1.0) 2.0

6.9 (1.0) 3.4 (0.5) 1.5

b. Frozen specimens

69 (10) 34 (5) –

69 (10) 69 (10) –

69 (10) 103 (15) –

69 (10) 138 (20) –

69 (10) 207 (30) –

69 (10) 276 (40) –

69 (10) 345 (50) –

69 (10) 483 (70) –

69 (10) 621 (90) –

69 (10) 690 (100) –

Notes:

Thawed samples: each combination of stresses normally used at each moisture condition.

Frozen samples: each combination of stresses normally used at each of three temperatures.

Table 12. Stress conditions of resilient modulus

tests—previous study.

Confining pressure Deviator stress Stress ratio

σ3,, kPa (lb/in.2) σd,, kPa (lb/in.2) (σ1/σ3)

a. Thawed specimens

6.9 (1.0) 3.4 (0.5) 1.5

13.8 (2.0) 6.9 (1.0) 1.5

27.6 (4.0) 13.8 (2.0) 1.5

48.3 (7.0) 24.1 (3.5) 1.5

69.0 (10.0) 34.5 (5.0) 1.5

6.9 (1.0) 6.9 (1.0) 2.0

13.8 (2.0) 13.8 (2.0) 2.0

27.6 (4.0) 27.6 (4.0) 2.0

48.3 (7.0) 48.3 (7.0) 2.0

69.0 (10.0) 69.0 (10.0) 2.0

6.9 (1.0) 10.3 (1.5) 2.5

13.8 (2.0) 20.7 (3.0) 2.5

27.6 (4.0) 41.4 (6.0) 2.5

48.3 (7.0) 72.4 (10.0) 2.5

69.0 (10.0) 103.4 (15.0) 2.5

b. Frozen specimens

6.9 (10) 60 (9) –

6.9 (10) 138 (20) –

6.9 (10) 207 (30) –

6.9 (10) 276 (40) –

6.9 (10) 345 (50) –

6.9 (10) 483 (70) –

6.9 (10) 621 (90) –

6.9 (10) 827 (120) –

21
rameter of eq 5 were directly related to the unfrozen water content, as follows: 1) wu–g, expressed

as a decimal, normalized to a unit unfrozen water

content, w0, of 1.0 (i.e., as calculated with eq 4);

and 2) the volumetric unfrozen water content,

wu–v, expressed as a decimal, normalized to a unit

unfrozen water content, w0, of 1.0. The volumetric unfrozen water content was determined with

the equation:

w w uv ug d − − = γ (7)

where γd = dry density, Mg/m3. The resulting equations with these terms substituted as the governing parameter were:

M Kw w K

r ug = ( /) 1 − 0 2 (8)

and

M Kw w K r uv = ( /) 1 0 − 2 (9)

In analyzing the frozen resilient modulus data,

the value of the governing parameter (wu–g/wt

,

wu–g/w0, wu–g/w0) at each test point was determined from the temperature (and total water content, if necessary). Then, regression analysis was

conducted to determine the relationship between

these values and the measured resilient modulus.

Data from the thawed, undrained state (assigned

to be at a temperature just barely below freezing)

were analyzed along with the frozen data. Regression analysis was then conducted to determine the

relationship between these values and the measured resilient modulus (Table 1a).

The left-hand graphs in Figure 14 compare the

frozen resilient modulus data (solid circles) with

predictions from the regression equations with the

three different governing parameters. The figure

shows that the frozen modulus does vary primarily as a function of the unfrozen water content. A

minor amount of variation results from the various stress combinations acting on the specimens,

as shown from the vertical spread in the data at

any particular temperature. The predictive equations without normalization to total water appear

to pass nearer to the center of the range of data

collected at temperatures warmer than –2.0°C.

Thawed/never frozen. To analyze data from the

thawed or never frozen specimens, the governing

parameter in the general form equation (eq 5) was

set to be a stress function. The constant K1 was

considered to be a function of the moisture level

expressed as the degree of saturation in the sample

and, when a range of data were available, the dry

density. Thus, the general equation becomes

M Kf K r = [ ] ( ) 1 σ 2 (10)

which includes the term

K C SS C

1 0 0 = 1 (/ ) (11)

or

K C SS C C

1 0 0 = 1 2 (/ ) ( / ) d o γ γ (12)

where f(σ) = a stress parameter normalized to a

unit stress of 6.9 kPa (1.0 lb/ft2)

C0, C1, C2 = constants

S = the degree of saturation (%)

S0 = a unit saturation (1.0 %)

γo = a unit density (1.0 Mg/m3).

Three stress parameters were investigated to

help characterize the stress dependence of the materials tested. These included J1, the bulk stress

(or first stress invariant); toct, the octahedral shear

stress; and J2/τoct, the ratio of the second stress

invariant to the octahedral shear stress. In our repeated-load triaxial test, where s2 = s3 and s1 = s3

+ sd, the functions are given as:

J1 3 = + 3σ σd

τoct σd = 2

3

and

J2

3

2 3 9 6

2

/ oct

d

d

τ

σ σσ

σ = +

where

J

J

1123

2 12 23 13

1 2

2

2 3

2

1 3 1 2

2

=++

=++

= − +− −

σσ σ

σσ σ σ σσ

τ σσ σ σ σσ oct ( ) ( )( )

.

We found that the bulk stress parameter, J1, provided the best fit to the data for the class 6 base

material; the ratio J2/toct best fit the data of the

three subbases: class 3, class 4, and class 5; and t

oct

best characterized the clay subgrades (Table 1b).

22
Figure 14. Frozen and unfrozen modulus data compared with calculated moduli from

predictive equations.

We also analyzed the data from the class 6 base

material in the thawed condition using an equation in the semilog form:

M KeK f r ( ) = [ ] 1 2 σ (13)

As before, K1 was considered to be a function of

the degree of saturation and the dry density (eq

12). In this case, the stress parameter, f(σ) was

the normalized bulk stress, J1. This form of the

equation was able to accommodate negative

stress values that were generated in the layered

elastic analysis portion of the predictive model.

100

Calculated

80 60 40 20

Degree of Saturation (%)

-10 -8 -6 -4 -2 0

103

104

105

106

107

108

Temperature (°C)

Class 3 Subbase

c

100 80 60

Degree of Saturation (%)

Calculated

90 70

Calculated

100 80 60 40

Degree of Saturation (%)

1206 Subgrade

w /wu t

w u-g

wu-v

Calculated

-10 -8 -6 -4 -2 0

102

103

104

105

106

107

Temperature (°C)

a

Resilient Modulus

7 x 102

7 x 103

7 x 104

7 x 105

7 x 106

7 x107

(kPa) (lb/in. ) 2

1232 Subgrade

-10 -8 -6 -4 -2 0

102

103

104

105

106

107

Temperature (°C)

b

Resilient Modulus

7 x 102

7 x 103

7 x 104

7 x 105

7 x 106

7 x107

(kPa) (lb/in. ) 2

Resilient Modulus

7 x 103

7 x 104

7 x 105

7 x 106

7 x 107

7 x108

(kPa) (lb/in. ) 2

w /wu t

w u-g

wu-v

Calculated

w /wu t

w u-g

wu-v

Calculated

23
Figure 14 (cont’d). Frozen and unfrozen modulus data compared with calculated moduli

from predictive equations.

The right-hand graphs in Figure 14 show the

resilient modulus data vs. degree of saturation for

the unfrozen specimens. For the two subgrade

materials, data are from specimens that were never

frozen; data from the base materials are from specimens that were thawed subsequent to freezing.

Also shown is a line representing the predicted

resilient moduli resulting from the equations given

in Table 1, at the mean stress level tested. Where

dry density is included in the equation, it was set

at the average value of all specimens tested. It can

be seen in Figure 14 that moisture level does in100 80 60 40

Degree of Saturation (%)

Calculated

-10 -8 -6 -4 -2 0

103

104

105

106

107

Temperature (°C)

Class 4 Subbase

Albany Taxiway A

d

Resilient Modulus

7 x 103

7 x 104

7 x 105

7 x 106

7 x107

(kPa) (lb/in. ) 2

100 80 60 40 20

Degree of Saturation (%)

Calculated

Class 5 Subbase

Dense-graded Stone

-10 -8 -6 -4 -2 0

103

104

105

106

107

108

Temperature (°C)

e

Resilient Modulus

7 x 103

7 x 104

7 x 105

7 x 106

7 x 107

7 x108

(kPa) (lb/in. ) 2

100 80 60 40 20 0

Degree of Saturation (%)

Calculated, Log Log

Calculated, Semi Log

f

Class 6 Base

-10 -8 -6 -4 -2 0

103

104

105

106

107

108

Temperature (°C)

Resilient Modulus

7 x 103

7 x 104

7 x 105

7 x 106

7 x 107

7 x108

(kPa) (lb/in. ) 2

w /wu t

w u-g

wu-v

Calculated

w /wu t

w u-g

wu-v

Calculated

w /wu t

w u-g

wu-v

Calculated

24
fluence the unfrozen moduli, but to different degrees, depending on the material. The vertical

spread in the data points at a particular degree of

saturation is the result of the material’s response

to the different stress combinations applied (Table

11a). In the case of the 1206 subgrade and the

class 6 base, it also relates to the variation in density.

To show the influence of density in the 1206

subgrade data, Figure 15 differentiates the data

from three density ranges (high, medium, and low),

along with the corresponding predicted moduli

lines.

The effect of stress combinations is shown in

Figure 16 for the low-density 1206 subgrade data,

and all of the 1232 subgrade and class 3 special

data. The two subgrades display an inverse relationship between modulus and deviator stress; the

class 3 special has a proportional relationship between modulus and the stress parameter J2/toct.

After the resilient modulus testing was completed, we discovered a calibration error in the

system used to test the 1206 subgrade in the unfrozen condition; these data are probably in error.

Testing the 1206 subgrade in the frozen condition

and all testing on the other materials were done

with a different system, which passed its calibration checks. Comparing test results from the 1206

subgrade with those from other materials indicates that unfrozen Mr

 data for the1206 subgrade

may be about an order of magnitude too high.

100 80 60 40

103

104

105

106

Degree of Saturation (%)

Resilient Modulus

115 lb/ft 3

108

105

High

Medium

Low

Density (lb/ft )3

114 - 117

107 - 110

104 - 106

7 x 10 6

7 x 10 5

7 x 10 4

7 x 103

(kPa) (lb/in. ) 2

Figure 15. Resilient modulus of never-frozen 1206

subgrade material vs. degree of saturation illustrating the effect of dry density.

100 80 60 40

103

104

105

106

Degree of Saturation (%)

0.5

1.0

4.0

10

14

σd (lb/in. ) Calculated 2

1206 Unfrozen

Resilient Modulus

7 x 10 6

7 x 10 5

7 x 10 4

7 x 10 3

(kPa) (lb/in. ) 2

0.5

1.0

5.0

9.0

14

σd (lb/in. ) Calculated 2

100 90 80 70 60

102

103

104

105

106

Degree of Saturation (%)

1232 Unfrozen

Resilient Modulus

7 x 10 6

7 x 10 5

7 x 10 4

7 x 10 3

(kPa) (lb/in. ) 2

7 x 10 2

100 80 60 40 20

103

104

105

106

Degree of Saturation (%)

Class 3 Subbase

640

330

117

58

5

Calculated (lb/in. ) 2 J2 τoct /

Resilient Modulus

7 x 10 6

7 x 10 5

7 x 10 4

7 x 10 3

(kPa) (lb/in. ) 2

b. 1232 subgrade.

c. Class 3 subbase.

Figure 16. Resilient modulus vs. degree of saturation illustrating effect of stress parameters.

a. Low-density (104–106 lb/ft3) 1206 subgrade.

(The data in this figure are probably in error—see

text.)

25
PERFORMANCE

PREDICTIONS

Performance predictions using the Mechanistic

Pavement Design Procedure were conducted in

three major efforts:

Phase 1, conducted in the spring of 1991, included an initial simulation series that modeled

temperatures from a year close to the mean freezing index. These boundary conditions were applied

to eight flexible and three rigid sections.

Phase 2, an effort in the summer of 1992, had

two primary objectives. Phase 2A included three

series modeling the eight flexible sections with

the mean freeze season and changing the method

employed to calculate the asphalt and subgrade

modulus. Phase 2B investigated the variability in

predictions when temperatures from freeze seasons with maximum and minimum freezing indices are applied to a single flexible section.

Phase 3, an effort in the summer of 1993, expanded the investigation of the effects of freeze

season characteristics. This series modeled 21 different freeze seasons applied to one full-depth and

one conventional flexible section.

Phase 1

Simulation period

Prior to conducting the initial series of simulations, we analyzed the distribution of seasonal air

freezing indices (an indication of winter severity)

in Buffalo, Minnesota, at a site about 16 km (10

mi) south of Mn/ROAD (Fig. 17). It was decided

to simulate the 1959–1960 winter, which had an

index very near the average value for the period.

The actual days simulated were 1 October 1959 to

14 November 1960, a span of 410 days that allowed some time prior to the start of freezing and

included the entire subsequent thaw season.

Pavement sections

The mechanistic pavement design procedure

was applied to 11 test sections, which were distributed among the designs as follows: four 5-yr

flexible, four 10-yr flexible, two 5-yr concrete,

and one 10-yr concrete (Fig. 18). Water table

depths were modeled based on field measurements

at the site. Seven of the test sections had variable

water table depths along their lengths, and these

were simulated at the two extreme water table

positions. Table 13 lists the test sections and water

table conditions simulated as well as the nomenclature used to denote the various cases. The nomenclature includes the Mn/ROAD test section

number and the water table depth (in ft) preceded

by a “w.” For example, f1w9 refers to Mn/ROAD

test section ML5-F-1 with a water table 9 ft below

the pavement surface and r11w6 refers to section

ML10-R-11 with a water table 6 ft below the pavement surface. All but one case involved the highheaving subgrade (sample 1206) beneath the paveFigure 17. Distribution of seasonal freezing index with time at Buffalo,

Minnesota.

1960 1970 1980 1990

3000

2000

1000

0

1600

1200

800

400

0

Freezing Index

(°C-days) (°F-days)

Buffalo, MN

26
Figure 18. Pavement structure of Mn/ROAD test sections simulated.

Table 13. Test sections simulated, and maximum frost heave/frost penetration preditions.

Water table Frost Frost

Mn/ROAD Simulation depth heave penetration

test section cases m (ft) cm (in.) cm (in.)

Flexible

5-year

ML5-F-1 f1w9 2.7 (9) 0.25 (0.10) 137.9 (54.3)

ML5-F-2 f2w9 2.7 (9) 1.19 (0.47) 121.9 (48.0)

ML5-F-2 f2w20 6.1 (20) 0.33 (0.13) 142.0 (55.9)

ML5-F-3 f3w8 2.4 (8) 0.08 (0.03) 134.1 (52.8)

ML5-F-3 f3w20 6.1 (20) 0.00 142.0 (55.9)

ML5-F-4 f4w6 1.8 (6) 1.37 (0.54) 118.1 (46.5)

ML5-F-4 f4w6 ld 1.8 (6) 1.32 (0.52) 118.1 (46.5)

ML5-F-4 f4w6 ss 1.8 (6) 0.03 (0.01) 137.9 (54.3)

10-year

ML10-F-14 f14w50 15.3 (50) 0.00 134.1 (52.8)

ML10-F-19 f19w18 5.5 (18) 0.00 142.0 (55.9)

ML10-F-21 f21w18 5.5 (18) 0.00 134.1 (52.8)

ML10-F-21 f21w45 13.7 (45) 0.00 134.1 (52.8)

ML10-F-22 f22w45 13.7 (45) 0.00 134.1 (52.8)

Rigid

5-year

ML5-R-5 r5w6 1.8 (6) 1.04 (0.41) 121.9 (48.0)

ML5-R-5 r5w12 3.7 (12) 0.00 137.9 (54.3)

ML5-R-6 r6w4 1.2 (4) 4.72 (1.86) 103.9 (40.9)

ML5-R-6 r6w12 3.7 (12) 0.00 134.1 (52.8)

10-year

ML10-R-11 r11w6 1.8 (6) 1.42 (0.56) 118.1 (46.5)

ML10-R-11 r11w12 3.7 (12) 0.00 134.1 (52.8)

ld = low density (1.69 Mg/m3 or 105.5 lb/ft3)

ss = second subgrade (1232)

Asphalt Concrete

Class 4

Portland Cement Concrete

Class 5

Class 3

Class 6

F-1 F-2 F-3 F-4

0

10

20

30

40

50

0

20

40

60

80

100

120

(cm) (in.)

Depth Below Pavement Surface

5 Year (ML 5-)

F-14 F-19 F-21 F-22 R-5 R-6 R-11

10 Year (ML 10-) 5 Year 10 Year

Flexible Rigid

27
Table 14. Material parameters input to FROST for Mn/ROAD test section simulations.

PCC DGS TAS 1206 1232

Parameter Asphalt Concrete Class 6 Class 5 Class 4 Class 3 Subgrade Subgrade

Soil density (g/cm3) 2.3 2.3 2.09 1.89 2.16 2.11 1.89 1.99

Specific heat of soil (cal/g °C) 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2Thermal cond. of soil (cal/cm hr °C) 17.5 17.5 17.0 17.0 17.0 17.0 17.0 17.0

Soil porosity (cm3/cm3) 0.14 0.14 0.331 0.337 0.206 0.251 0.374 0.320

Soil water characteristics:

A

w 0.3090 0.3090 1.0001 0.4961 0.152 0.1735 0.00240 0.00226

α 0.3190 0.3190 0.4444 0.3660 0.269 0.3239 0.7134 0.6790

Residual water content (cm3/cm3) 0.039 0.039 0.01614 0.05008 0.10741 0.09994 0.2916 0.2638

Saturated hydraulic cond. (cm/hr) 2.10 1.05 6.0 5.54 2.8 4.5 0.14 0.0087Permeability characteristics:

Ak 0.0349 0.0349 3.723×10–8 3.912 6.58

×10–5 1647.1 0.000571 0.001886

β 2.6450 2.6450 5.6733 1.3930 2.962 0.7207 2.6395 1.8129

28
ment structure. The final simulation included the

lower-heaving subgrade (sample 1232) under the

5-yr full-depth section (ML5-F-4), termed case

f4w6ss, or “second subgrade.” One of the 1206

subgrade simulations, also the 5-yr full depth section (case f4w6ld) used a lower dry density of

1.69 Mg/m3 (105.5 lb/ft3) for the subgrade, as compared with what was set as the “normal” case, or

1.89 Mg/m3 (118 lb/ft3).

Material properties

Material properties input to the FROST program are shown in Table 14. Note that the class 3

special, class 6 special, and two subgrade materials were tested as part of this study to determine

the information for input to the model. The class 4

special and class 5 special materials were not

tested, and their behavior was approximated using

data from previously tested materials that most

closely matched their specified size gradations. A

subbase from taxiway A at the Albany, New York,

airport most closely matched the class 4 special

subbase specifications; and a dense-graded stone,

from Winchendon, Massachusetts, most closely

matched the class 5 special material.

In this initial modeling series, the equations

used in TRANSFORM to calculate the modulus

of base, subbase, and subgrade materials were the

gravimetric form of the frozen equations (Table

1a) and the unfrozen equations in Table 1b. For

the class 6 special material, we used the semilog

form listed in Table 1b. The asphalt concrete modulus was calculated with the Schmidt (1975) relationship.

As stated earlier, after these Phase 1 simulations were completed, we discovered that resilient

modulus tests on the 1206 subgrade in the unfrozen condition were probably in error due to a

miscalibrated testing system. As a result, the unfrozen subgrade moduli predicted in Phase 1 modeling

are likely to be substantially higher than exist in

the field, resulting in less damage than would have

been obtained with more reasonable moduli.

In the NELAPAV program, we used the linear

model for paving materials, and for the base, subbase, and subgrade when frozen. Nonlinear models of various forms (Table 2) were assigned to

unfrozen base, subbase, and subgrade as follows:

Model 1 (modified to semilog form)—class 6;

Model 3—class 3 and class 4; and Model 4—both

clay subgrades.

In all of these simulations, it was assumed that

the pavement properties were constant from one

pavement test section to another. Some of the test

sections will possess properties different from others because of the experimental design of the paved

surface. Some variations in the asphalt pavement

properties could be considered in subsequent modeling efforts, but we maintained the same asphalt

pavement properties in all of these simulations.

Results—flexible sections

Figure 19 is an example of output from FROST

for the 5-yr full depth simulation (f4w6). The top

graph shows the daily mean air temperature for

the period from 1 October 1959 to 14 November

1960. The center portion illustrates the predicted

frost heave and the bottom graph contains the predicted frost and thaw penetration as functions of

time. Frost output graphs for all the flexible cases

are compiled in Bigl and Berg (1996b). The freeze

season simulated was characterized by several

short freeze-thaw events early in the season, followed by a continuous severe freeze event with a

fairly rapid spring thaw. Table 13 contains maximum frost heave and maximum frost penetration

depths for each of the cases simulated. Simulations with shallower water table depths had greater

amounts of heave and less frost penetration compared to simulations with a deeper water table

location. Sections that included the substitute for

the class 4 special subbase (taxiway A subbase)

had higher amounts of heave than those with other

combinations of subbase materials.

Figure 20 presents the moduli being calculated

by TRANSFORM and passed as seed moduli to

NELAPAV for the f4w6 case. The plotted moduli

are the minimum values for each day, with the

subgrade (top) being located within 0.3 m (1 ft) of

the asphalt and subgrade (bottom) being the rest

of the modeled section. Note that the predicted

asphalt moduli during the summer months are

smaller than those of the subgrade, which results

in high horizontal strains at the base of the asphalt

layer during the summer months. In later simulations of this study, we used another model for

predicting asphalt modulus at temperatures above

1°C.

29
Figure 19. Example output from FROST for Mn/ROAD test section ML5-F4 with a 1.8-m (6-ft ) water table. Simulation starts on

1 October.

Figure 20. Seed moduli output by TRANSFORM for Mn/ROAD test section

ML5-F4 with a 1.8-m (6-ft) water table. Subgrade (top) is within the upper 0.3

m (1 ft) of subgrade beneath the asphalt. Subgrade (bottom) is beneath that

layer to the bottom of the modeled section.

30
Figure 21 shows the deflection and strains

computed by NELAPAV for the f4w6 case. The

horizontal strain at the base of the asphalt is

small through the winter with a few small peaks

during short-term thawing periods. It then exhibits high peaks during spring thaw and summer. It appears to be closely related to the asphalt temperature/modulus during the spring

thaw. The vertical strain at the top of the subgrade is also low during the winter with three

sharp peaks during thaw events. The vertical

strain also rises during spring and summer,

closely tracking the pavement surface temperature. The deflection plotted is from the base of

the asphalt, but is assumed to be similar to the

surface deflection. It also shows peaks during

midwinter thaws, and a maximum peak during

spring thaw prior to drainage of excess subsurface moisture. Generally, deflections in the summer are greater than winter values.

Table 15 lists the applications to failure predicted from the 1-yr simulation period applied

to the flexible sections. The values listed in

Table 15 were determined by taking the reciprocal of the one year (365-day) cumulative damage

Table 15. Predicted applications to failure (×1000) from Phase 1 simulation series of flexible pavement test

sections.

Horizontal criteria Vertical criteria

Asp. Inst. Asp. Inst. Corps of Coetzee/ Asp. Inst. Corps of

Cases MS-1 MS-11 Engineers Connor MS-1 Engineers FAA

5-Year

F1W9 86 498 88 4,380 136,942 5,653 11,879

F2W9 522 1,244 550 42,703 32,477 1,345 1,526

F2W20 722 1,534 764 66,450 155,909 8,226 9,855

F3W8 957 1,706 958 92,419 116,287 2,653 9,611

F3W20 1,068 1,801 1,055 105,202 222,462 7,889 20,632

F4W6 28,585 75,751 90,926 >107 3,715 15 152

F4W6ld 1,905 20,209 7,036 >107 165 >107 >107

F4W6ss 72 1,180 96 >107 >107 >107 >107

10-Year

F14W50 103,272 485,198 605,194 > 107 8,602 10 251

F19W18 396 6,148 966 75,751 2,962,263 56,680 457,585

F21W18 3,394 30,456 12,751 2,010,107 562,830 84,382 42,478

F21W45 3,404 30,358 12,794 2,010,107 611,772 92,571 48,188

F22W45 7,614 57,315 31,147 8,040,429 73,190 22,415 3,388

Notes:

ld = low density (1.69 Mg/m3 or 105.5 lb/ft3)

ss = second subgrade (1232)

Traffic simulated at rate of 562,830 ESAL applications/yr.

Figure 21. Deflection and strain calculated by

NELAPAV for Mn/ROAD test section ML5-F4 with a 1.8-

m (6-ft) water table. Horizontal strain is at the base of the

pavement. Vertical strain is at the top of the subgrade.

31
value produced by the CUMDAM program and

multiplying by the number of applications received

by the sections during that time period (562,830

per year). This application rate was based on an

initial estimate that the traffic across the test sections would be 2,815,000 ESALs in five years, or

5,630,000 ESALs in 10 years. Subsequent to conducting the Phase 1 series, a revised estimate is

that the 5-yr sections will receive 3,300,000 ESAL

applications in five years, (i.e., are designed to fail

after 3,300,000 ESAL applications); the 10-yr sections will fail at 6,600,000 ESAL applications.

Individual values listed in Table 15 vary anywhere from very much below to very much above

the failure values described. By comparing values

horizontally across the table for any case, it can be

seen that different models estimate substantially

different pavement lives for the same strain conditions.

A close review of the values in Table 15 illustrates a variety of interesting occurrences. Some

of them are the following:

1. Cases with Mn/ROAD test section ML5-F-4

that employed the lower density subgrade (f4w6ld)

or the 1232 subgrade (f4w6ss) predicted the pavement to fail much more quickly than when the

higher (optimum) density 1206 subgrade was used.

This is due to the fact that the higher density 1206

subgrade used in most simulations maintained a

resilient modulus during the summer months in

excess of 276,000 kPa (40,000 lb/in.2), but the

modulus values for the same period were about

96,000 kPa (14,000 lb/in.2) for f4w6ld and

about 6900 kPa (1000 lb/in.2 ) for f4w6ss.

The “low density” predicted moduli are

the closest to the values measured during

the summer months with an FWD.

2. Variations in water table position in

the same test section result in different

predicted lifespans, especially if the water table is less than 3 m (10 ft) deep at

one location and more than 6.1 m (20 ft)

deep at another. Both the ML5-F-2 and

ML5-F-3 test section simulations illustrate a shorter predicted life with a shallow water table depth. For the shallow

water table conditions, greater availability of water results in higher thaw weakening (reduced modulus values) in the

spring.

3. Most of the sections are predicted to fail due

to cracking of the pavement caused by tensile

stresses at the bottom of the pavement much before they will fail due to rutting caused by excessive deformation of the subgrade. It is only the

simulations of the full-depth sections (ML5-F-4,

case f4w6, and ML10-F-14, f14w50) that indicate

rutting failures may occur before excessive fatigue cracking.

Figures 22–24 illustrate examples of the relation between accumulating damage and time. Additional plots of heave, frost penetration, and cumulative damage for all the flexible sections are

compiled in Bigl and Berg (1996b).

Damage related to the horizontal strain criteria

has different patterns with time for different models. Damage predicted by the MS-1 (Asphalt Institute) model has some increase during winter

thaw events and during the main spring thaw, but

a majority of its increase is in the summer period.

Predicted damage from the MS-11 (Witczak)

model has a consistent pattern of rising during

winter and spring thaw periods, and remaining

constant during the summer. The pattern of damage accumulation from the Corps of Engineers

model is similar to the MS-1 model, especially

when the water table is shallow, causing larger

resultant deflections and strains. For simulations

with deeper water tables, smaller amounts of damage accumulate during the summer.

Damage from models using the vertical strain

criteria follow three general patterns: 1) a sharp

Table 16. Applications to failure (×1000) from simulations of

rigid test sections.

RCON = 650 RCON = 500 RCON = 650

Case SCI = 80 SCI = 80 SCI = 90

5-Year

R5W6 52,601 507 45,244

R5W12 65,598 605 56,452

R6W4 157,655 1,505 135,622

R6W12 132,120 1,701 113,933

10-Year

R11W6 >5.6 × 108 18,761,000 >5.6 × 108

R11W12 >5.6 × 108 28,141,500 >5.6 × 108

Notes:

RCON = concrete flexural strength, lb/in.2

SCI = surface condition index at failure

Traffic simulated at rate of 562,830 ESAL applications/yr.

32
rise during spring thaw period with no accumulation at other times of the year (e.g., Fig. 23); 2) a

series of increases during winter thaw events and

the spring thaw (Fig. 22), and 3) in the cases with

lower modulus subgrades, a gradual increase in

damage during the spring, with sharper increases

in the summer (Fig. 24). This last result is likely

due to the anomalously low asphalt moduli being

predicted by the Schmidt model.

Results—rigid sections

Predicted application to failure for the concrete sections is shown in Table 16, with the

three sections in the table indicating the results

of a sensitivity study. In the left-hand section,

the flexural strength of the concrete was set at

4480 kPa (650 lb/in.2) and the surface condition index (SCI) at the point of failure was set

at 80. In the central section, the flexural strength

was reduced to 3448 kPa (500 lb/in.2), while

the SCI remained at 80. For predictions in the

right-hand columns, the flexural strength was

kept at 4480 kPa (650 lb/in.2 ) and the SCI was

increased to 90. A comparison of the cumulative damage with time for the case representing section ML5-R-5 with a 1.8-m (6-ft) water

table (r5w6) using all three combinations of

flexural strength and SCI is also illustrated in

Figure 25. Bigl and Berg (1996b) has a compilation of graphs depicting the frost/thaw penetration and cumulative damage for all rigid

sections simulated.

Cases with a flexural strength of 4480 kPa

exhibited very little damage, with the ML10-

R-11 section having immeasurable damage.

Reducing the flexural strength to 3448 kPa increased the predicted damage for the 5-yr sections, but had little effect on damage in the 10-

yr section.

The pattern of damage accumulation with

time varied with the test section simulated.

ML5-R-5 experienced rapid increases in damage during the thaw periods, but also had an

equivalent increase in damage over the summer months. The other sections experienced a

majority of their damage during the thaw periods and very little damage during the summer.

The low damage predictions result from the

fact that the model predicts damage at the center of a slab, whereas the majority of damage

occurs at the slab edges. Chou (1989) recommends increasing the stresses computed from

the layered elastic method by a factor of 1.33

to estimate the coverage levels for roadway

pavements.

Figure 22. Cumulative damage for case f4w6 with “normal” subgrade.

Figure 23. Cumulative damage for case f2w9.

Figure 24. Cumulative damage for case f4w6 with 1232

subgrade.

33
Phase 2A

To address problems discovered in the Phase 1

modeling series, three additional simulation series were conducted on the eight flexible test sections studied in Phase 1 with the water table located at the shallowest position. A change that

applied to all three series was that the normalized

volumetric unfrozen water content form of the

frozen modulus equations (Table 1a), rather than

the normalized gravimetric form used in Phase 1.

The first of the new series was essentially a

repeat of the initial series in that it used the Schmidt

model (Fig. 7) for calculation of the asphalt modulus and the high density 1206 form of the subgrade

for modulus calculations. It differed from the initial series in that the normalized volumetric

unfrozen water content form of the frozen modulus equations was utilized. A mistake in the

CUMDAM program was also remedied—

correcting the value of the subgrade modulus used in the Corps of Engineers vertical

strain damage calculation. Table 17 lists the

results of this series in the rows labeled

“Schmidt.” In general, predictions of applications to failure in the conventional cross

sections were less than in the original series

using the horizontal strain criteria and greater

using the vertical strain criteria. In the full

depth sections (F4 and F14), applications to

failure were increased in both the horizontal

and vertical strain criteria.

The second series addressed the issue that

the Phase 1 simulations computed summer

asphalt moduli that were lower than considered reasonable. In this series, the Ullidtz

model was used to calculate the asphalt

modulus at temperatures greater 1°C; at colder temperatures, the Schmidt model was used

(Fig. 7). This series also used the high density 1206 form for the subgrade modulus

calculations. Results for this series are shown

in Table 17 in rows labeled “Ullidtz.” In

nearly all cases, this series produced higher

predicted applications to failure than the corresponding Schmidt series.

The third series also used the Ullidtz model

to calculate the asphalt modulus. In addition, it addressed the problem from the Phase

1 simulations that during the summer the

predicted subgrade moduli based on the

high-density 1206, or “normal” form were higher

than FWD-measured values. For this series, the

unfrozen subgrade modulus, when recovered, was

set to be constant at 1.03 × 105 kPa (15,000 lb/

in.2). This value was chosen as being approximately equal to an average value back-calculated

from FWD measurements on subgrade during fall

1991.* As a result of this modulus approximation, the linear model (model 0 in Table 2) was

used in NELAPAV for all subgrade calculations.

The applications to failure from this series are

listed in Table 17 as “Ull-15K.” In the conventional sections including a base/subbase, the applications to failure were slightly lower than those

resulting from the previous case with the Ullidtz

asphalt model and the higher-modulus subgrade;

Figure 25. Cumulative damage for case r5w6.

* D. Van Deusen, Mn/ROAD, person. comm. 1992.

34
Table 17. Predicted applications to failure (×1000) from simulations of flexible test sections run in Phase 2A

series.

Horizontal criteria Vertical criteria

Asp. Inst. Asp. Inst. Corps of Coetzee/ Asp. Inst. Corps of

Cases MS-1 MS-11 Engineers Connor MS-1 Engineers FAA

5-year

F1W9 Phase 1 86 498 88 4,380 136,942 5,653 11,879

Schmidt 85 414 78 3,557 244,709 3,297 15,665

Ullidtz 651 935 218 17,616 258,179 3,430 17,025

Ull-15K 617 863 201 15,578 213,193 3,133 18,441

F2W9 Phase 1 522 1,244 550 42,703 32,477 1,345 1,526

Schmidt 271 859 259 14,634 210,011 2,840 11,389

Ullidtz 970 1,429 376 37,053 255,832 3,262 15,488

Ull-15K 908 1,303 340 31,925 117,747 1,971 6,649

F3W8 Phase 1 957 1,706 958 92,419 116,287 2,653 9,611

Schmidt 533 1,224 487 32,818 96,046 1,197 7,298

Ullidtz 1,255 1,842 528 58,812 87,260 1,108 6,381

Ull-15K 1,225 1,705 503 54,327 115,098 1,404 10,501

F4W6 Phase 1 28,585 75,751 90,926 >107 3,715 15 152

Schmidt 45,171 121,039 175,884 >107 4,505 314 164

Ullidtz 65,218 123,699 149,292 >107 11,952 317 246

Ull-15K 7,055 26,561 8,219 3,752,200 7,996 331 467

10-Year

F14W50 Phase 1 103,272 485,198 605,194 >107 8,602 10 251

Schmidt 126,479 721,577 970,397 >107 11,687 417 336

Ullidtz 209,230 760,581 852,773 >107 17,107 412 359

Ull-15K 19,902 153,779 40,903 >107 26,943 787 2,232

F19W18 Phase 1 396 6,148 966 75,751 2,962,263 56,680 457,585

Schmidt 309 4,335 635 43,328 4,329,462 37,175 632,393

Ullidtz 2,948 14,480 2,278 574,316 4,329,462 37,422 639,580

Ull-15K 2,688 12,367 1,976 469,025 1,125,660 18,173 264,239

F21W18 Phase 1 3,394 30,456 12,751 2,010,107 562,830 84,382 42,478

Schmidt 1,958 16,072 4,701 420,022 865,892 10,452 70,442

Ullidtz 8,515 33,402 9,343 3,752,200 792,718 9,689 61,849

Ull-15K 6,661 23,335 6,513 2,345,125 457,585 8,752 66,686

F22W45 Phase 1 7,614 57,315 31,147 8,040,429 73,190 22,415 3,388

Schmidt 1,750 21,507 5,070 493,711 68,388 1,078 3,077

Ullidtz 8,235 42,964 9,192 3,752,200 85,667 1,278 4,297

Ull-15K 6,186 26,045 5,986 2,084,556 120,520 2,086 9,840

Notes:

Phase 1—previous work, Schmidt— new series with Schmidt asphalt model, Ullidtz—new series with Ullidtz

asphalt model above 1°C, Ull-15K—new series with Ullidtz asphalt model and summer subgrade modulus =

15K lb/in.2 Traffic simulated at rate of 562,830 ESAL applications/yr.

35
in the full depth sections, they were quite a bit

lower.

A comparison of the Ullidtz/15K subgrade

series results with the originally designed failure at 3,300,000 applications for the 5-yr sections and at 6,600,000 applications for the 10-

yr sections yields the following conclusions:

1. In general, the Mechanistic Pavement Design Procedure predicts the 5-yr conventional sections to fail due to asphalt cracking prior to the

end of the design life, while failure from subgrade

rutting is predicted beyond the design life.

2. Predictions for the 5-yr full-depth section

(F4) indicate that it will not fail from asphalt cracking, but two of the three criteria for subgrade rutting indicate early failure.

3. The two 10-yr conventional sections with

class 5 and class 6 special bases (F21 and F22) are

predicted to fail from asphalt cracking at about

the end of the design applications, while subgrade

rutting criteria indicate longer life.

4. The 10-yr conventional section with class 3

special subbase (F19) may fail due to asphalt cracking, but not from subgrade rutting.

5. Predictions for the 10-yr full-depth section

(F14) indicate that it will not fail from asphalt

cracking, but two of the three criteria for subgrade

rutting indicate early failure.

Phase 2B

To investigate the influence of the applied freeze/

thaw season on the predicted performance of the

sections, an environmental effects sensitivity series was conducted using the single conventional

flexible test section, F3, which included class 5

special and class 3 special materials as its base

and subbase courses (Fig. 18) and a water table at

a depth of 2.4 m (8 ft). Prior simulations had applied upper boundary temperatures from the season with a freezing index near to the 30-yr mean,

1959–60 (freezing index 1003°C-days or 1806 °Fdays). This new series applied temperatures from

3 other freeze/thaw seasons, including those with

freezing indices equal to the mean of the three

coldest seasons during the period 1959 to 1987

and the maximum and minimum for the 1959–

1987 period. These seasons were as follows: maximum—1978–79 (1477 °C-days or 2658 °F-days),

minimum—1986–87 (4.67 °C-days or 841 °Fdays), and mean 3 coldest out of 30—1964–65

(1391 °C-days or 2503 °F-days). Results from these

years were compared with f3w8 predictions for

the mean year that had been run in the Phase 2A

“Schmidt” series, since this Phase 2B series also

used the Schmidt model for asphalt modulus calculations and the high density 1206 form for the

subgrade modulus calculations.

Figure 26 shows the freeze/thaw penetration in

the F3 section predicted by FROST for all four

freeze seasons. In the mean year, multiple small

freeze/thaw events were followed by a long freeze

event that penetrated the subgrade and a spring

Figure 26. Frost and thaw

penetrations predicted by

FROST for freeze seasons in

Phase 2B environmental sensitivity study. Simulations

start on 1 October.

AC

CL5

CL3

0 60 120 180 240 300 0 60 120 180 240 300

0

20

40

60

0

20

40

60

Elapsed Time (days)

Frost/Thaw Depth

0

50

100

150

0

50

100

150

(cm) (in.)

1959–60 1986–87

1978–79 1964–65

Mean Min.

Max. 3/30

Frozen

Unfrozen

36
warming that remained above freezing. The minimum year had several freeze/thaw events, but they

were less severe—none of them penetrated beyond the base course materials. The maximum

year began with a very severe freeze event that

penetrated to the subgrade and lasted all winter. In

the spring, thawing of this freeze bulb was interrupted by two smaller freeze events, such that there

existed a thawed layer in the subbase between two

frozen zones. The year with a freezing index equal

to the mean of the three coldest in 30 (3/30 year)

had a freeze season consisting of a single severe

freeze event that penetrated into the subgrade,

which then thawed with no small freeze events.

Table 18 lists the predicted damage in terms of

applications to failure from this environmental series, in which traffic was simulated at 562,830

ESALs per year. Compared with the mean year,

failure due to the horizontal strain criteria (asphalt

cracking) is predicted earlier with the maximum

year and the 3/30 year, and later with the minimum year. However, the spread of values is not

that great, and three of the four models predict

failure sooner than the design figure of 3,300,000

applications for all four of the seasons modeled.

Time of failure due to the vertical strain criteria

(asphalt rutting) is predicted sooner in the maximum year than the mean year, and at about the

same time as the mean year with the 3/30 year. No

damage due to subgrade rutting was predicted with

the minimum year in which no frost penetrated

the subgrade.

Phase 3

The third phase of the study modeled two flexible pavement sections to which 21 years of environmental conditions were applied. Various analyses were conducted attempting to correlate the

predicted damage with the characteristics of the

freeze seasons simulated.

Cross sections/Material properties

The two cross sections simulated employed layer

thicknesses from two Mn/ROAD test sections. The

first, section F4, was a “full-depth” section consisting of an asphalt layer lying directly above the

lean clay subgrade. The second, section F3, was a

“conventional” section, including class 6 special

as the base material (substituted for class 5 special

in the actual pavement structure) and class 3 special as the subbase.

Physical properties used for the materials were

the same as shown in Table 14, with the exception

that a lower density (1.69 Mg/m3, 105.5 lb/ft3)

was used for the 1206 subgrade (Fig. 15). The asphalt modulus was calculated with a combination

of the Ullidtz model at above 1°C temperatures

and the Schmidt model at colder temperatures.

Table 18. Performance predictions for F3 test section with water table at 2.4 m

(8 ft). Freeze/ thaw seasons applied as upper boundary temperatures were mean

year (1959–60), maximum year (1978–79), minimum year (1986–87), average of

the 3 coldest out of 30 (1964–65).

Applications to failure (×1000)

Failure criteria Mean Max Min 3/30

Horizontal

Asphalt Institute (MS-1) 533 384 573 397

Asphalt Institute (MS-11) 1,224 1,215 1,117 1,445

Corps of Engineers 487 375 593 368

Coetzee/Conner 32,818 25,284 50,660 23,530

Vertical

Asphalt Institute (MS-1) 96,046 51,120 >107 96,046

Corps of Engineers 1,197 600 >107 1,143

FAA 7,298 4,080 >107 7,625

Note: Traffic simulated at rate of 562,830 ESAL applications/yr.

37
1.0

1.2

1.4

1.6

1.8

Water Table Depth

(m)

0 400 800 1200 1600 (°C-days)

Freezing Index

6

5

4

3

0 1000 2000 3000 (°F-days)

(ft)

Figure 27. Distribution of freezing indices and water table depths in 21-yr

Phase 3 series.

Table 19. Results of 21-yr freezing index/water table series.

Maximum Applications to failure (millions)

Water table Freezing Freeze/thaw freeze depth Horizontal strain Vertical strain

depth index events in into subgrade Asphalt cracking Subgrade rutting

Year m (ft) °C (°F) -days subgrade (cm) CEH AIH-MS11 CEV AIV-MS1

A. Full depth (F4)

6970 1.5 (4.8) 1191 (2144) 2 91.8 18.20 66.00 0.21 5.38

7071 1.3 (4.2) 1152 (2074) 4 91.8 18.02 52.59 0.34 8.23

7172 1.1 (3.6) 1274 (2294) 2 91.8 15.16 45.02 0.31 7.64

7273 1.2 (4.0) 839 (1510) 2 69.8 18.97 50.69 0.37 7.72

7374 1.3 (4.2) 923 (1661) 2 77.8 17.80 51.48 0.78 10.97

7475 1.4 (4.6) 968 (1743) 3 81.8 17.21 47.93 0.18 5.47

7576 1.3 (4.2) 931 (1675) 3 73.8 16.83 52.26 0.16 4.15

7677 1.6 (5.3) 1256 (2261) 4 107.8 17.92 62.38 0.16 4.87

7778 1.1 (3.7) 1331 (2395) 1 91.8 13.88 60.22 0.10 3.01

7879 1.2 (3.8) 1477 (2658) 3 99.8 17.66 51.36 6.66 17.18

7980 1.2 (3.8) 903 (1625) 5 79.8 16.67 43.10 0.19 5.30

8081 1.2 (4.0) 666 (1199) 3 67.8 17.15 42.63 0.26 7.72

8182 1.8 (6.0) 1227 (2209) 3 107.8 16.29 47.92 0.04 1.44

8283 1.2 (3.9) 589 (1061) 8 63.8 16.73 34.26 0.11 3.71

8384 1.0 (3.3) 1179 (2123) 2 81.8 16.86 48.96 0.12 3.50

8485 1.0 (3.3) 942 (1696) 3 81.8 16.08 44.68 0.15 4.31

8586 1.0 (3.2) 1197 (2154) 2 81.8 17.67 71.27 0.79 11.48

8687 0.9 (3.0) 467 (841) 4 45.8 15.91 33.52 0.48 8.44

8788 1.5 (4.8) 898 (1616) 4 87.8 16.91 48.28 0.34 6.15

8889 1.5 (4.9) 1032 (1858) 4 87.8 17.57 50.53 0.26 7.19

8990 1.4 (4.7) 750 (1350) 7 65.8 16.50 37.45 0.25 6.83

Notes: CEH = Corps of Engineers (horizontal) CEV = Corps of Engineers (vertical)

AIH-MS11 = Asphalt Institute (MS-11) AIV = Asphalt Institute (MS-1)

ND = no damage

Traffic simulated at rate of 660,000 ESAL applications/yr.

38
Environmental conditions

The series simulated the 21-yr time period

1969–70 to 1989–90, using a combination of recorded air temperatures and an estimated position

of the water table. The simulations started on 1

October of the first year and proceeded for 365

days, using mean daily air temperatures recorded

at Buffalo, Minnesota, applied as a step condition

for 24-hr periods. The depth to the water table

was varied based on the total precipitation accumulated at St. Cloud, Minnesota, during the thaw

season prior to the simulated freeze season. An

inverse relationship between precipitation and

water table depth was applied such that the maximum precipitation produced the shallowest water

table at 0.91 m (3 ft) below the surface and the

minimum precipitation produced the deepest water table at 1.82 m (6 ft). The water table was held

constant throughout the simulation at the depth determined by this relationship. Figure 27 shows the

distribution of estimated water table and freeze index for this period.

Results

As in previous simulation series, there was a

wide variation in the damage amounts predicted

by the different models (Table 19). In general, less

damage related to horizontal strain was predicted

in the full-depth design than in the conventional

design. On the other hand, when all other conditions are constant, there was more damage related

to vertical strain in the full-depth design. When

frost did not penetrate the subgrade in the conventional design, essentially no vertical strain damage was predicted.

Freeze season characteristics were initially

quantified by analyzing the total freezing index,

the number of times that frost was predicted to

Table 19 (cont’d).

Maximum Applications to failure (millions)

Water table Freezing Freeze/thaw freeze depth Horizontal strain Vertical strain

depth index events in into subgrade Asphalt cracking Subgrade rutting

Year m (ft) °C (°F) -days subgrade (cm) CEH AIH-MS11 CEV AIV-MS1

B. Conventional (F3)

6970 1.5 (4.8) 1191 (2144) 1 13.4 0.46 2.46 0.82 61.97

7071 1.3 (4.2) 1152 (2074) 1 13.4 0.56 2.63 0.47 34.83

7172 1.1 (3.6) 1274 (2294) 1 17.4 0.56 2.53 0.34 26.17

7273 1.2 (4.0) 839 (1510) 0 0 0.49 1.69 ND ND

7374 1.3 (4.2) 923 (1661) 2 1.4 0.46 2.04 ND ND

7475 1.4 (4.6) 968 (1743) 1 5.4 0.49 2.61 1.46 120.66

7576 1.3 (4.2) 931 (1675) 1 0 0.55 2.71 ND ND

7677 1.6 (5.3) 1256 (2261) 1 25.4 0.43 2.18 0.71 58.36

7778 1.1 (3.7) 1331 (2395) 1 13.4 0.49 2.31 0.51 38.69

7879 1.2 (3.8) 1477 (2658) 1 21.4 0.49 2.72 0.36 27.68

7980 1.2 (3.8) 903 (1625) 1 5.4 0.52 1.87 0.44 33.62

8081 1.2 (4.0) 666 (1199) 0 0 0.50 1.50 ND ND

8182 1.8 (6.0) 1227 (2209) 1 29.4 0.42 2.21 0.46 37.95

8283 1.2 (3.9) 589 (1061) 0 0 0.51 1.34 ND ND

8384 1.0 (3.3) 1179 (2123) 1 5.4 0.49 1.84 1.18 91.16

8485 1.0 (3.3) 942 (1696) 1 5.4 0.48 1.56 0.98 77.74

8586 1.0 (3.2) 1197 (2154) 1 5.4 0.48 2.70 1.64 ND

8687 0.9 (3.0) 467 (841) 0 0 0.44 1.45 ND ND

8788 1.5 (4.8) 898 (1616) 1 9.4 0.45 1.85 0.72 58.30

8889 1.5 (4.9) 1032 (1858) 1 9.4 0.53 1.89 0.45 33.69

8990 1.4 (4.7) 750 (1350) 0 0 0.55 1.65 ND ND

Notes: CEH = Corps of Engineers (horiz.) CEV = Corps of Engineers (vert.)

AIH-MS11 = Asphalt Institute MS-11 AIV = Asphalt Institute MS-1

ND = no damage

Traffic simulated at rate of 660,000 ESAL applications/yr.

39
enter the subgrade and the maximum depth of

frost penetration beneath the top of the subgrade

(Table 19). Lower amounts of damage (higher applications to failure) were predicted by the Asphalt Institute horizontal strain model in seasons

with higher freezing indices and deeper frost penetration in both the full-depth and conventional

cross sections. However, predictions of damage

from the other models did not correlate with any

of the above parameters.

It was noted that two similarly categorized seasons, 1983–84 and 1985–86, which had nearly

identical freezing indexes and water table depths,

as well as the same number of freeze thaw events,

had diversely different damage predictions in the

full-depth section (Table 19a). A large thaw event

in the middle of the 1983–1984 freeze season was

accompanied by severe weakening of the subgrade

both during midwinter and spring thaw, which resulted in a considerable amount of predicted damage (Fig. 28). The 1985–86 year experienced a

nearly continuous freeze season with no significant midwinter thaw event (Fig. 29). As a result,

the subgrade modulus underwent thaw weakening

only during spring thaw in the 1985–86 season,

and the corresponding total damage accumulation

was much less.

Based on the above observation, we tried a new

approach to quantifying the characteristics of the

freeze seasons. It involved summing the thawing

degree days experienced during the freeze season

in two ways. The first was a total from all events,

0 100 200 300

Elapsed Time (days)

0.04

0.03

0.02

Horizontal Damage

0.01

Vertical Damage

1.0

0.5

0

103

104

105

106

107

7 × 103

7 × 104

7 × 105

7 × 106

7 × 107

Resilient Modulus (lb/in.2)

Resilient Modulus (lkPa)

0

40

80

120

Depth (in.)

Depth (cm)

Subgrade

Subgrade

AC

Asphalt

a

b

c

CEV CEH

AIH

0

100

200

300

Figure 29. Predicted results from simulation of

full-depth section during freeze season 1985–1986,

starting on 1 October; a) frost/thaw depth, b) seed

resilient modulus passed to NELAPAV, and c) cumulative damage (see Table 19).

Figure 28. Predicted results from simulation of

full-depth section during freeze season 1983–1984,

starting on 1 October; a) frost/thaw depth, b) seed

resilient modulus passed to NELAPAV, and c) cumulative damage (see Table 19).

40
Table 20. Midwinter season thaw index summations.

Water table Freezing Midwinter thaw index

depth index (Total) (> 30 DD)

Year m (ft) °C(°F)-days °C(°F)-days °C(°F)-days

6970 1.5 (4.8) 1191 (2144) 25.5 (45.9) 0.0

7071 1.3 (4.2) 1152 (2074) 41.0 (73.8) 0.0

7172 1.1 (3.6) 1274 (2294) 50.0 (90.0) 19.4 (35.0)

7273 1.2 (4.0) 839 (1510) 21.5 (38.7) 0.0

7374 11.3 (4.2) 923 (1661) 56.0 (100.8) 22.3 (40.1)

7475 1.4 (4.6) 968 (1743) 35.0 (63.0) 14.2 (25.5)

7576 11.3 (4.2) 931 (1675) 67.0 (120.6) 20.7 (37.2)

7677 1.6 (5.3) 1256 (2261) 44.0 (79.2) 0.0

7778 1.1 (3.7) 1331 (2395) 26.5 (47.7) 0.0

7879 1.2 (3.8) 1477 (2658) 52.0 (93.6) 18.0 (32.4

7980 1.2 (3.8) 903 (1625) 32.0 (57.6) 0.0

8081 1.2 (4.0) 666 (1199) 41.0 (73.8) 17.5 (31.5)

8182 1.8 (6.0) 1227 (2209) 31.5 (56.7) 21.9 (39.4)

8283 11.2 (3.9) 589 (1061) 92.5 (166.5) 75.0 (135.0)

8384 1.0 (3.3) 1179 (2123) 40.0 (72.0) 34.7 (62.4)

8485 1.0 (3.3) 942 (1696) 40.0 (72.0) 22.9 (41.2)

8586 1.0 (3.2) 1197 (2154) 29.0 (52.2) 0.0

8687 10.9 (3.0) 467 (841) 65.0 (117.0) 40.1 (72.1)

8788 11.5 (4.8) 898 (1616) 79.0 (142.2) 54.2 (97.6)

8889 1.5 (4.9) 1032 (1858) 49.0 (88.2) 0.0

8990 11.4 (4.7) 750 (1350) 70.5 (126.9) 27.0 (48.6)

and the second was a total from only the thaw

events that exceeded 16°C-days (30°F-days) (Table

20). The quantity 16°C-days was chosen based on

analysis by Mahoney et al. (1985) indicating that

pavements approach their critically weak condition after this amount of thaw has been experienced. Unfortunately, neither of these quantities

correlated with predicted damage amounts. Apparently, a more sophisticated index that perhaps

combines freeze index, severity of midwinter thaw

events, and other parameters is required to correlate with predicted damage.

In analyzing the Phase 3 simulation results, we

examined the distribution of predicted damage

through the four seasons defined as follows: fall—

1 October to start of freeze, winter—freeze season

as defined by freezing index, spring—75 days following end of freeze season, summer—remainder

of 365-day simulation. The simulations predicted

a wide variation in seasonal damage amounts for

different years, especially in the vertical strain damage in the conventional cross section (Fig. 30). In

years when vertical strain damage was predicted

for the conventional cross section, a majority occurred in the spring, while the remainder occurred

in the winter (Table 21). Horizontal strain damage

in the conventional cross section also occurred

mainly in the spring, with additional significant

amounts in both the winter and fall, and very small

Table 21. Average percentage of total yearly damage

accumulated during four seasons.

Accumulated damage (% of total)

Section/model Fall Winter Spring Summer

Conventional

AIH 22 31 45 2

AIV 0 40 60 0

CEV 0 42 58 0

Full depth

AIH 16 51 32 1

AIV 2 44 16 38

CEV 0 80 20 0

Notes:

AIH = Asphalt Institute horizontal (MS-11)

AIV = Asphalt Institute vertical (MS-1)

CEV = Corps of Engineers vertical

41
a. Conventional section, Asphalt Institute horizontal

strain model MS-11.

b. Conventional section, Asphalt Institute vertical strain

model MS-1.

c. Full-depth section, Asphalt Institute horizontal strain

model MS-11.

d. Full-depth section, Asphalt Institute vertical strain

model MS-1.

Figure 30. Distribution of cumulative damage during seasons.

amounts in the summer. In the full-depth cross

section, horizontal strain damage occurred primarily in the winter, with slightly less in the spring,

and some additional damage in the fall. Both vertical strain models predicted damage in the fulldepth section to occur mainly in the winter, with

some in the spring. The Asphalt Institute vertical

strain model also predicted additional amounts of

summer damage.

DISCUSSION AND

RECOMMENDATIONS

The component of this study involving verification of the Mechanistic Pavement Design Procedure results with pavement performance data

from Mn/ROAD was not accomplished due to

delayed completion of the road.

The Phase 1 modeling series indicated significantly different performance by the different test

sections and highly variable results depending on

the performance model applied (Table 15). The

simulated performance of the test sections was

also significantly affected by the subgrade conditions, e.g., density, soil moisture and water table

depth. For example, compare the model predictions using the Asphalt Institute MS-1 horizontal

strain criteria. For case f4w6, the full-depth 5-yr

section with the 1206 subgrade in its high density

condition, the model predicts 28,585,000 applications to failure. In case f4w6ld, the same test

section with a low density value for the 1206

subgrade, the model predicts 1,905,000 applica1970 1975 1980 1985 1990

0.6

0.4

0.2

0

Annual Damage

Fall Winter Spring Summer

1970 1975 1980 1985 1990

0.03

0.02

0.01

0

Annual Damage

Fall Winter Spring Summer

1970 1975 1980 1985 1990

0.03

0.04

0.02

0

0.01

Annual Damage

Fall Winter Spring Summer

1970 1975 1980 1985 1990

0.6

0.4

0.2

0

Annual Damage

Fall Winter Spring Summer

42
tions to failure. And finally, in case f4w6ss, with

the 1232 subgrade that produced lower resilient

modulus values in lab tests, failure is predicted

after only 72,000 applications, or in less than one

year.

After the Phase 1 simulations were complete,

the resilient modulus data from the 1206 subgrade

were reviewed. A calibration error of unknown

magnitude was discovered in the resilient modulus equipment used to measure the unfrozen modulus on that material. Modulus testing of the 1206

subgrade in the frozen condition and all testing on

the other materials were conducted on a different

machine, which passed its calibration checks.

Comparing frozen and unfrozen resilient modulus

test results from the 1206 subgrade with those

from other materials tested (Fig. 14) indicates that

the unfrozen Mr values for the 1206 subgrade may

be about an order of magnitude too high. A lower

Mr for the 1206 subgrade would have resulted in

earlier failures than computed in this report where

the 1206 optimum density subgrade was used.

We are currently investigating the unfrozen 1206

subgrade results and will include findings and revised performance predictions in Berg (in prep).

It is obviously extremely important to use the

representative subgrade conditions in the design

simulations. Results are consistent with observations from in-service pavements; e.g., weak areas

fail much more rapidly than strong ones and high

water tables cause failures before similar pavements constructed over lower water tables. Both

the “1206” and “1232” subgrade samples were

obtained from the test site and were located less

than one-half mile apart, yet their tested behavior

was quite different. It is hoped that the actual

subgrade will perform more like the “1206”

subgrade than the “1232” material.

Another important aspect governing the results

of the Mechanistic Pavement Design Procedure is

the method used to calculate the asphalt concrete

resilient modulus. The use of the Schmidt model,

which produces extremely low summer season resilient moduli, partially accounts for the short

lifespans predicted in the Phase 1 modeling series. Replacement with the Ullidtz model at temperatures above 1°C in the Phase 2A modeling

series increased the predicted lifespans of the sections when judged by the horizontal strain criteria

(Table 17).

Results from the Phase 2A series that used the

Ullidtz model for asphalt modulus calculations

and a recovered summer subgrade modulus of 1.03

× 105 kPa (15,000 lb/in.2), a close approximation

of the value back-calculated from FWD measurements on subgrade during fall 1991, yield performance predictions that are as “fine-tuned” as possible, so far (Table 17 “Ull-15K”). When these

Mechanistic Pavement Design Procedure predictions are compared with the designed failure at

3,300,000 applications for the 5-yr sections and

6,600,000 applications for the 10-yr sections, the

following statements can be made:

1. Predictions for the full depth sections, both 5

and 10 yr, indicate that they will not fail prematurely from asphalt cracking, but two of the three

criteria for subgrade rutting indicate early failure.

2. Conventional sections are predicted not to

fail due to subgrade rutting; however, sections with

more frost-susceptible bases are predicted to fail

because of asphalt cracking relatively early in their

design life, and sections with non-frost-susceptible bases are predicted to fail towards the end of

their design life.

By modeling 21 years of environmental conditions in the Phase 3 series, we were hoping to

identify the characteristics of a winter that could

be used for design purposes. The results were complex and a relation between predicted failure and

characteristics of freeze seasons was elusive, at

best.

It is recommended that funding be located for

the following studies:

• The class 4 special and class 5 special base

materials should receive the full complement of

laboratory tests so that simulations may be run

using properties of actual materials from the site

rather those of substitute materials.

• Once performance data are received from Mn/

ROAD, predicted and measured values of moisture, temperature, strains and failure times should

be compared to complete the verification component of the study.

• Use performance data from Mn/ROAD to

revise, refine or develop new damage models for

rutting and fatigue cracking.

• Use performance data from Mn/ROAD to

refine or develop a new model for the change of

the asphalt modulus with temperature.

• Use data from falling weight deflectometer

43
tests on Mn/ROAD to estimate pavement performance on an annual basis.

• The Mechanistic Pavement Design Procedure

should be used to estimate performance of all of

the test sections. This study evaluated less than

one-half of the sections.

CONCLUSIONS*

The range of values produced for the various

scenarios is, as noted, extremely wide. This leads

to the conclusion that mechanistic design in its

present stage, while a powerful predictor of

changes in pavement response with changes in

loads or moduli, is at present an uncertain predictor of pavement performance. Data and analyses

from Mn/ROAD are crucial to improving that current uncertain state of performance prediction.

LITERATURE CITED

The Asphalt Institute (1982) Research and development of the Asphalt Institute’s thickness design manual (MS-1), Ninth Edition. College Park,

Maryland. Research Report No. 82-2.

R. Berg (in prep.) Resilient modulus testing of

materials from Mn/ROAD, Phase 2. USA Cold

Regions Research and Engineering Laboratory,

Special Report.

Berg, R.L., S.R. Bigl, J. Stark and G. Durell

(1996) Resilient modulus testing of materials from

Mn/ROAD, Phase 1. USA Cold Regions Research

and Engineering Laboratory, Special Report 96-

19, Mn/DOT Report 96-21.

Berg, R.L., G.L. Guymon and T.C. Johnson

(1980) Mathematical model to correlate frost heave

of pavements with laboratory predictions. USA

Cold Regions Research and Engineering Laboratory, CRREL Report 80-10.

Bigl, S.R. and R.L. Berg (1996a) Testing of materials from the Minnesota Cold Regions Pavement Research Test Facility. USA Cold Regions

Research and Engineering Laboratory, Special

Report 96-20, Mn/DOT Report 96-24.

Bigl, S.R. and R.L. Berg (1996b) Modeling of

Mn/ROAD test sections with the CRREL mechanistic pavement design procedure. USA Cold Regions Research and Engineering Laboratory, Special Report 96-21, Mn/DOT Report 96-22.

Bush, A. (1980) Non-destructive testing for light

aircraft pavements. USAE Waterways Experiment

Station, Vicksburg, Mississippi (sponsored by the

Federal Aviation Administration).

Chamberlain, E.J. (1987) A freeze thaw test to

determine the frost susceptibility of soils. USA

Cold Regions Research and Engineering Laboratory, special Report 87-1.

Chamberlain, E.J., T.C. Johnson, R.L. Berg

and D.M. Cole (in prep.) Prediction of pavement

behavior under loading during freezing and thawing. USA Cold Regions Research and Engineering Laboratory, CRREL Report.

Chou, Y.T (1989) Development of failure criteria

of rigid pavement thickness requirements for military roads and streets, elastic layered method.

USAE Waterways Experiment Station, Vicksburg,

Mississippi, Miscellaneous Paper GL-89-9.

Cole, D., D. Bently, G. Durell and T. Johnson

(1986) Resilient modulus of freeze-thaw affected

granular soils for pavement design and evaluation,

Part 1. Laboratory tests on soils from Winchendon,

Massachusetts, test sections. USA Cold Regions

Research and Engineering Laboratory, CRREL

Report 86-4.

Cole, D., D. Bently, G. Durell and T. Johnson

(1987) Resilient modulus of freeze-thaw affected

granular soils for pavement design and evaluation,

Part 3. Laboratory tests on soils from Albany

county airport. USA Cold Regions Research and

Engineering Laboratory, CRREL Report 87-2.

Coetzee, N.F. and B.G. Connor (1990) Fatigue

characteristics of Alaskan pavement mixes. Transportation Research Record No. 1269, Transportation Research Board, National Research Council,

Washington D.C., p.168–175.

Gardner, W.R. (1958) Some steady-state solutions of the unsaturated flow equation with application to evaporation from a water table. Soil Science, 88: 228–232.

Guymon, G.L., R.L. Berg and T.V. Hromadka

(1993) Mathematical model of frost heave and

thaw settlement in pavements. USA Cold Regions

Research and Engineering Laboratory, CRREL

Report 93-2.

Ingersoll, J. (1981) Method for coincidentally

* This was written by G. Cochran, Mn/ROAD, pers. comm. 1994. determining soil hydraulic conductivity and mois44
ture retention characteristics. USA Cold Regions

Research and Engineering Laboratory, Special Report 81-2.

Irwin, L. and D. Speck (1986) NELAPAV user’s

guide. Cornell University, Ithaca, New York,

Cornell University Local Road Program Report

No. 86-1

Mahoney, J.P., J.A. Lary, J. Sharma and N.

Jackson (1985) Investigation of seasonal load restrictions in Washington state. Transportation Research Record 1043, TRB, National Research

Council, Washington D.C., p. 58–67.

Schmidt, R.J. (1975) Use of ASTM tests to predict low temperature stiffness of asphalt mixes.

Transportation Research Record 544, TRB,

National Research Council, Washington, D.C. p.

35–45.

Tice, A.R., J.L. Oliphant, Y. Nakano and T.F.

Jenkins (1982) Relationship between the ice and

unfrozen water phases in frozen soil as determined by pulsed nuclear magnetic resonance and

physical absorption data. USA Cold Regions Research and Engineering Laboratory, CRREL Report 82-15.

Ullidtz, P. (1987) Pavement analysis. In Developments in Civil Engineering, Vol. 19. Amsterdam: Elsevier Science Publishers.

U.S. Army (1987) Flexible pavement design for

airfields (layered elastic method). Department of

the Army, Washington, D.C. Draft Technical

Manual TM 5-825-2-1.

U.S. Army (1988) Pavement design for roads,

streets, and open storage areas, elastic layered

method. Department of the Army, Washington,

D.C. Technical Manual TM 5-800-09.

U.S. Army (1990) Rigid pavements for airfields

other than Army (layered elastic method). Department of the Army,Washington, D.C. Technical Manual TM 5-824-2-1.

Witczak, M. (1972) Design of full depth airfield

pavements. Proceedings, Third International Conference on the Structural Design of Asphalt Pavements. London, England, Vol. I, p. 450–467.

Yang, W. (1988) Mechanistic analysis of nondestructive pavement deflection data. Doctorate

dissertation, Cornell University, Ithaca, New York

(unpublished).

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September 1996 Final Report June 1988–October 1994

Material Testing and Initial Pavement Design Modeling: Minnesota CPAR Project

Road Research Project Agreement No. 64632

Task Order No. 1

Susan R. Bigl and Richard L. Berg

U.S. Army Cold Regions Research and Engineering Laboratory

72 Lyme Road CRREL Report 96-14

Hanover, New Hampshire 03755-1290

Minnesota Department of Transportation

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Mechanistic pavement design and evaluation procedure Freeze season characteristics

Construction Productivity Advancement Research (CPAR) Pavement performance

UNCLASSIFIED UNCLASSIFIED UNCLASSIFIED UL

Between January 1990 and December 1994, a study verified and applied a Corps of Engineers-developed

mechanistic design and evaluation method for pavements in seasonal frost areas as part of a Construction

Productivity Advancement Research (CPAR) project between the Minnesota Department of Transportation

(Mn/DOT) and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL). The study

involved four primary components. Mn/DOT constructed a full scale pavement test facility adjacent to Interstate

94, referred to as the Minnesota Road Research Project (Mn/ROAD). CRREL performed extensive laboratory

tests on the base and subgrade materials from Mn/ROAD to characterize them and their behavior under seasonal

frost conditions. Laboratory tests provided the input parameters necessary for the study’s third component,

modeling with the CRREL Mechanistic Pavement Design and Evaluation Procedure. The modeling effort was

conducted in three phases, which investigated the effects of freeze season characteristics, water table position,

asphalt model and subgrade characteristics on the predicted performance of selected Mn/ROAD test sections.

Delays in construction on the Mn/ROAD facility prevented the completion of the study’s fourth component—

using performance data from Mn/ROAD to validate the mechanistic pavement design and evaluation procedure.

The report details results from the other three components.