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m , _LIBRARY
1 Michigan State
goo/21 University

 

 

This is to certify that the
thesis entitled

BACKCALCULATED SUBGRADE RESILIENT MODULUS
DESIGN VALUES FOR THE STATE OF MICHIGAN

presented by

Tyler Allen Dawson

has been accepted towards fulfillment
of the requirements for the

Master of degree in Civil Engineering
Science

 

 

/mL.

ajor'Professor’s Signature

WP—

Date

MSU is an Affirmative Action/Equal Opportunity Employer

 

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

5/08 K lProj/Acc&Pres/CIRC/DaleDue indd

BACKCALCULATED SUBGRADE RESILIENT MODULUS DESIGN VALUES FOR
THE STATE OF MICHIGAN

By

Tyler Allen Dawson

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE
Civil Engineering

2008

ABSTRACT

BACKCALCULATED SUBGRADE RESILIENT MODULUS DESIGN VALUES FOR
THE STATE OF MICHIGAN

By
Tyler Allen Dawson

The resilient modulus (MR) of roadbed soils is an important input required for the
design of pavement structures. The MR is a fundamental soil property reflecting the soil
response to the applied stresses. The MR of a given roadbed soil is dependent on the soil
type, water content, dry density, particle gradation and angularity, and stress states. The
latter is a function of the pavement layer thicknesses and stiffness. The implication of the
above is that for a given soil type and stress level, the MR of the soil is independent of
the type of pavement surface (such as concrete, asphalt, or composite) and the type of
testing procedure conducted (triaxial cyclic loading or Falling Weight Deflectometer
(FWD) testing).

The Michigan Department of Transportation (MDOT) sponsored this study to
characterize the MR of the roadbed soils in the State of Michigan. Laboratory tests were
conducted to develop average MR values, by soil type, and correlations to simple tests
(Sessions 2008). FWD tests were conducted and pavement layer moduli were
backcalculated to determine roadbed soil MR. The MR results were very similar between

laboratory and field testing, and between flexible and rigid pavements.

TO EMILY & ZUMAYA

iii

ACKNOWLEDGEMENTS

I would like to thank my advisor, Dr. Gilbert Ba’ladi, for his gracious extension of
help and guidance through this study. I would also like to thank the Michigan State
University department of Civil & Environmental Engineering, and my advisory
committee, Dr. Karim Chatti and Dr. Syed Waqar Haider.

I would also like to thank the Michigan Department of Transportation (MDOT)
for sponsoring and funding this study. Thanks also to the MDOT research advisory panel
headed by Mr. Dave Weber. Special thanks to my co-researcher and friend Colin
Sessions.

The technical, personal, and financial support of the above mentioned as well as

my family has made this all possible. Thank you to everyone who has made this possible.

TABLE OF CONTENTS

LIST OF TABLES .................................................................................. vii
LIST OF FIGURES ................................................................................. ix
CHAPTER 1
INTRODUCTION
1 .1 Background .............................................................................................................. 1
1.2 Problem Statement ................................................................................................... 2
1 .3 Objectives ................................................................................................................ 2
1.4 Research Plan ........................................................................................................... 3
1.5 Thesis Layout ........................................................................................................... 8
CHAPTER 2
LITERATURE REVIEW
2.1 Review of MDOT Practices ..................................................................................... 9
2.2 Soil Classification Systems .................................................................................... 10
2.3 The Role of Roadbed MR in Pavement Design for the ME-PDG ......................... 15
2.4 Engineering Evaluation of Roadbed Soils .............................................. 16
2.4.1 Nondestructive Deflection Tests (NDT) ....................................... 16
2.4.1.1 NDT Devices .................................................................. 17
2.4.1.2 Falling Weight Deflectometer (FWD) Test ............................... 20
2.5 Backcalculation of Layer Moduli of Flexible Pavement ............................. 24
2.5.1 Backcalculation Methods for Flexible Pavement ............................ 24
2.5.1.1 MICHBACK ................................................................... 27
2.5.2 Flexible Pavement Temperature Effect on Resilient Modulus .............. 30
2.5.3 Depth to Stiff Layer Effect on Resilient Modulus ............................ 31
2.6 Backcalculation of Layer Moduli of Rigid Pavement ................................ 32
2.6.1 Backcalculation Methods for Rigid Pavement ............................... 32
2.6.2 Rigid Pavement Temperature Effect on Resilient Modulus ................. 34
2.6.3 Slab Location Selection for NDT ............................................... 35
2.6.3.1 Mid—Slab Loading ............................................................ 35
2.6.3.2 Joint Loading .................................................................. 35
2.6.3.3 Edge Loading .................................................................. 35
2.7 Comparison of Backcalculated and Laboratory Determined MR Values .......... 36
2.8 Seasonal Changes ........................................................................... 38
2.8.1 Spring Season ...................................................................... 38
2.8.2 Summer Season .................................................................... 39
2.9 Distribution of Resilient Modulus of Roadbed Soils in the State of Michigan. . ..40
2.9.1 State Partitioning .................................................................. 40
2.9.2 Soil Sample Collection ........................................................... 42

CHAPTER 3
LABORATORY & FIELD INVESTIGATION

3 .1 Introduction ................................................................................. 46
3.2 State Partitioning and Soil Sampling .................................................... 46
3.3 Laboratory Tests and Procedures ......................................................... 47
3.3.1 Moisture Content, Particle Gradation, and Atterberg Limits ................ 47
3.3.2 Cyclic Load Triaxial Test ........................................................ 47
3.4 Field Tests ................................................................................... 48
3.4.1 FWD Tests ......................................................................... 48
3.4.2 Penetration Resistance and Vane Shear Test .................................. 54
CHAPTER 4
DATA ANALYSIS & DISCUSSION
4.1 Analysis of Laboratory Test Data ........................................................ 58
4.1.1 Soil Classification ................................................................. 58
4.1.2 Cyclic Load Triaxial Test ........................................................ 58
4.2 Backcalculation of Layer Moduli ........................................................ 60
4.2.1 Flexible Pavement ................................................................. 64
4.2.1.1 Sensitivity of the Backcalculated Moduli ............................. 65
4.2.1.2 Analysis of Backcalculated Data from MICHBACK ............... 73
4.2.2 Rigid Pavement .................................................................... 76
4.2.2.1 Analysis of Backcalculated Data from the AREA Method ............. 79
4.3 Comparison between Backcalculated Resilient Modulus Values of Roadbed Soils
Supporting Flexible and Rigid Pavement ............................................... 81
4.4 Comparison between Backcalculated and laboratory Determined Resilient
Modulus Values ............................................................................ 87
4.5 Damage ...................................................................................... 94
CHAPTER 5
SUMMARY, CONCLUSIONS, & RECOMMENDATIONS
5.1 Summary .................................................................................... 96
5.2 Conclusions ................................................................................. 97
5.3 Recommendations .......................................................................... 98
APPENDIX A ...................................................................................... 106
APPENDIX B ...................................................................................... 141
REFERENCES .................................................................................... 148

vi

LIST OF TABLES

Table 2.1 Typical MDOT testing procedures and values for MR ............................ 10
Table 2.2 Comparison between three soil classification systems (USDA 1992) ........... 12
Table 2.3 Typical resilient modulus values for unbound granular and roadbed materials
(NCHRP 2004) ............................................................................. 13
Table 2.4 Backcalculation programs .............................................................. 28
a:
Table 2.5 Regression coefficients for 6,. ..................................................... 34
Table 3.1Distribution of old FWD files .......................................................... 50
Table 3.2 New FWD test locations ............................................................... 55
Table 4.1 MR Predictive Equations ............................................................... 61
Table 4.2 Backcalculated roadbed soil MR supporting flexible pavement .................. 75
Table 4.3 Regression coefficients for 6: .................................................... 77
Table 4.4 Backcalculated roadbed soil MR supporting rigid pavement ..................... 81

Table 4.5 Backcalculated roadbed soil MR supporting flexible and rigid pavements. . ...82

Table 4.6 Laboratory determined and backcalculated roadbed soil MR values ............ 89
Table 5.1 Summary of predictive equations for each soil type .............................. 100
Table 5.2 Average roadbed soil MR values .................................................... 101
Table A] Soil percentages for each area within the 15 clusters (Sessions 2008). . . . . ....109
Table A2 Pocket penetrometer and vane shear test results .................................. 115
Table A3 Moisture content, sieving, and Atterberg limit results ........................... 119
Table A4 Triaxial cyclic load results ........................................................... 122
Table A5 MR results .............................................................................. .136
Table B.l Backcalculated results of flexible pavement ....................................... 143

vii

Table 8.2 Backcalculated results of rigid pavement .......................................... 145

viii

LIST OF FIGURES

Figure 2.1 Regional divisions for MDOT ......................................................... 9
Figure 2.2 Soil support, structural coefficient, and MR correlations (MDOT) ............. 11
Figure 2.3 Soil classification related to strength parameters (NHL 1998) .................. 14
Figure 2.4 Benkelman beam .......................... . ............................................ 18
Figure 2.5 La Croix deflectograph ................................................................. 19
Figure 2.6 Dynaflect ................................................................................ 19
Figure 2.7 Dynatest Falling Weight Deflectometer ............................................. 20
Figure 2.8 Typical deflections at all sensors ..................................................... 23
Figure 2.9 KUAB falling weight deflectometer ................................................ 23
Figure 2.10 Regular and irregular deflection basins ........................................... 30
Figure 2.11 Typical pavement deflections illustrating seasonal pavement strength changes

(PTC 2008) .................................................................................. 39
Figure 2.12 Formations of ice lenses in a pavement structure (PTC 2008) .................. 41
Figure 2.13 Areas and clusters of the State of Michigan ....................................... 42
Figure 3.1 FWD test locations in the State of Michigan ....................................... 51
Figure 4.1 MR versus moisture index for the SM soils ........................................ 60
Figure 4.2 MR versus the SVSM for the SM soils ............................................. 62
Figure 4.3 MR versus SCSP2 for the SP2 soils ................................................. 62
Figure 4.4 MR versus the degree of saturation for the SC, CL and ML soils ............... 63
Figure 4.5 Regular and irregular deflection basins ............................................. 64
Figure 4.6 Effect of number of pavement layers ................................................ 67
Figure 4.7 Effect of AC layer thickness on MR ................................................ 67

Figure 4.8 Effect of base thickness on MR ...................................................... 68

Figure 4.9 No stiff layer ............................................................................ 69
Figure 4.10 Stiff layer at shallow depth .......................................................... 70
Figure 4.11. Stiff layer at deep location ........................................................... 70
Figure 4.12 Soft layer at deep location ........................................................... 71
Figure 4.13 Effect of stiff layer depth ............................................................ 71
Figure 4.14 Effect of stiff layer MR .............................................................. 72
Figure 4.15 Effect of roadbed seed MR .......................................................... 73
Figure 4.16 MR vs. d60 and d36 .................................................................... 74
Figure 4.17 MR vs. deflection ..................................................................... 75
Figure 4.18 Soil classification related to strength parameters (NHI 1998) .................. 79
Figure 4.19 Modulus of subgrade reaction versus California Bearing Ratio (after Huang
2004) ......................................................................................... 80
Figure 4.20 Flexible vs. rigid backcalculated roadbed soil MR .............................. 83
Figure 4.21 Frequency of backcalculated MR of roadbed soils .............................. 83
Figure 4.22 Stiff layer effects on backcalculated k ............................................. 85
Figure 4.23 Range of backcalculated MR (SM, SP1, and SP2 soil) .......................... 86
Figure 4.24 Range of backcalculated MR (SP-SM, SC-SM, SC, and CL soil) ............. 86
Figure 4.25 Laboratory determined and backcalculated roadbed soil MR ........................ 88
Figure 4.26 Moisture content affect on MR of ML soils ................................................... 91
Figure 4.27 Laboratory obtained resilient modulus versus the cyclic stress level .......... 93
Figure 4.28 Range of MR values (SM, SP1, SP2, and SP-SM soil) .......................... 93
Figure 4.29 Range of MR values (SC-SM, SC, CL, and ML soil) ........................... 94
Figure 4.30 Partial spring condition FWD testing .............................................. 95

Figure 5.1 State of Michigan backcalculated MR distribution .............................. 102

xi

CHAPTER 1

INTRODUCTION

1.1 Background

A brief summary of the geography of the State of Michigan is presented below.
The detailed geography can be found in (Sessions 2008).

The State of Michigan is geographically located within the glaciated section of
North America and most of its soil has developed from glacial deposits. The ice sheet
advanced over the state in three lobes, one along Lake Michigan, one along Lake Huron
and the third along Lake Erie. A branch from the Lake Huron lobe advanced
southwesterly and connected to the other two lobes. During the advance of ice a large
amount of soil and bedrock along the path of each ice lobe was pulverized and
incorporated into the ice sheet to later be re-deposited. When the Wisconsin ice sheet
retreated to the north, these materials (known as glacial drift) were superimposed on
sedimentary rock of the Michigan Basin in the Lower Peninsula and the Eastern part of
the Upper Peninsula and on igneous and metamorphic rocks in the Western part of the
Upper Peninsula. The thickness and composition of the drift varies from one location to
another. For example, the thickness of the drift in the Alpena area is only a few inches
whereas it is more than 1200 ft thick in the Cadillac area. The glacial drifi also varies
from clay to gravel; the granular texture may be segregated or mixed heterogeneously
with boulders and clays. Because of these complex arrangements, about 165 different soil
types were formed and are being used for engineering purposes by the Michigan
Department of Transportation (MDOT) (MDSH 1970). The engineering and physical

characteristics of these soils vary significantly from those of gravel and sand in the

Western side of the Lower Peninsula, to clay in the Eastem side, and to varved clay in the
Western part of the Upper Peninsula.

For a given type of roadbed soil, its mechanical (engineering) properties (the
resilient modulus (MR) and the plastic properties) are a function of the physical
parameters (moisture content, grain size, grain angularity, Atterberg limits, etc.) of the
soil and have a major impact on the performance of pavement structures. In this study,
the MR of various roadbed soil types will be determined in the field using Falling Weight
Deflectometer (FWD) deflection data and in the laboratory using cyclic load triaxial tests.
1.2 Problem Statement

The roadbed soils in the State of Michigan consist of glacial soils with distinct
seasonal stiffness changes due to temperature (possible frozen condition) and moisture
levels. MDOT’s current pavement design process follows the procedure outlined in the
1993 American Association of State Highway and Transportation Officials (AASHTO
1993) Design Guide. One of the inputs of said procedure is the effective value of the
resilient modulus of the roadbed soil, which is a function of seasonal changes. The
pending new AASHTO Mechanistic-Empirical Pavement Design Guide (M-E PDG)
procedure is even more stringent for defining MR in terms of seasonal effects. Currently,
MDOT’s various regions provide the “adjusted” MR value used for pavement design.
The MR value is derived from either backcalculated deflection data or a correlation with
known Soil Support Values (SSV).

1.3 Objectives

The main objectives of this study are to:

1.4

Evaluate the existing processes used by all regions of MDOT for determining the MR
value of roadbed soil.
Determine the needed modifications to make the MR selection process compatible
with the new M-E PDG.
Develop procedures, equations, and values for roadbed soil MR for use in any (1, 2,
or 3) level design of the M-E PDG and the current AASHTO design guide.

Research Plan

To accomplish the objectives, a research plan consisting of five tasks was

developed and is presented below.

Task 1— Review and Information Gathering

In this task, the research team will become familiar with MDOT current and

historical processes/procedures for selecting MR and k values for the design of flexible

and rigid pavements. The information could be obtained from the soil engineers in the

various regions. The research team will also obtain information from MDOT that is

needed for the other tasks in this study. These include:

1.

Collection of deflection data from previously conducted FWD tests with known
pavement cross-sections.

Tabulation of the procedures used by the various regions for selecting MR and k
values and the basis of such selection-

Tabulation of the range and typical MR and k values used by the regional soil
engineers for the various soil types.

Assessment of the adequacy and sufficiency of the existing process for estimating

MR values to be used in the new M-E PDG.

Task 2— Partitioned State Map

Based on the MDOT Field Manual of Soil Engineering, the information obtained
from the various regions in Task 1, the trunkline locations, and the soil maps of the US
Soil Conservation Services (USCS), the state will be partitioned into geological zones for
the purpose of field testing and soil sampling. The state will be divided into a maximum
of 15 coarse clusters where the soil within any given cluster would have a similar range
of engineering and physical characteristics. Each coarse cluster will then be further
divided into areas to narrow the range of the soil characteristics. A maximum of 99 areas
will be produced. The results will be presented to members of the Research Advisory
Panel (RAP) for review and possible modification. The main use of the partitioned soil
map will be to determine the locations for field testing and soil sampling.
Task 3— Field and Laboratory Testing and Soil Sampling

In this task, the research team will finalize the field sampling locations and the
laboratory testing plans based upon the information obtained in Tasks 1 and 2. The total
number of tests to be conducted will be based purely on cost and available budget. The
field sampling and the laboratory testing plans are presented in three subtasks below.
Subtask 3.1 - Soil Sampling Plan

From each area on the state partitioned map, roadbed soil samples will be
obtained. In areas where the roadbed soil is predominantly sand, only disturbed bag
samples will be collected. In areas where the roadbed soil is composed of mostly clay,
both disturbed and undisturbed (Shelby tube) samples will be obtained. All samples will
be transported to the laboratory at Michigan State University (MSU) for testing as

presented in Subtask 3.2 below.

Subtask 3.2 — Laboratory Testing Plan

The laboratory testing plan consists of moisture content, sieve analysis, Atterberg

limits, and cyclic load triaxial tests. All tests will be conducted according to MDOT,

AASHTO or American Society for Testing and Materials (ASTM) standard test

procedures. Results of the laboratory testing will be analyzed (see Task 4) to determine:

1.

Soil classification - For each soil sample the soil will be subjected to sieve analyses to

determine its gradation. Plastic and liquid limit tests (Atterberg Limits) will also be

conducted on any sample where the fine fraction (passing sieve number 200) is more

than seven percent. Results of the sieve analyses and Atterberg limit tests will be used

to:

0 Classify the soil according to the USCS and the AASHTO soil classification
systems.

0 Develop, if possible, statistical correlations between the resilient modulus of the
roadbed soils and the gradation and Atterberg limits of the material.

Resilient modulus (MR) - For each soil sample, at least one triaxial cyclic load test

will be conducted to determine the MR. Since, the resilient moduli of roadbed soils

are heavily dependent upon the deviatoric stress; the laboratory tests will be

conducted at three stress states which will be estimated through mechanistic analyses

to simulate the probable in-situ field conditions.

Subtask 3.3 —Field Test Plan

This plan consists of FWD tests. The FWD tests will be conducted at the network-

and proj ect-levels. At the network level, one FWD tests will be conducted at 500 foot

intervals along the state trunkline. At the project level, 20 FWD tests will be conducted

within : 50 ft from all locations where Shelby tubes (undisturbed. soil samples) will be
extracted.

All FWD tests will be conducted, at the same location, once in the spring and
again in the late summer — early fall seasons. For those areas where FWD tests were
conducted in the past and the deflection and pavement cross—section data are available
from MDOT, the data will be used and the number of FWD tests (to be conducted in
those areas in this study) will be reduced depending on the availability of spring and fall
deflection data.

It should be noted that analyses of various damage models, including AASHTO,
indicate that the two point FWD testing (spring and fall seasons) is adequate to assess the
relative pavement damage related to the roadbed soil due to different degrees of
saturation.

Task 4 - Data Analyses

The data analysis, in this study, will be accomplished according to the three
subtasks presented below. First, it should be noted that for all soil types, the relationship
between the MR and k found in the ME PDG will be used.

Subtask 4.1 — Backcalculation of Pavement Layer Moduli

All deflection data, whether collected during this study or other studies, will be
used (depending on the availability of pavement cross-section data) to backcalculate the
pavement layer moduli. The MICHBACK computer program will be used for flexible
pavements and the AREA method for rigid pavements. Although the moduli of all
pavement layers will be backcalculated, only the resilient modulus of the roadbed soils

will be subjected to further analyses. The moduli of the other pavement layers will be

reported without further analyses. .For each test area on the partitioned map, two sets of
moduli will be backcalculated; one set will be based on the spring deflection data and the
other on the late summer-early fall data. The two sets will be further analyzed to estimate
the seasonal damage factor as presented in task five below.

Subtask 4.2 — Laboratory Test Data

Results of the cyclic load tests conducted on Shelby tube and reconstituted bag
samples at various moisture contents will be analyzed to determine the laboratory values
of the resilient modulus of the roadbed soil. Results of the analyses will be used to assess
the impact of moisture (season) on pavement damage and to compare the values to those
obtained from backcalculation.

The Atterberg limits (liquid limit, plastic limit, and plasticity index) and sieve
analysis data will be used to classify the soil and to develop correlations to MR whenever
possible.

Subtask 4.3 — Backcalculated and Laboratory Determined MR Comparison

MR results of roadbed soil from backcalculated FWD deflection data will be
compared with results from cyclic load tests in the laboratory. Any variation between
results, by soil type, will be analyzed. A correlation, if possible, will be made between
backcalculated and laboratory determined MR results.

Task 5— Damage Assessment Analyses

The damage assessment analyses (noted in subtask 4.1) will be conducted based
on the seasonal MR values obtained from the backcalculation of the FWD deflection
data. The purpose of the analyses is to determine the effective MR values to be used in

the design and rehabilitation of flexible and rigid pavements. The effective roadbed

resilient modulus is an equivalent modulus that would result in the same damage as if the
various seasonal resilient modulus values were used (Huang 2004).

The research plan was accomplished in two parts, laboratory testing and analyses
and field testing and analyses. The fomier was presented in (Sessions 2008) whereas the
latter is presented in this thesis.

1.5 Thesis Layout

This thesis is composed of six chapters as follows:
Chapter 1 — Introduction
Chapter 2 — Literature Review
Chapter 3 — Laboratory and Field Investigation
Chapter 4 — Data Analysis & Discussion
Chapter 5 — Summary, Conclusions, & Recommendations
Appendix A — Laboratory and field test results

Appendix B — NDT data test results

CHAPTER 2
LITERATURE REVIEW
2.1 Review of MDOT Practices
The Michigan Department of Transportation (MDOT) has divided the State of
Michigan into seven autonomous regions as shown in Figure 2.1. Each region has
developed its own practice (see Table 2.1) to estimate the resilient modulus (MR) of the
roadbed soils. MDOT has its own soil classification system, based on other systems like
the USCS to classify soil by grain size and other visual properties. Several MDOT
regions use a correlation between soil support values (SSV), AASHTO layer coefficients,

and MR based on the USDA soil classification system which can be seen in Figure 2.2.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 2.1 Regional divisions for MDOT

Table 2.1 Typical MDOT testing procedures and values for MR

 

 

 

 

 

 

 

 

 

Region Procedure 5:153:21 (11:2:
Bay Soil boring & visual identification 3600
Grand FWD data (if available) or soil boring & 2700 _ 8600
Visual identification
Metro Soil boring & visual identification 3000 - 4500
North FWD data (if available) or soil boring & 2500 _ 6000
Visual identification
Southwest California Bearing Ratio correlations
Superior Soil boring & visual identification 4500 - 7000
University Soil boring & visual identification 3000 - 4000

 

 

2.2 Soil Classification Systems

 

A brief summary of soil classification systems is presented in this section. A

detailed review can be found in (Sessions 2008).

There are several soil classification systems used by various agencies and

organizations. The three most popular include; the United States Department of

Agriculture (USDA), the Unified Soil Classification System (USCS), and the American
Association of State Highway and Transportation Officials (AASHTO) soil classification
system (Holtz and Kovacs 1981). MDOT also has its own system, Uniform Field Soil

Classification System, which was created to be applicable on site by visual identification.

In order for various highway organizations to compare their roadbed soils with other

agencies, that use other classification systems, a comparison must be made. Table 2.2

below compares USDA, USCS, and AASHTO.

10

 

SOIL SUPPORT VALUES

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 2.2 Soil support, structural coefficient, and MR correlations (MDSH)

ll

Limestone
““F --------- - 0.15
Salvaged
Gravel 22A Gravel plus
I: bit surface
——-— ------------------- 1 seal 0.14 $
Sand Gravel 20A 1%
r IO
0
UJ
e a)
h--- --------------------------- 0.127 0.115 a
(D
<
o
LU
Sand ‘3
—" - ----- ------------------- 0.11 0.074
Loamy Sand ------- 0'09
Q)
Q
l :s
l a
----- 0.07 :8
-o
8
D
---------- 0.05
Clay """"""""" 0.03
J

 

 

 

85,000

 

 

 

 

69,000

 

 

 

 

 

53,000

 

 

 

 

 

39,000

 

 

 

 

 

26,000

 

 

STRUCTURAL COEFFICIENT

 

 

15,000

 

 

 

7,500

 

fl

 

 

 

3,000

 

 

 

 

RESILIENT MODULUS (PSI)

Table 2.2 Comparison between three soil classification systems (USDA 1992)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

USDA Classification Percent Passing Sieve Number Liquid Plastic
texture USCS AASHTO 4 10 40 200 Limit Limit
Muck PT A-8 100 100 90-100 40-100 014 NP
SP'SM’ SM’ iii-iii:- 40- 25-
Sand SP, GP, GP- ’ ’ 15-90 0-35 <25 NP
A-2, A-3, 100 100
GM, GM
A-2
SM, 80 A-2, A-4,
Loamy SM, ML, A-l-b, A— 85- 60- _
Sand CL-ML,SP- 1,A-2-4, 100 100 30% 3 55 <30 NP
SM, SP A-3
. ML, CL,
5‘2; CL-ML, SC, :‘I; 1162’ 1936 i336 60-100 3095 <45 NP/P
0 SM, CH ’
SM, SC- A-2-4, A-
Sandy SM, ML, 4, A—2, A- 70- 60-
Loam CL-ML, SC, 1,A-1-b, 100 100 35'” ”'75 <35 NP
CL A-6
CL, CL-
Clay ML, SC, A'6’A'4’ 95' 75' 70-100 3590 25—45 NP/P
Loam A-7, A-2 100 100
SC-SM
CL, CL- A-4, A-6, 90- 75—
Loam MLML A_7 100 100 70-100 5090 15-45 NP/P
Mucky SM, SP, SP- A-l-b, A- 95- 75-
Sand SM 2-4,A-3 100 100 ”‘70 0'15 0’14 NP
A-6, A-7- 90- 85-
Clay CH, CL 6 100 100 65-95 45-95 30-65 P
Silty CL, SC, CL- A-4, A-6, 85- 60-
Clay ML A_7 100 100 50-100 3090 25-50 NP/P

 

 

NP = non-plastic, plastic limit<10

P = plastic soil, plastic limit>10

 

Several correlations between the soil classification systems and the resilient

modulus of roadbed soils can be found. Some regions of MDOT use the correlations

found in Figure 2.2 currently. For use with the ME PDG, Table 2.3 recommends ranges

and typical MR values by AASHTO soil classification and USCS. Figure 2.3 also

provides estimations of various roadbed soil parameters correlating to the AASHTO

 

classification system and USCS (NHI 1998). The tables and figures previously mentioned
only provide ranges and it is up to the engineer to decide upon a value to use in design.

Table 2.3 Typical resilient modulus values for unbound granular and roadbed materials

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(NCHRP 2004)

Classification Material pounds/square inch . 1
System Classification MR Range Tylelga
A—l-a 38,500 - 42,000 40,000

A-l-b 35,500 - 40,000 38,000

A-2-4 28,000 - 37,500 32,000

A-2-5 24,000 - 33,000 28,000

A-2-6 21,500 - 31,000 26,000

. A-2-7 21,500 - 28,000 24,000
AASHTO A-3 24,500 - 35,500 29,000
A-4 21,500 - 29,000 24,000

A-5 17,000 - 25,500 20,000

A-6 13,500 - 24,000 17,000

A-7-5 8,000 - 17,500 12,000

A-7-6 5,000 - 13,500 8,000

CH 5,000 - 13,500 8,000

MB 8,000 - 17,500 11,500

CL 13,500 - 24,000 17,000

ML 17,000 - 25,500 20,000

SW 28,000 - 37,500 32,000

SP 24,000 - 33,000 28,000

SW - SC 21,500 - 31,000 25,500

SW - SM 24,000 - 33,000 28,000

SP — SC 21,500 - 31,000 25,500

USCS SP - SM 24,000 - 33,000 28,000
SC 21,500 - 28,000 24,000

SM 28,000 - 37,500 32,000

GW 39,500 - 42,000 41,000

GP 35,500 - 40,000 38,000

GW - GC 28,000 - 40,000 34,500

GW - GM 35,500 - 40,500 38,500

GP - GC 28,000 - 39,000 34,000

GP - GM 31,000 - 40,000 36,000

GC 24,000 - 37,500 31,000

GM 33,000 - 42,000 38,500

 

 

 

 

 

13

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

l 1.5 2 3 4 5 6 8 10 15 20 3040 50 70 100
I I r A I GLIAGW

ASTM Soil Classification System : V r I 17“ l T '
Unified Soil Classification System (USCS) GM :‘ I . i, . t L ,

 

 

 

 

 

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I
3 —H SM
1 ; SP-II ,
l l l 3 ‘ ; SC I I l l I
CH :I I:: I ; ‘ i I
A LA _ ML

CH ~ .-T , , . , , . .

<i—-’-r+ 0L I CL ’- 1 I ,
MH : I I I :1 I E I I I I

l r T i T T; ‘ l i ‘
AASHTO Soil Classification A-l-a T l I l r
I :I It a: A-l-b l

A-2-4,A-2-5 fit I, . w 1 .
. F . t A-2-6,A-2-7

I l l A-3 : I ;I ‘ l j |

: . 1 ‘ I t A-4

5 I p f: A-5 I ‘
4 I ‘ I L A-6 I ‘ I
< , . ~ > A-7-5,A-7-6 ‘ j I I 1

: I I I I j 5
I I I I l 1| I I l l I I i
1 Resistance Value—R I I
I 5 10 20 30 40 50 60 70 2 I I
I | ' I I I I I I l I I

 

Modulus of Subgrade Reaction — k (psi per inch)

 

 

 

 

 

 

 

 

100 150 200 250 300 400 500 700
I . . I I I I i , l I I
l Bearing Value (psi)
1 10 20 30 40 50
I I I I I I l . I I
California Bearing Ratio (CBR) . I 4
l 1.5 2 3 4 5 6 8 IO 15 20 30 40 50 70 100

Figure 2.3 Soil classification related to strength parameters (NHI 1998)

14

2.3 The Role of Roadbed MR in Pavement Design for the M-E PDG

A brief summary the ME PDG procedure with regard to roadbed MR is
presented in this section. A detailed review can be found in (Sessions 2008).

The M-E PDG allows users to be flexible with the specificity they have in the
input data to the design guide. Depending on the resources available and requirements of
any given design project, the user can choose how general or specific the input data will
be. Structural inputs, such as the roadbed MR, can be selected from any of a three level
hierarchy (Coree et. al 2005).

Level one design is the most precise of the levels and requires the most accurate
inputs. Roadbed MR must be determined by field or laboratory tests, such as FWD
deflection testing or cyclic load triaxial testing. Pavement sections that are of greater
importance to the agency, such as high traffic roads or those with economic and social
significance, will be designed at level one. This level is more expensive and time
consuming, but will lead toward a more dependable result.

Level two and three designs require less specific data. Roadbed MR could be
estimated, for level two, from simple soil tests. Typical default values could be used with
level three designs. The lower levels will be less expensive to design with but will yield
less reliable results. The design level used does not have to stay constant between
different inputs; general, traffic, climatic and structural. However, the design process will
be the same regardless of the input level (Prozzi and Hong 2006).

In all three levels of design the roadbed MR is a required input to the pavement
structural response model. No matter what design level is used, roadbed MR plays a

significant role in computing pavement response and dynamic modulus of subgrade

15

reaction, k-value, which is computed internally by the Design Guide software (NCHRP

2004)

2.4 Engineering Evaluation of Roadbed Soils

The engineering evaluation of roadbed soils can be achieved using several
techniques that can be divided, in general, into two categories: destructive and

nondestructive. Destructive tests include:

o Coring

o Drilling and/or Shelby tube extraction

Nondestructive tests include:

0 Ground penetrating radar (GPR) to estimate the pavement layer thicknesses

o Nondestructive deflection tests (NDT) to measure the pavement response to loads

0 Surface wave application to measure pavement response

Literature review regarding NDT and the use of the deflection data in pavement

evaluation processes are addressed in the next sections.

2.4.] Nondestructive Deflection Tests (NDT)

The nondestructive deflection test (NDT) is the most popular test used in
pavement evaluation. Relative to destructive testing, NDT are fast and require minimum
lane closure time. In recent years, the use of NDT has become an integral part of the

structural evaluation and rehabilitation of pavement structures.

16

The NDT results (the pavement deflections at various distances from the center of

the load) are used to:

o Backcalculate the pavement layer moduli

0 Assess the variability of the pavement response to loads along and across the

pavement and. hence, the variability of the pavement structural capacity

0 Estimate load transfer efficiency of dowel bars

0 Evaluate the presence of voids beneath the pavement surface

0 Design the thickness of pavement overlays

Various types of NDT devices are available and being used by various State
Highway Agencies (SHA). These are presented in the next subsection.
2.4.1.1 NDT Devices

NDT devices are used by state highway agencies to apply patterns of loading and
record deflection data along the pavement surface. The deflection data measured along
the pavement surface at different distances from the center of the load are typically used
to backcalculate the modulus values of the various pavement layers and the roadbed soil.
Numerous backcalculation software packages are available either in the public domain or
can be purchased. Most of these use more or less the common procedures presented in the
next sections.

Various types of NDT equipment are available. A brief summary of the available

equipment is presented in this subsection. Details on the equipment can be found in

(Mahmood 1993).

17

0 Static deflection equipment including: the Benkelman Beam, which can be seen in
Figure 2.4, (Moore et a1 1978; Asphalt Institute 1977; Epps et al 1989), the plate
bearing test (Moore et a1 1978; Nazarian et a1 1989), the Dehlen Curvature Meter

(Gouzheng 1982), the Pavement Deflection Logging Machine (Keneddy et a1 1978),

and the C.E.B.T.P. Curviameter (Paquet 1978).

 

 

Figure 2.4 Benkelman beam

0 Automated deflection equipment including: the La Croix Deflectograph, which can
be seen in Figure 2.5, (Hoffman et a1 1982; Keneddy 1978), and the California
Travelling Deflectometer (Roberts 1977).

o Steady-State dynamic deflection equipment including: the Dynaflect, which can be
seen in Figure 2.6, the Road Rater, the Cox Device, the Waterways Experiment
Station (WES) Heavy Vibrator, and the Federal Highway Administration (FHWA)

Thumper (Scrivner et al 1969; Smith et al 1984; Moore et al 1978).

 

Figure 2.6 Dynaflect

0 Impulse deflection equipment including: the Dynatest FWD, which can be seen in
Figure 2.7, KUAB FWD, and the Phoenix FWD (Nazarian et al 1989; Hoffman and

Thompson 1981; Bohn et a1 1972; Crovetti et a1 1989; Claessan et a1 1976).

 

Figure 2.7 Dynatest Falling Weight Deflectometer

2.4.1.2 Falling Weight Deflectometer (FWD) Test

Falling Weight Deflectometers (FWD) are used to apply load to the pavement and
measure deflection on the pavement surface at several longitudinal distances from the
applied load. The FWD is often preferred over laboratory testing for several reasons
including: the nondestructive nature of the tests, low operational cost per test, short test
duration, tests can be designed to provide more coverage of the pavement network, and
the roadbed soils are being tested under in-situ boundary conditions. The disadvantages

include the difficulty to determine or control the water content of the roadbed soils,

20

determine the roadbed soil density, and to control the applied normal and shear stress
levels (Houston et. a1 1992).

The FWD operates on two basic assumptions; the force of impact due to a falling
load is considered a static load, and the roadbed soil acts as an elastic body. The weight

of the falling mass can be calculated as follows, as presented in (Kim et a1 2006).

WI (H + amax )— ’5K6 21““ = 0 Equation 2.1

Where, W1 = weight corresponding to the mass M

H = height M was dropped from

dmax = maximum pavement deflection
K = spring constant

5max/5sr = the impact factor, which can be found by equation 2.2.

5 /53,=1+ 1+ —

max

Equation 2.2

st

1
2H I2

Where, (Sst = static deflection

The impact load is calculated using equation 2.3, by multiplying the static load by

the impact factor.

2
=W,1+1+2—fi

S!

P

“III I Equation 2.3

Due to the difficulty in measuring impact load, force is calculated by multiplying

weight by height.

21

F = WH Equation 2.4
Where, F = force

The uniformly distributed load can be obtained from equation 2.5.
q = 2 Equation 2.5

Where, q = applied load to plate
A = loading plate area

A series of FWD tests are usually preformed in order to obtain more accurate
results. Consecutive tests are conducted at regular intervals along a pavement surface. At
each interval four drops of the weight are conducted. The first drop is not used in
analysis, and the following three are averaged to create one set of data for each interval.
This allows for average values along the pavement to be calculated. Averages are taken
in order to capture the range of deflections as well as the most common values over a
pavement section. The variations in deflection are due to non-constant roadbed soils and
construction practices which often result in varying densities and thicknesses of the
pavement layers. A typical asphalt concrete (AC) surface can range from plus or minus 1
inch of thickness from the design thickness. This can affect MR results because a ,
constant layer thickness and Poisons’ ratio is used for the entire pavement section tested.
An example of how measured deflections at each sensor vary along a pavement section is
shown in Figure 2.8.

The KUAB brand FWD is used by several state agencies, including MDOT and
other agencies around the world; the device can be seen in Figure 2.9. The system applies

a dynamic impulse load to the pavement surface with a two mass system that simulates a

22

 

 

 

 

20* 7 7 7 7 I
‘ +Oinch :I
II E315 -E‘—81nch I‘I
; E +12inchjl
I .§ 10 ‘—°-l8inchl:i
I g I-I-24inch“
‘ ES l—e—361nchII
I 5 If69i1101h}
I l
I 0 I I
l 5 15 25 35 45 55 65 3
I Interval I

Figure 2.8 Typical deflections at all sensors
moving tire load. Seismometers set at specific distances along the pavement surface
measure acceleration and double integrate to determine vertical deformation or
deflection. The entire system is housed in a trailer and can be operated remotely from the

truck cab, which allows for quick and easy execution of tests in any weather.

 

Figure 2.9 KUAB falling weight deflectometer

23

2.5 Backcalculation of Layer Moduli of Flexible Pavement

Flexible pavement layer moduli are backcalculated using deflection data from
FWD tests. Deflection data is analyzed using computer programs to iteratively forward
calculate deflection based on layer moduli, Poisson ratios, and thicknesses and load
magnitude. Then the layer moduli are incremented until the calculated deflection is very
close to the measured deflection. When the absolute or Root Mean Squared (RMS) error
between the measured and calculated deflection is minimized results are the most
accurate. There are 5 categories of assumptions that have been used to create the various
computer programs; linear elastic-static, nonlinear elastic-static, linear-dynamic using
frequency domain fitting, linear-dynamic using time domain fitting, and nonlinear-
dynamic (Uzan 1994). Each category utilizes different assumptions and techniques.
2.5.1 Backcalculation Methods for Flexible Pavement

The roadbed soil modulus can be determined by using the pavement surface
deflection measured at distances of 48-inches or more from the center of the load.
Because of arching effects, at these distances, the pavement surface deflection is
influenced mainly by the roadbed soils. Hence, the subgrade MR can be backcalculated
from a single deflection measurement. The most widely used routine to backcalculate the

subgrade MR from a single deflection measurement is the Boussinesq equation (George

 

 

2003).
CP(1—v2) CP(1—UZ)
dr : 01’ MR: E tion26
mMR 71rd, qua '
Where, dr = the surface deflection (in) at a distance r (in) from the load

P = applied load (lbs)

24

C = correlation/adj ustment factor that accounts for the difference between
the backcalculated and the laboratory obtained MR value
MR = resilient modulus (psi)
v= poison’s ratio of the asphalt layer
By assuming a Poisson’s ratio of 0.5, equation 2.6 can be reduced to the following

equation (AASHTO I993).

_ 0.24CP

MR -
Equation 2.7
drr

AASHTO recommends the use of a C value no greater than 0.33

The minimum distance (r) in Equations 2.6 and 2.7 is given by the following relationship.

 

3 E”
r207 512+ DX E 7 Equation2.8

Where, a2 = radius of load plate (in)

D = total thickness of pavement layers above the roadbed (in)

Ep = effective modulus of all layers above the roadbed (psi)

Ep in equation 2.8 can be calculated by using the following equation:

f N

 

 

 

 

 

 

l
1— 2
II
1+ —
MRxdo 1 a
———=l.5< + >
q X a D E 2 E p Equation 2.9
1+ —3,I—i —
a MR MR

25

Where, do = deflection measured at the center of the load plate after adjustment to

a = temperature of 68 0F
q = pressure on load plate

D = total thickness of pavement layers above the subgrade

Ep = effective modulus of all layers above the subgrade

The Washington State Department of Transportation (WSDOT) developed, for
asphalt pavements, Equations 2.10 through 2.12 and, for concrete pavements, Equation
2.13 to estimate the subgrade modulus from deflection sensors located at various

distances from the center of the load (Pierce 1999).

 

MR (psi) = 9000 92322— Equation 2.10
24d 24
MR (psi) 2 —466 + 9000 Fifi/93 Equation 2.11
36
MR (psi) 2 —198 + 9000 0'030567 Equation 2.12
48

And for concrete pavements,

MR (psi) 2 —111+ 9000M Equation 2.13
48

Where, d24, d36 and d48 are the pavement surface deflections in inches measured

at 24, 36, and 48 inches from the center of the load.
There are several different computer programs that utilize the before mentioned
backcalculation methods, each with varying assumptions, routines, and methods. Table

2.4 below lists many ofthe available backcalculation programs.

26

 

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28

2.5.1.1 MICHBACK
The program for backcalculation of layer moduli of flexible pavement used in this report
is MICHBACK, developed at Michigan State University (MSU). The MICHBACK uses
the Chevronx (a multilayer elastic program) as the forward engine to calculate the
pavement deflections for a given set of data (layer moduli and Poisson ratios, layer
thicknesses, and load magnitude). The MICHBACK program utilizes a modified
Newtonian algorithm to increment the layer modulus values based on the differences
between the measured and the backcalculated pavement deflections (George 2003).

A brief summary of the MICHBACK program is presented in below. A detailed
flow-sheet can be found in (Mahmood 1993).
1) Input initial data (pavement location, file name, layer information, etc...)
2) Upload FWD file, or manually input deflection data
3) Input modulus seed values and stiff layer depth
4) Perform backcalculation
5) View or print results

MICHBACK uses a linear-elastic model, as mentioned previously. In order for
the program to work correctly, and converge, the deflection basin must be uniform with
an elastic system. The main contributing factor leading to non-convergence is the degree
of irregularity of the deflection basin. For the backcalculation of layer moduli to be
successful, the shape of the deflection basin must be smooth and compatible with the
elastic layer theory. Highly irregular measured deflection basins (such as that shown in
Figure 2.10) cannot be matched to that calculated using the layer elastic theory.

Irregularities in the deflection basins could be caused by an uneven contact between one

29

or more deflection sensors and the pavement surface, debris (such as sand particles)
between the deflection sensors and the pavement surface, and/or cracks or other structural
distresses in the pavement that adversely impact the continuity of the stress dissipation

with depth and distance from the load.

Lateral distance from load (inch) 1

 

  
   

00 0\ -§ N O
l
l
l
l
l
l

m

  

l

Deflection (mil) '

fl
0

 

v—d
N

 

 

14 * ' i

+ Regular-5+ 3:01am

Figure 2.10 Regular and irregular deflection basins

2.5.2 Flexible Pavement Temperature Effect on Resilient Modulus

The Asphalt Concrete (AC) layer MR of a pavement system is greatly affected by
temperature. It is common for the temperature of the AC layer to vary by 30° F in a given
day. This temperature fluctuation can result in a 500,000 psi variation in AC MR, which
will significantly affect the MR of other pavement layers when backcalculating. The ideal
AC temperature for FWD testing is between 40° and 100° F. It can be difficult to
backcalculate AC stiffness when the MR is above 2 million or below 200,000 psi,
therefore flexible pavements should only be FWD tested within the recommended

temperatures (Kathleen et al 2001 ).

3O

A procedure was developed by (the Asphalt Institute 1977) to correct for
temperature of AC pavement layers. This process requires the following data: The high
and low temperature for the previous 5 days leading up to the NDT, pavement surface
temperature at exact time of NDT, frequency of loading and time duration of load
impulse, as well as percent asphalt content by weight. If all of this data is available, then
AC temperature at the top, middle, and bottom of the layer can be determined, and the
mean of the three temperatures is used as the corrected pavement temperature.

2.5.3 Depth to Stiff Layer Effect on Resilient Modulus

Roadbed soil is assumed to be uniformly stiff and infinitely thick, when using
linear elastic models such as the one utilized by MICHBACK. This assumption is
incorrect as roadbed soil tends to become denser with depth, due to stress increases. At
some depth a “stiff layer” will be present, which can be composed of either bedrock or a
very dense layer of roadbed soil. To account for this, an additional layer is incorporated
in the backcalculation procedure. A stiff layer can be included in several ways:

0 Assignment of a very high modulus to the lowest layer in the pavement system;
however the depth to this layer will be unknown.

0 Assignment of a 20 ft. depth to stiff layer for all FWD analysis (Bush 1980).

0 Use of measured velocity of compression waves and frequency of loading (Uddin et
all986)

0 Application of trial and error method carried out until a minimum RMS error is
reached (Chou 1989).

The above mentioned methods make various assumptions about depth, which is

often unknown. Regression models have also been developed to estimate depth to stiff

31

layer from deflections and layer thicknesses (Brown 1991). This method is used in
MODULUS and EVERCALC, but does not accurately predict depth for medium to deep
layers (Rohde and Scullion 1990; Mahoney et al 1993). The MICHBACK program uses a
regression equation developed by (Baladi 1993) which iteratively improves the depth as
described in (Mahmood 1993).
2.6 Backcalculation of Layer Moduli of Rigid Pavement

The modulus of subgrade reaction (k) can be determined from deflection testing
conducted at the center of a Portland Cement Concrete (PCC) slab. An empirical set of

equations known as the AREA method can be used to backcalculate k as well as the

elastic modulus (EC) of the concrete. Correlation equations have been developed to

convert k to MR (AASHTO 1993).
2.6.1 Backcalculation Methods for Rigid Pavement

The AREA method for calculating the radius of relative stiffness and dynamic
foundation k is presented in this subsection. A summary of various other methods can be
found in (Sessions 2008).

The method for backcalculation of layer moduli of rigid pavement used in this
study is based on (Frabizzio 1998). The method is based on calculating the area of the
deflection basin, the radius of relative stiffness (l), the elastic modulus of the concrete
(EC), and the modulus of subgrade reaction using the measured deflection data as shown

in equations 2.14 through 2.18.

 

5 5 5 6, c5 5
AREA: 4+6 —-8- +5 —12 +6 3 +9 ~4 +18 _39_ +12 fl
5, 50 5, 5, 50 0
Equation 2.14

1

Where,

2.566

 

6O — AREA
N( )4" 0-698) Equation 2.15

 

289.708
_12(1— v2)P125:
C _ 5 h3 Equation 2.16

6: = a exp[_bexp(_d)]

Equation 2.17

E6113
: 12(1— v2 )14 Equation 2.18

AREA = deflection basin area, inches

k

 

. . th .
(5,. = deflection of the r sensor, inches

1: radius of relative stiffness, in

EC = elastic modulus of the concrete, psi

1.) = Poisson’s ratio for concrete = .15

P = FWD load, pounds

*
6‘ ,9

or = non-dimensional deflection coefficient at distance r

h = concrete slab thickness, inches
(1, b and c = regression coefficients (see Table 2.5)

k = modulus of subgrade reaction, pci

AREA is the cross-sectional area of the deflection basin between the center of the

FWD load plate and the outer most deflection sensor. The radius of relative stiffness (l)

characterizes the stiffness of the slab-foundation system. It should be noted that the final

33

*
Table 2.5 Regression coefficients for 5r

 

 

 

 

 

 

 

 

Radial Distance, r a b 0
(inches)
0 0.12450 0.14707 0.07565
8 0.12323 0.46911 0.07209
12 0.12188 0.79432 0.07074
18 0.11933 1.38363 0.06909
24 0.11634 2.06115 0.06775
36 0.10960 3.62187 0.06568
60 0.09521 7.41241 0.06255

 

 

 

 

 

 

elastic modulus of the concrete slab is the average of the seven elastic modulus values
(one for each deflection sensor) obtained from equation 2.17 (Frabizzio1998).

Equation 2.19 is used in the AASHTO pavement design guide to convert k into
MR.

MR 2 k * 19.4 Equation 2.19

2.6.2 Rigid Pavement Temperature Effect on Resilient Modulus

Temperature can play a huge roll in the accuracy of deflection testing of concrete
pavements. A concrete slab experiencing a temperature gradient can curl and come out of
contact with the underlying material. Curling is more likely to occur on slabs supported
by hi gh-stren gth stabilized bases than those supported by soft bases. To avoid possible
slab curling, testing the middle of the slab should be avoided during the day when the
surface is hotter than the bottom of the slab and upward curling is taking place. Likewise,

testing the comers and edges of the slab should be avoided at night when the slab surface

is colder than the bottom of the slab and downward curling is taking place (Kathleen et a1

2001).

34

2.6.3 Slab Location Selection for N DT

Conducting NDT at different positions on a PCC slab can be done to test for
different pavement properties and conditions. Discussion of mid—slab, edge, and corner
slab loading follows.
2.6.3.1 Mid-Slab Loading

The middle of the slab, in the outer lane, is usually where FWD tests are
conducted for backcalculation of roadbed k-values. An infinite horizontal layer is
assumed when considering rigid pavements, due to the evenly distributed load under a
loaded slab. However, the standard 12-fl highway lane width is smaller than that required.
for the assumption of an infinite horizontal layer, but this is ofien ignored. The middle of
the slab is tested to create the largest distance from pavement joints and edges, and from
any distresses at these locations (Kathleen et a1 2001).
2.6.3.2 Joint Loading

Loading near the joint of a concrete slab is usually done to calculate load transfer
efficiency (LTE). One sensor can be placed on the loaded slab and all others on the
unloaded slab. The ratio between the approach and leave slab deflection is used in
calculation of LTE. The deflection measured from the 60-inch sensor can be used for
roadbed MR backcalculation (Kathleen et al 2001).
2.6.3.3 Edge Loading

Loading the edge of a concrete slab is done to estimate the slab support to its
adjacent structure, shoulder, or lane, as well as the presence of voids underneath the slab.

This testing location is not normally used for backcalculation purposes.

35

2.7 Comparison of Backcalculated and Laboratory Determined MR Values

A brief summary of the comparison between backcalculated and laboratory
determined MR value is presented in this section. The detailed comparison can be found
in (Sessions 2008).

The primary purpose of establishing relationships between backcalculated and
laboratory determined MR values are for pavement overlay design. The MR values are
stress dependent. Therefore, in order to compare the different modulus values, the stress
state in which the FWD test was performed must be known (George 2003). However, the
grain size distribution, water content, saturation, dry unit weight, and other factors are
often unknown in FWD testing. For this reason, it is very difficult to compare
backcalculated to laboratory determined MR values.

Whether the backcalculated or laboratory determined MR of the roadbed soil is
used in the pavement design and analysis depends on the input required for the model
being used. For example, the original American Association of State Highway Officials
(AASHO) road test was calibrated to the laboratory MR of the soil present at the test,
clay. Therefore, when using the 1993 AASHTO pavement design or overlay procedures
the appropriate input for the roadbed soil is the laboratory MR (AASHTO 1993).

In many other cases, MR values obtained from laboratory tests may be
considerably lower than the backcalculated MR values. This is due largely in part to
differences in the magnitudes of the deviatoric stress, confining pressure, and loading rate
(George 2003). Similarly, field MR values for fine grained soils, obtained by
backcalculation from FWD deflections, have been reported in a number of studies to

exceed the laboratory MR values by factors between 3 and 5 (AASHTO 1993).

36

Several correlations have been developed to compare backcalculated and
laboratory determined roadbed MR values. These correlations identify and allow
correction for various factors which can lead to inflated or deflated MR values. Another
study found similar results when layer theory was employed for the analysis of the stress
state under a 9000 pound FWD load. It was found that a reasonable correlation exists
between FWD backcalculated moduli and the laboratory moduli based on the in-situ

conditions with identical stress states (Ping et al 2002).

The FWD backcalculated moduli were about 1.65 times higher than the laboratory

MR. This ratio is in agreement with the suggestion by the AASHTO design guide
(AASHTO 1993), which suggests that the FWD backcalculated moduli are
approximately two to three times higher than the laboratory determined moduli. It must
be remembered to consider that the AASHTO relationships were based primarily on clay
soils. In addition, for this comparison the FWD tests were performed under in-situ soil
conditions and the laboratory determined MR were obtained from the reconstituted soil
samples; simulating the in-situ moisture and density conditions under identical stress
states. The possible causes for the difference between the lab MR and backcalculated
values as reported in the study (Ping et a] 2002) were:
0 The FWD backcalculation program is based on the assumption of linear elastic theory

of multiple layer pavement structures, while the pavement materials are not purely

elastic.

37

o The FWD backcalculation method does not lead to a unique solution; therefore,
different layer moduli could be obtained from the same FWD data.

0 The lab specimens were tested almost immediately after they were compacted, and
the confining pressure for the triaxial test was applied by air; the in—situ soil had been
there for many years, and the confining pressure was caused by vertical load and soil
weight.

Von Quintus and Killingsworth (1998) reported that, for unbound granular
materials, the ratio of the backcalculated to the laboratory determined MR ranged from
0.1 to 3.5. They stated that the reasons for the differences between the backcalculated and
the laboratory determined MR values are related to the inability to simulate the in—situ
boundary conditions in the laboratory.

2.8 Seasonal Changes

Pavement layers have varying properties and characteristics dependant on the
time of the year. Pavements residing in areas that undergo freeze-thaw cycles are subject
to seasonal effects. A pavement system can become very weak during the spring thaw
season, then rapidly recover strength leading into summer, slowly recover over the
summer and fall, and then reach a maximum stiffness when frozen during the winter
(Shepherd and Vosen 1997). A typical annual range in deflection is shown in Figure 2.11.
2.8.1 Spring Season

During the winter season, un-drained water within the pavement, along with water
from shallow water tables, can freeze and create ice lenses. Due to this, the surface can
experience frost heave. When the spring season begins, and the lenses start to melt, the

pavement layers can become saturated if not properly drained. Also, additional water can

38

01
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‘ 'r "' 'r ‘ thaw" ‘recovery"
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E Pavement
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3‘,
I:
.9
E 20 'i
‘5
o
10 -
Pavement structure
frozen
0 t a t i t : t 1
Aug Sept Oct Nov Dec Jan Feb Mar

Figure 2.1 1 Typical pavement deflections illustrating seasonal pavement strength changes
(PTC 2008)

enter the system from rain and snow melt. All pavement layers can experience a
reduction in bearing capacity as a result of this. It is estimated that 90% of damage to
pavements occurs during the spring thaw season (J anoo and Greatorex 2002). A diagram
showing the formation of ice lenses can be seen in Figure 2.12.
2.8.2 Summer Season

The summer season is considered to start after the conclusion of the spring-thaw
season which is defined by the time when moisture conditions, within the pavement
system, return to normal and the ambient temperatures begin to rise. The date when this
occurs changes from year to year and from location to location. The summer-fall season
ends when the ground starts to freeze, but is often considered to last until the spring-thaw
season begins and the ice starts to melt. In Michigan, summer season is typically from

May to December.

39

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Figure 2.12 Formations of ice lenses in a pavement structure (PTC 2008)

Distribution of Resilient Modulus of Roadbed Soils in the State of Michigan

The entire state of Michigan is within the North American glaciated section. This

implies that all soils have been deposited by glaciers. The action of the moving glaciers

pulverized soil and bedrock while moving south, and then re-deposited the soil upon its

melting and retreat. This created the topography of the state as well as the locations and

variations of Michigan’s soils. Within the state, 165 different soil classifications can be

40

found. This includes everything from clay to boulders, and combinations throughout
(MDSH 1970). All of these various classifications of soil deposited by glacial drifts can
have different MR values and need to be classified and distinguished.

2.9.1 State Partitioning

A brief summary of the state partitioning process is presented in this subsection.
The detailed process can be found in (Sessions 2008).

To characterize the resilient modulus of the glacial drifts in an economical and
practical manner, the State of Michigan was divided into 15 clusters where the soil in
each cluster has similar engineering and physical characteristics. The boundaries of the
15 clusters were established based on the 1982 Quaternary Geology map of Michigan,
inputs from members of the Research Advisory Panel (RAP) of MDOT, and inputs from
the soil engineers in the various MDOT Regions. After establishing the cluster
boundaries, each cluster was divided into areas based on the percentages of each soil type
found in the Natural Resources Conservation Service (NRCS) Web Soil Survey (Web
Soil Survey 2007). Once again, the boundaries of each area were slightly modified based
on inputs from the RAP members and from the soil engineers in the various MDOT
Regions. The final state divisions consisted of 99 areas within the 15 clusters. Figure 2.13
depicts the boundaries of the clusters shown by the dashed lines and the boundaries of the
99 areas shown by the solid lines. Once again it should be noted that the division between
the clusters was based on similar (not the same) soil types whereas the boundaries
between the areas were based on narrowing the range of the soil parameters within each

cluster.

41

 

 

 

 

 

 

Figure 2.13 Areas and clusters of the State of Michigan

42

 

 

 

 

 

 

 

 

 

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Figure 2.13 (cont’d)

After dividing the State of Michigan into 15 clusters and 99 areas, the percent of
each soil type (sand, clay, silt, etc) in each area was quantified from the Natural
Resources Conservation Service (NRCS) Web Soil Survey (Web Soil Survey 2007).
Table A.1, in Appendix A, lists the percentages of each soil type in each of the 99 areas.
2.9.2 Soil Sample Collection

Of the 99 areas listed above, 75 have had disturbed soil samples collected from
near the roadway. Areas with similar soils to each other were lumped together, for
economic reasons, and only one sample was collected to represent both areas. The soil
samples were analyzed at Michigan State University (MSU) for natural moisture content,
Atterberg Limits (liquid and plastic limits and plasticity index), grain size distribution

(wet and dry sieving and hydrometer analysis), and cyclic load triaxial tests.

45

CHAPTER 3

LABORATORY & FIELD INVESTIGATION

3.1 Introduction
The objectives of this study were achieved by carrying out several field and

laboratory investigations. These investigations include:
0 State partitioning
0 Soil sampling
0 Laboratory tests which consist of:

0 Moisture content

0 Sieve analysis (wet and dry sieving)

o Hydrometer analysis

0 Atterberg limits (liquid and plastic limits and plasticity index)

0 Cyclic load triaxial test
0 Field tests which consist of:

o Penetration resistance using pocket size penetrometer

o Shear strength using pocket vane shear tester

o Deflection using Falling Weight Deflectometer (FWD)
3.2 State Partitioning and Soil Sampling

The state was divided into 15 clusters and 99 areas as discussed in subsection

2.9. 1. At every location (75) where a disturbed soil sample was collected, as discussed in
subsection 2.9.2, penetration resistance and vane shear tests were conducted on site. The
roadbed soil samples were taken to the Geotechnical laboratory at MSU for further

testing. In addition to the disturbed soil samples, 10 undisturbed (Shelby tube) samples

46

were collected by MDOT and taken to the laboratory at MSU for testing. State
partitioning and soil sampling is discussed in detail elsewhere (Sessions 2008).
3.3 Laboratory Tests and Procedures

All 81 disturbed soil samples, as well as the 10 Shelby tube samples were
analyzed in the Geotechnical Laboratory at MSU. Each sample was subjected to a battery
of tests to determine its moisture content, particle gradation, Atterberg limits, soil
classification (both USCS and AASHTO soil classification system), and MR. A brief
description of each test administered follows, a full explanation of each test can be found
in (Sessions 2008).
3.3.1 Moisture Content, Particle Gradation, and Atterberg Limits

All 81 soil samples collected underwent natural moisture content, particle
gradation (dry and wet sieve and hydrometer), and Atterberg limit analyses. The
following standard test procedures were followed:
0 Moisture content analysis - ASTM C 29
0 Dry sieving - ASTM C 117
0 Wet sieving - ASTM C136
0 Hydrometer analysis - AASHTO T 88
o Atterberg limit analysis - AASHTO T 89

A detailed review of the tests and their effects on the MR values can be found in
(Sessions 2008).
3.3.2 Cyclic Load Triaxial Test

Cyclic load triaxial tests were conducted to determine the resilient modulus of

laboratory compacted sand and clay samples as well as Shelby tube samples. The sand

47

samples were compacted in a split mold by vibration and static load. The clay samples
were compacted according to AASHTO standard proctor test procedure T99 and then
trimmed to the correct diameter. Shelby tube samples were simply cut into sections of
proper length. All samples were contained within a rubber membrane. All cyclic load
triaxial tests were mainly conducted according to the AASHTO T307 standard test
procedure. Because of the type of tests and equipment available some modifications to
the procedure are detail in (Sessions 2008).

Cyclic load triaxial tests are difficult to conduct and require extreme care and
patience. The resulting MR values obtained from the test are typically affected by several
test and sample variables including: confining pressure, deviatoric stress, loading
frequency, soil type, moisture content, and specimen conditioning.

3.4 Field Tests

Several thousand deflection tests using Falling Weight Deflectometer (FWD)
were conducted and analyzed during this study. In addition, all 81 disturbed soil samples
were tested in the field using pocket penetration resistance and vane shear testers.

3.4.1 FWD Tests

In this study, all NDT were conducted by MDOT personnel using the MDOT
KUAB FWD. The weight and the height of drop for all NDT were adjusted to produce
9000 pound load. For each test, the pavement surface deflections were measured at the
distances of 0.0, 8.0, 12.0, 18.0, 24.0, 36.0 and 60.0-inch from the center of the loaded
area. To analyze the roadbed soils of the entire state FWD tests must be conducted on the
entire state road network. MDOT has been conducting FWD tests for over 20 years and

has collected deflection data from most of the state road network. A total of five hundred

48

five data files were obtained from MDOT and scrutinized for possible inclusion in the

backcalculation of the roadbed modulus. All data files were tested relative to the

information available in the data file and. MDOT records. All files that passed the tests

were included in the analysis. The tests consisted of the following:

o The FWD data files contain the proper date and location reference information.

o The pavement type and the pavement cross-section data at the time of the FWD tests
are available in (and can be obtained from) the MDOT project files and records.

0 The FWD tests were conducted on Interstate (1), United State (US), and/or Michigan
(M) roads.

0 The FVW) tests were conducted on either flexible or rigid pavement types (composite
pavements were not analyzed).

One hundred one FWD data files containing six thousand two hundred forty six
FWD tests satisfied the above requirements, and therefore they were included in the
analyses. These files were examined to determine the NDT test locations (see solid
squares in Figure 3.1). The tests were conducted along twenty one roads (eleven M roads,
six I roads, and four U.S. roads) spanning twelve clusters and thirty two areas. Table 3.1
shows the distribution of the FWD data files by pavement type (flexible or rigid
pavement) and by roadbed soil USCS.

As can be seen from the Figure 3.1, certain areas of the state lack sufficient NDT
tests. Hence, 217 additional FWD test sites were requested from MDOT to fill up the gap
and to cover different environmental seasons (see open squares and triangles in Figure
3.1). Due to several constraints, the number of requested FWD tests was reduced several

times. Finally, 56 additional FWD tests were conducted spanning fifteen roads (four M

49

Table 3.1Distribution of old FWD files

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Rigid pavement Flexrble Total
pavement
Files Tests Files Tests Files Tests
USCS Total 295 - 140 - 435 -
Usable 64 4,684 3 7 1,562 101 6,246
SM 6 244 1 79 7 323
SP1 9 494 22 1,027 31 1,521
SP2 8 575 2 67 10 642
SP-SM 9 379 0 0 9 379
SC-SM l. 1 1,967 0 0 11 1,967
SC 19 941 12 389 31 1,330
CL 2 84 0 O 2 84
ML 0 0 0 0 0 0

 

 

 

 

 

 

 

 

 

roads, four I roads, and seven U.S. roads) in eleven clusters and nineteen areas by
MDOT; the locations of these tests are indicated by the open triangles in Figure 3.1, and
detailed in Table 3.2.

The deflection data from the existing FWD files and from the new FWD tests
were used to:
o Backcalculate layer moduli of flexible and rigid pavements
0 Evaluate the variability in roadbed soil MR along and across the pavement network
0 Study roadbed soil MR as a function of soil type
0 Assess the seasonal effects on roadbed soil MR
The results of these analyses are presented and discussed in chapter 4.

Analysis of seasonal effects on roadbed soil MR could not be accomplished due
to a lack of deflection data reflecting spring conditions. FWD tests were not performed

during the spring season in this study due to equipment breakdown and MDOT limited

f6SOLlI'CCS.

50

 

 

  
 

 

I Previous FWD test locations
A New FWD test locations

0 Requested FWD test locations

 

 

Figure 3.1 FWD test locations in the State of Michigan

51

 

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52

 

 

 

 

 

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st locations
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I Previous FWD te

 

 

 

Figure 3.1 (cont’d)

 

 

 

   

CA New FWD test locations
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Figure 3.1 (cont’d)
3.4.2 Penetration Resistance and Vane Shear Test
Penetration resistance and vane shear tests were conducted in the field using hand
held devices in order to capture in-situ conditions. The tests were conducted by
measuring the soils penetration resistance using pocket penetrometer, and the shear
strength resistance using pocket size vane shear tester. The results and analyses of these

tests are discussed in (Sessions 2008) and can be seen in Table A2 of Appendix A.

54

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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57

CHAPTER 4

DATA ANALYSIS & DISCUSSION

4.] Analysis of Laboratory Test Data

A brief summary of the analysis of the laboratory test data is presented in the next
two subsections. The detailed analyses can be found in (Sessions 2008).
4.1.1 Soil Classification

For each soil sample, the natural water content, the dry and wet sieve, the
hydrometer, and the Atterberg Limits tests data were obtained and are listed in Table A.3
of Appendix A. The data were used to classify the soils according to the USCS and the
AASHTO soil classification system. Results of the classification are also listed in Table
A.3 of Appendix A. As can be seen in the table, the roadbed soils in the State of
Michigan were divided into eight soil types according to the USCS; SM, SP, SC, SP—SM,
SP-SC, ML, CL, and GW.
4.1.2 Cyclic Load Triaxial Test

For each disturbed and Shelby tube soil sample, at least one cyclic load triaxial
test was conducted. In all tests a confining pressure of seven and a half psi, a sustained
load of ten pounds and cyclic stresses of ten and fifteen psi were used. Some of the test
parameters and the test results (the resilient modulus at load cycles 100, 200, 500, 800,
and 1,000 and the average resilient modulus of at load cycles 500, 800, and 1,000) for
each cyclic load are listed in Tables A.4. Table A5 lists the sample parameters and the
average resilient modulus for the ten and fifteen psi cyclic stresses. For each soil type, the
average resilient modulus value at load cycles 500, 800 and 1000 Was correlated to the

soil physical parameters (moisture content, particle gradation, coefficient of uniformity,

58

coefficient of curvature, liquid limit, plastic limit, plasticity index, dry density, percent

passing certain sieves, degree of saturation, penetration resistance, and vane shear

strength) using univariate and multivariate statistical analyses. Results of the analyses

(the correlation equations) for all eight soil types are listed in Table 4.1.

1.

Three important points should be noted herein are:
For the SC, CL, and ML soil types; similar trend between their parameters and MR
values was found. Therefore, in the analyses they were grouped together.
For the SP soils, two distinctive trends between the MR values and the soil
parameters were found. Hence, the SP soils were divided into two groups SP1 (the
soil samples were obtained from the west side of the State of Michigan) and SP2 (the
soil samples were obtained from the east side). The main difference between SP1 and
SP2 is the course sand content. On average, the SP1 soil contains 90 percent passing
sieve number 40 whereas SP2 soil, 50 percent.
As can be seen from table 4.1, the predictive equations apply to one or more soil
types according to USCS. For example, the SP—SM soil has one predictive equation.
Since for this soil, the AASHTO soil classification system yields three types of soil
(A-l-b, A-2-4, and A-3), the USCS was used throughout the remainder of this thesis.

Two sets of additional cyclic load triaxial tests were conducted. The MR values

and the sample parameters of both sets of tests were used to verify the MR predictive

equations presented in Table 4.1. The results of the first set of additional tests are shown

by the open squares in Figures 4.1 through 4.4. The results of the second set of tests, on

the other hand, are shown by the open triangles in the figures. As can be seen from the

figures, the results of both sets of tests are located relatively close to the solid curve

59

 

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- 30.000 3 - ~ > fMR=45722e 0.0258(M){ ‘
'5 ‘ 2-
3; 25,000 . R —0.8847 , 7 ,7 ‘
'5 20,000 - A ,. g -- 3 ,—, .2 L 3 -3 ‘
'0 ‘ , .
° 2 .
E 15,000 -, . .__ _ __ ||
5 i
:5 10,000 — . ,, g 1
t ,
5.000— , _- _ , .
l 1
0 1 i
i
0.00 20.00 40.00 60.00 80.00 100.00

Moisture Index (MI)

Figure 4.l MR versus moisture index (see table 4.1) for the SM soils

5 SM gerifiéaion C A New Verification? I

 

35,000 . y a
30,000 ,, 7 ..__..-: ._! _._ T- __ L .

J I i
25,000 . . , L-) L ,
20,000 * I 7 6 l 3 _ l

    

Resilient modulus (psi) '

 

 

 

 

15’000 ‘ ”" ‘ .‘:-:,_‘ l L, l

l 9 1 0 0.1742 SVSM l !

10,000 ‘* [jl‘MR=231.24e ( ), I

’ l i 2_

5,000 #0 a R —0.7439 1 , 3
i j 3 . SE = 1,482

0 ’5 t 1 i

18.00 20.00 22.00 24.00 26.00 28.00 30.00 i.

SVSM

Figure 4.2 MR versus the SVSM (see table 4.1) for the SM soils

61

    

  
   

45,000 - ~ . ~ . ~ ~ ~~ 2 ~~
’ 40,000 ‘ - -. a 1
E? 35,000 L13 |~
; :3 30,000 J i 2 ‘
‘ '3 1, . ~ _
-, 520,000 3 ~ * ; + +0 ,;:1 1251”: 1 y
. .353 15,0001 , -1 , .1MR=0.8295(SVSP2)A(3.6006)‘. 4, 1
* '3 10,000 ? _, 2 - .; , R2=O.8106 1 2, 1
5,000 - - e- 2 3 5.13:3’141 12 , 1
0 , ~ 2 ,, +4 ,. » — e 2, 1
12.000 14.000 16.000 18.000 20.000 22.000 ?
SVSP2
Figure 4.3 MR versus SVSP2 (see table 4.1) for the SP2 soils
0 0 Model CIVerification ANew Verification:
80,000 . - , 44444 1T 1 ,
1 1 , 1 AL LL 2
- 70,000 is 6%; ‘ 1 MR=650486e(-0.0501(S))“* .
a 60,000 , 1 , 1 , . . R2=0.8782 1" 1
E 50000 1 SE=5’081 ~' 1
a 40,000 i
g 30,000
‘0 20,000 '1 1
6‘2 ,
10,000 = . 1
1 1
0 1 ~ , A 1 4.444--— —m1
40 50 6O 70 80 90 100 1

Degree of saturation, S (°/o)

Figure 4.4 MR versus the degree of saturation (S, see table 4.1) for the SC, CL and ML

soils

62

representing the predicted MR values. This implies that the MR predictive equations for
the SM, SP2, and ML soils are reliable and relatively accurate. It should be noted that the
correlation equation and the values of R2 and standard error (SE) stated in Figures 4.1
through 4.4 were obtained based on the original data. When the additional data from the
verification tests were included, the values of the statistical parameters of the equations
were changed, and the values of R2 and SE decreased.

Nevertheless, the results of the second set of additional cyclic load triaxial tests
(verification tests) were also used to assess the impact of the applied stress boundary
conditions and the sample moisture contents on the MR values of the test samples. These
results are discussed in Section 4.4.

4.2 Backcalculation of Layer Moduli

As noted in Chapter 3, all existing FWD data files for flexible and rigid pavements were
requested and obtained from MDOT. The locations of these tests were marked on a state
map. Additional FWD test locations were then determined to fill the gap. Consequently,
MDOT conducted the FWD tests at the new locations. These along with the old FWD
tests provided good coverage of the pavement network in the State of Michigan (see
Chapter 3).

For each existing FWD data file, the test location reference was obtained and the
MDOT project files and records were searched to obtain the pavement cross-section data
that existed at the time when the FWD tests were conducted. All FWD test data where
pavement cross-section data were not found were eliminated from further analyses.

Each deflection basin in the remaining and new FWD data files was examined for

possible irregularities by plotting the pavement surface deflections as a function of

63

distance from the center of the applied load as shown in Figure 4.5. Irregular deflection
basins were removed and stored in different data files and were not included in the
backcalculation of layer moduli. For some FWD data files, as much as 75% of the

deflection basins were irregular while others didn’t contain any irregular basins.
Lateral distance from load (inch)
0 10 20 30 40 50 60

 

 

 

 

O I I A i
2 A i
f; 4 ,- i
E
z: 6 i
.2
8 +
c:
g 10 e
12 ,
14*

 

 

 

+ Regular -8- Irregular

Figure 4.5 Regular and irregular deflection basins

4.2.1 Flexible Pavement

For flexible pavements, the deflection data were used along with the appropriate
pavement cross-section data to backcalculate the pavement layer moduli using the
MICHBACK iterative computer program. The program, which was developed at
Michigan State University, uses the Chevronx computer program (a five layer elastic
program) as the forward engine to calculate the pavement deflections for a given set of
layer moduli, Poisson ratios, layer thicknesses, and load magnitude. The MICHBACK
program utilizes a modified Newtonian algorithm to calculate a gradient matrix by

incrementing the estimated layer modulus values and calculating the differences between

64

the measured and the calculated pavement deflection in three consecutive cycles. When

the convergence criteria (specified by the program user) are satisfied, the iteration

process stops and the final set of backcalculated layer moduli are recorded. In this study,
the following convergence criteria were used:

1. Modulus Tolerance — Maximum modulus tolerance (the difference between two
successive backcalculated modulus values) of 0.2 percent.

2. Root Mean Square (RMS) error - Maximum RMS error tolerance (the square root of
the sum of squared errors between measured and calculated deflections) of 0.2
percent.

The MICHBACK is a user-friendly computer program. The program was used
with some of the available default values (such as Poisson’s ratios for the various
pavement layers) when appropriate. The sensitivity of the backcalculated layer moduli
using the MICHBACK computer program to some of the input parameters is presented in
the subsection 4.2.1.1. Results of the backcalculations are presented and discussed in
subsection 4.2.1.2.
4.2.1.1 Sensitivity of the Backcalculated Moduli

The MICHBACK computer program is sensitive to some of the inputs used in the
backcalculation procedure. Several MICHBACK computer program sensitivity analyses
were conducted by forward calculating pavement response to applied loads with the
Chevronx computer program and then backcalculating layer moduli, from the calculated
deflection, with the MICHBACK computer program. The error between the layer moduli
used in forward calculation and the backcalculated layer moduli were than studied. The

analyses are discussed in this subsection.

65

Number of Layers - In all backcalculation of layer moduli of flexible pavements, a two
layer and roadbed soil system was used. The reason is that the objective of the
backcalculation is to determine the roadbed modulus only. The moduli of the asphalt,
aggregate base, and sand subbase layers were not included in this study. Hence, the
aggregate base and sand subbase layers were combined into one granular base layer. This
significantly decreased the number of iterations required to satisfy the convergence
criteria, and yet yielded more accurate roadbed modulus values. This procedure was
tested by using forward calculation of pavement response to applied loads and
backcalculating the layer moduli. It should be noted that a typical flexible pavement
section, in the State of Michigan, consists of three layers (asphalt, aggregate base, sand
subbase) and the roadbed soil, and the MICHBACK program is capable of handling a
total of five layers, including the roadbed soil. However, the accuracy of the
backcalculated moduli of a five layer system is questionable. Figure 4.6 illustrates the
effects of using three and four layered systems on the value of the backcalculated layer
moduli when combining the base and subbase layers. As can be seen in the figure, the
MR of the roadbed soiI is not affected much when a single granular base layer is used.
Therefore, the base/subbase combination is appropriate when backcalculating roadbed
soil MR.

Pavement Layer Thickness - The thickness of the pavement layers used in
backcalculation can have a significant impact on backcalculated MR values; especially
for the AC layer. Constant pavement layer thickness is used for each layer in the
backcalculation of layer moduli. However, due to construction practices the AC thickness

may vary +/- 1 inch from the average. Figure 4.7 shows that when the AC thickness is

66

*—E1— AC —e— Base +subbaééé3-33adbw

200

 

100 *

 

Percent error in pavement layer
MR '

 

 

-100 .
2 3 . 4 5

 

Ntunber of pavement layers

Figure 4.6 Effect of number of pavement layers

—B— AC —e— Base —A- Roadbed

 

 

 

 

 

 

Ex

2 400

8

>x

£3 300

a:

0.)

g 200

ES

2‘ 100

E 0 _
Q)

g -100

Si -40 -30 -20 -10 0 10 20 30 40 50

Percent error in AC thickness

Figure 4.7 Effect of AC layer thickness on MR
varied, to reflect possible conditions, the backcalculated AC MR is drastically affected,
while the other layers remain generally constant. The roadbed soil MR is more or less

unaffected by changes in the AC layer thickness.

()7

Similarly, Figure 4.8 shows that varying base thickness does not have much effect
on the backcalculated roadbed soil MR. However, the backcalculated MR of the base and

AC layers is affected by varying the base thickness.

g—B—Ac -e—Base -£x—Roadbed Z

 

 

 

 

 

 

% 120 . 1
g .
£3
.. 80
8
E
1 “3
1 c6 40 "
CL.
.5
‘g 0
CL)
‘5
fig 40
<1.)
e- -60 -40 -20 0 20 40 60

Percent error in base thickness

Figure 4.8 Effect of base layer thickness on MR
Stiff Layer - The effects of stiff layer depth are accounted for in the MICHBACK
computer program. In the analyses, the depth to stiff layer was estimated using Equations

4.1 and 4.2 of the Boussinesq equivalent modulus procedure.

Eo(0):2(l—,u2)aoxa

d(0) Equation 4.1

500141-4270va

r X db”) Equation 4.2

Where, E0(r) = surface modulus at a distance r from the center of the FWD loading plate

11 = Poisson’s ratio (0.5 assumed)

0,, = contact stress under the loading plate (82 psi)

68

d(r) = deflection at a distance r (inch)

a = radius ofloading plate (5.91 inch)

By calculating EO for each sensor in a deflection basin and plotting them against

the distance between the sensor and the load, four possible outcomes may occur.
Examples of the four outcomes are listed below and shown in Figures 4.9 through 4.12.
a) No stiff layer exists

b) A stiff layer at a shallow depth exists

c) A stifflayer at a deep location exists

(1) A soft layer at a deep location exists

Equivalent moduli (ksi)
0 5 10 15 20 25 30 35 40

 

I Distance from center of load (inch)

10 w
20
3O
40

50 *
60
70

 

 

 

 

Figure 4.9 No stifflayer
Based on the Boussinesq procedure, the depth to stiff layer is estimated and then
changed incrementally to minimize the root mean square error between the measured and
the calculated deflections. If the depth to stiff layer used in the backcalculation is not

relatively close to the actual depth, the MR of the roadbed soil can be greatly affected.

69

Equivalent moduli (ksi)

 

 

 

 

 

0 5 10 15 20 25 30 35
L. 0 ‘
..C‘.
Q
.3 10
1:: 1
3 20 1 ~
‘8
1.. 30
<1)
‘5
8 4O
8
gs: 50
8
g 60 —
'5 70
Figure 4.10 Stiff layer at shallow depth
Equivalent moduli. (ksi)

0 50 100 150 200

 

 

 

Distance from center of load (inch) '

 

 

70

Figure 4.1 l Stiff layer at deep location

70

Equivalent moduli (ksi)
0 5 10 15 20 ‘

 

N t—i
O O O
1

Distance from center of load (inch) '1 I
b)
o

.5
O

U]
C

 

O\
O
1

 

 

\l
O

 

Figure 4.12 Soft layer at deep location”

This procedure was tested by using forward calculation of pavement response to
applied loads and backcalculating the layer moduli. Figure 4.13 illustrates the effects of
errors in the estimated depth to stiff layer on the backcalculated MR values for four true
depths to stiff layer (100, 300, 500 and 700-inch). It can be seen that negative errors in
the estimates (shallower estimated depths) cause negative errors (decreases) in the MR
values and visa versa.

Figure 4.14 illustrates that the MR of the stiff layer has almost no affect on the
backcalculated layer moduli. To be considered a stiff layer the MR must be several
hundred thousand psi, and anything more stiff has nearly the same effect.

Roadbed Soil Seed Modulus - The MICHBACK begins its iterative process with a seed
MR value for each layer. Figure 4.15 shows that variation in the roadbed seed modulus

does not have much impact on the backcalculated MR values.

71

. -8- True depth to stiff layer of 100 inch -6- 300 -A— 500 -G- 700

 

 

 

 

 

 

 

 

 

 

 

 

 

' 33017
E 225
8
g 150
'8
E 75
.E
E 0 ~
0
E
8 -75
3 <
12..
-150 . 1 _
—100 0 100 200 300 400 500 600
Percent error in depth to stiff layer
Figure 4.13 Effect of stiff layer depth
'— “—— __,,,,,,,,,, __ . . ' — —' 1
-B-AC -e-Base -$-Roadbed 1 1
a: *W ’ " ’ 1
E 40 1
<13 1
a * 1 1
a 20 1 * ~ — *~ 1
Q) 1
1 1 1 1 1
8.. O 7.1 r % 1 a 1 B—‘
.s ‘ 1 ‘
S I
E _20 _ _ L ,L_.1
E .
8 1
3-4 L 1
Ga: '40 1 1
-60 -40 -20 0 20 40 60

Percent error in stiff layer MR

Figure 4.14 Effect of stiff layer MR

72

3-8- AC -e~ f ease; Roadbed:

.5
O

 

N
O

1

1

1

 

115
O
1
1

 

 

 

.18.
o

-60 -40 -20 0 20 40 60 80

Percent error in roadbed seed modulus

do
0

Percent error in pavement layer MR '
o
1

Figure 4.15 Effect of roadbed seed MR
The range of MR values specified is important, as the values used must be within
a reasonable range for each pavement layer. The minimum, seed, and maximum MR
values used in this study were:
0 AC = (minimum = 100,000, seed = 1,000,000, maximum = 4,000,000 psi)
0 Base = (minimum =10,000, seed = 50,000, maximum = 500,000 psi)
0 Roadbed = (minimum = 3,000, seed = 7,500, maximum = 100,000 psi)
4.2.1.2 Analysis of Backcalculated Data from MICHBACK
The accuracy of the backcalculated results were also verified in the following
ways:
0 After deflection data were backcalculated using the MICHBACK the data was
scrutinized to make sure that all results with greater than a 2% RMS error were
eliminated. A maximum RMS error of 2% was established for acceptance of the

backcalculated MR results because errors above this threshold are much less accurate.

73

o The deflection measured at the sensor 60 inch from the load most closely corresponds
to the deflection of the roadbed soil. This is due to the arching effects of soil as stress
is distributed downward and away from an applied load. The deflection measured at
sensors closer to the load (36 inch and less) are not as closely related to the MR of

roadbed soils. This is illustrated, in Figure 4.16 where the open triangles represent the

measured deflection at d60 and. the open squares represent the deflection measured at

d36. The R2 of the correlation between MR and d60 is much greater than that of d36,

as can be seen in the figure. Due to this relationship, the accuracy of the MICHBACK

results can be scrutinized based on the accuracy of the correlation between d60 and

the MR of roadbed soils.

 

1 -ADfiODDa6 1

 

 

60000

Resilientwmodulus (p81) '
N w 4:. m
o o o 9
§ § § §

 

 

 

 

 

0 0.5 1 1.5 2 2.5 3 3.5 4
Deflection at 60,3 6—inch from the load (mil)

Figure 4.16 MR vs. d60 and d36

o The deflection measured at the sensor 60 inch from the load is inversely proportionate

to the backcalculated roadbed soil MR. An increase in measured deflection

74

corresponds to a decrease in backcalculated MR and vise versa, as illustrated by

Figure 4.17. Due to this relationship, the accuracy of the MICHBACK results can be

scrutinized based on an observation of this trend.
Results - Only the backcalculated results of roadbed soil MR were further analyzed. The
raw results of base/subbase and AC MR are listed in Table B] of Appendix B, and will
be further discussed as part of the upcoming unbound material MR project. The average,
maximum, minimum, and standard deviation of MR of backcalculated roadbed soil
supporting flexible pavements are listed in Table 4.2, and the detailed results are listed in
Table 8.1. The full set of NDT data and backcalculated results of flexible pavements is

available on the accompanying compact disc.

2 A Resilient Modulus (psi) —E-;Deflection at 60-in h 1

50,000

 

1 :
1 4 A - 1
540,000 ” 'A f * A i“ A AA 1. 1 § 1
§ A .A AA 1 , 1 35 g
1 3 2222_ 2-144224. 2 -' ‘ 9-2 422223. 2 .ii ' w 1
1 330,000 A 11333 . AA A AAA” 5 1
1‘23 MA A44 AA A. Aj 211A .5
1 4.. 1 1 2.‘ i ‘ 2.5 3
5 20,000 , A: 'A . a: 1
1 fi 1! g
. g 10,000 " 1-5 ‘8 1
1 <8
1 D .
0 0.5 1

 

 

 

 

Station

Figure 4.17 MR vs. deflection

75

 

 

 

 

 

 

 

 

 

 

 

 

Roadbed MR results (psi)

type

USCS Average Maximum Minimum 3::
SM 22,976 32,319 16,115 3,373
SP1 30,707 70,138 13,154 7,562
SP2 23,042 28,602 19,243 3,036
SP-SM 21,292 30,666 15,623 3,740
SC-SM 18,989 31,218 7,088 6,541
SC 24,704 67,793 11,728 6,695
CL 20,100 28,849 1 1,996 4,326
ML 15,976 31,279 8,711 6,394

 

 

 

 

 

Table 4.2 Backcalculated roadbed soil MR supporting flexible pavement

4.2.2 Rigid Pavement

The rigid pavements layer moduli were backcalculated using the measured
deflection data and the empiricaI AREA method. The method uses the measured
deflection at 7 sensors and Equation 4.3 to estimate the parameter “AREA”, Equation 4.4

to calculate the radius of relative stiffness (l) of the concrete slab, Equations 4.5 and 4.6
to calculate the elastic modulus of the concrete (EC), and Equation 4.7 to calculate the
modulus of subgrade reaction (k) which can be converted into MR value using Equation

4.8 (AASHTO 1993). The following equations were repeated from subsection 2.6.1 for

the reader’s convenience.

 

 

AREA: 4+6 5&- +5 5'2 +6 55$ +9 .5221 +18 §‘_6 +12 _6_60_
60 60 0 0 60 0
Equation 4.3
2.566
60—AREA
I: N[ 289708 J/(_ 0698) Equation 4.4

76

6: = a eXP1—bexp(_d)]

= 12(1—1/21P125:

C 3 Equation 4.6
5,4

Equation 4.5

 

_ ECh3
— 12(1_ V2 y4 Equation 4.7

MR 2 19.4/C Equation 4.8

 

Where, AREA = deflection basin area, inches

. . th .
8» = deflection of the r sensor, inches

1 = radius of relative stiffness, inches

EC = elastic modulus of the concrete, psi

1) = Poisson’s ratio for concrete = .15

P = FWD load, pounds

it
6‘, 9,

5r = non-dimensional regression coefficient at distance r

h = concrete slab thickness, inches (use 9” if unknown)
(1 ,b, and c = regression coefficients (see Table 4.3)
k = modulus of subgrade reaction, pci
MR = resilient modulus, psi
Equation 4.8 was developed based on k values backcalculated from plate load
bearing tests. The tests were conducted to simulate a pavement system where the slab is

placed directly on top of the subgrade. The FWD tests in this study were conducted on a

77

I.

II.

*
Table 4.3 Regression coefficients for 5r (Smith et al 1997)

 

 

 

 

 

 

 

 

 

 

 

 

Radial distance, r a b c
(inches)
0 0.12450 0.14707 0.07565
8 0.12323 0.46911 0.07209
12 0.12188 0.79432 0.07074
18 0.11933 1.38363 0.06909
24 0.11634 2.06115 0.06775
36 0.10960 3.62187 0.06568
60 0.09521 7.41241 0.06255

 

 

pavement system consisting of concrete slabs, granular base/subbase and roadbed soil.
When Equation 4.8 was used, the resulting MR values were substantially lower than the
backcalculated resilient modulus of the same roadbed soils under flexible pavements.
Hence, Equation 4.8 was modified by adding a correction factor (CF), as a multiplier, as
shown in Equation 4.9.

MR = (CF)19.4k Equation 4.9

The value of the correction factor (CF) of Equation 4.9 was estimated using the
three step procedure enumerated below.
In the first step, Figure 4.18 was used to estimate the values of the modulus of
subgrade reaction (k) corresponding to California Bearing Ratio (CBR) values from 1
to 100. The estimates were then plotted and the best fit curve and equation were

obtained as shown in Figure 4.19 and stated in Equation 4.10.

k = 51.495(CBR)0'5835

Equation 4.10

In this step, Equation 4.1 1 (a known correlation between MR and CBR) was divided

by Equation 4.10, which resulted in Equation 4.12 as follows:

78

 

l 1.52 3 456

15

20

 

 

I I 1

 

 

ASTM Soil Classification System

 

1

 

 

 

Unified Soil Classification System (USCS) GM

 

CH H11;

 

 

 

 

 

 

 

3040 50 70 100__1

1 fiquvLEL-v 1

 

 

 

 

 

11:
1

 

 

 

 

 

 

 

 

 

 

 

 

 

CH fi-F—rf1

 

 

 

 

MH

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

H

 

 

 

 

 

 

 

 

 

 

41

 

 

 

V

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

4

 

 

 

 

 

 

, A-6

 

#222. *2117

AA

 

1

 

 

 

 

 

1 l ’ 1

50 60

1 1 i
4 A-7-5,A-7—6 1 1
1 1 1

Resistance Value — R

1 5 10 20 30 40 70

 

1

 

 

1111

100 150

200

1 1 1

Modulus of Subgrade Reaction — k (psi per inch)
250 300

1

 

400 500 700

 

1 1 1

1 ‘ 1 0

1 2

1

11

20 30

1

I
I

Bearing Value (psi)

40

'III

50

 

 

 

 

l 1.52 3 4 56

8

California Bearing Ratio (CBR)

10

II

15

 

1

V T
1
1
1 1

 

 

20

3O 40 50

70 100

Figure 4.18 Soil classification related to strength parameters (N HI 1998)

79

 

 

 

    

 

 

 

 

 

 

E“ 800 k = 51.495(CBR)"0.5835 i ., f _‘ A
g 1 R2 = 0.9901 1 .
g 1 1 A_ ,, 7, , 1
q, 600 _
"U 1
c3 1
.25” 1
a 400 i
“H 1
O 1 1
E 200 ,, 7: , - if ~ ~ 5517 V41 1
3 1
1:
o 1
2 O 1 1 1
0 20 40 6O 80 100 120 1
California Bearing Ratio (CBR) 1
1

F...-

 

Figure 4.19 Modulus of subgrade reaction versus California Bearing Ratio (after NHI

1998)

MR = 1500(CBR) Equation 4.11

MR 1500 CBR .
_ =29.13(CBR)"“1 Equationm

k — 51.495 CBR0'584

 

 

111. Since the CBR value of each roadbed soil type in the State of Michigan is not known,
an average value of 11 (MR of 16,500 psi, which is slightly lower than the average
backcalculated or the average laboratory measured MR values) was assumed.
Substituting CBR of 11 in Equation 4.12, arranging terms, and substituting in
Equation 4.9, yielded Equation 4.13, which was used throughout this study for the

backcalculation of roadbed modulus under concrete pavements.

MR = (CF)(19.4)(k) = (29.13)(2.67)(k) = (4)(19.4)(k) Equation 4.13

80

4.2.2.1 Analysis of Backcalculated Data from the AREA Method

All deflection basins which had a do of 10 mils or greater were not included in the

analyses. This threshold was set because rigid pavements FWD tested at mid-slab should
not experience more than 10 mils of deflection under the center of a 9,000 pound load.
Results - Only the backcalculated results of roadbed soil MR were further analyzed. The
average, maximum, minimum, and standard deviation of MR of backcalculated roadbed
soil supporting rigid pavements are listed in Table 4.4, and the detailed results are listed
in Table 8.2. The full set of NDT data and backcalculated results of rigid pavements is
available on the accompanying compact disc. It should be noted that no ML soil
supporting rigid pavements was FWD tested.

Table 4.4 Backcalculated roadbed soil MR supporting rigid pavement

 

 

 

 

 

 

 

 

 

 

 

 

Roadbed MR results (psi)

type

USCS Average Maximum Minimum 3::
SM 26,637 55,200 14,292 8,033
SP1 20,731 37,209 11,81 1 4,240
SP2 25,393 41,941 9,495 7,364

SP-SM 20,317 38,035 10,226 5,879

SC-SM 20,435 47,655 3,875 6,647
SC 23,034 35,830 11,662 4,147
CL 24,964 37,358 16,431 4,399
ML - - - —

 

 

 

 

 

4.3 Comparison between Backcalculated Resilient Modulus Values of Roadbed
Soils Supporting Flexible and Rigid Pavements

The resilient modulus (MR), for a given soil classification, is a fundamental soil

property reflecting its response to the applied stresses. The resilient modulus of roadbed

81

soils is more or less constant regardless if the soils are supporting flexible or rigid
pavements. The MR of roadbed soils is dependent only on the soil type, water content,
dry density, particle gradation, Atterberg limits, and stress states. Roadbed soil response
to load is dependent on the stress level applied to the roadbed soil and the thickness, not
the type of the pavement layers.

For each soil classification, the average values of the backcalculated MR of the
roadbed soils supporting flexible and rigid pavements as well as the average between
flexible and rigid pavements are listed in Table 4.5. The average value was calculated by
giving each NDT conducted equal weight, as opposed to simply using the average
between flexible and rigid pavements. The number of NDT for each pavement and soil
type is also given in the table. Please note that no NDT were conducted on rigid
pavements supported on ML roadbed soils.

The average ratio of backcalculated roadbed soil MR supporting flexible
pavements to rigid pavements was 1.02. The distribution of this ratio by soil type can be
seen in Figure 4.20. The frequency of the backcalculated MR values of roadbed soils
supporting both flexible and rigid pavements are shown in Figure 4.21.

As indicated by Figure 4.20, for all soil types except the SP1 roadbed soils, the
backcalculated resilient modulus is roughly the same regardless if the soils are supporting
flexible or rigid pavement sections. This was expected because, for the same soil
classification, the resilient modulus is a fundamental soil property reflecting its response
to the applied stresses. Such a response is dependent on the stress level applied to the
roadbed soil, not the type of the pavement layers. For the SP1 roadbed soils, the flexible

pavement sections that were FWD tested are located mainly on the western side of the

82

Table 4.5 Backcalculated roadbed soil MR supporting flexible and rigid pavements

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Roadbed Pavement Number MR results (psi) Ratio
type Type of NDT Std (flex1ble/
USCS Average Maximum Minimum dev. “819)
Flexible 86 22,976 32,319 16,115 3,373
SM Rigid 218 26,637 55,200 14,292 8,033 0.86
Combined 304 25,602 55,200 14,292 6,715
Flexible 1,053 30,707 70,138 13,154 7,562
SP1 Rigid 446 20,731 37,209 11,81 1 4,240 1.48
Combined 1,499 27,739 70,138 11,811 6,573
Flexible 67 23,042 28,602 19,243 3,036
SP2 Rigid 496 25,393 41,941 9,495 7,364 0.91
Combined 563 25,1 13 41 ,941 9,495 6,849
Flexible 31 21,292 30,666 15,623 3,740
SP-SM Rigid 333 20,317 38,035 10,226 5,879 1.05
Combined 364 20,400 3 8,035 10,226 5,697
Flexible 34 18,989 31,218 7,088 6,541
SC-SM Rigid 1,838 20,435 47,655 3,875 6,647 0.93
Combined 1,872 20,409 47,655 3,875 6,645
Flexible 393 24,704 67,793 11,728 6,695
SC Rigid 884 23,034 35,830 11,662 4,147 1.07
Combined 1,277 23,548 67,793 1 1,662 4,931
Flexible 18 20,100 28,849 11,996 4,326
CL Rigid 79 24,964 37,358 16,431 4,399 0.81
Combined 97 24,062 37,358 11,996 4,386
Flexible 23 15,976 31,279 8,711 6,394
ML Rigid - - - - - -
Combined 23 15,976 31,279 8,711 6,394
Average 1.02

 

 

 

state where the sand deposit varies from more than 500 feet in the Cadillac area to about

200 feet in the Grand Rapid area. On the other hand, the SP1 roadbed soils under the

rigid pavement along I-75 is located in the Upper Peninsula and the northern part of the

Lower Peninsula of the State of Michigan where the bedrock is located at shallow depths

(in some locations rock outcrop can be seen on both sides of I-75). The significant point

is that the AREA method algorithm doesn’t account for shallow stiff layer or bedrock.

 

<>SM QSPI lspz

 

 

 

 

 

1:1 SP-SM A SC-SM A sc
'8 ‘77? 1 ,, - -
, g 3 g C} -- +_ Pregwqggmu L .
1 e E 1
~— E 30,000 - 9’ - , ~ 1 ,, A
>
E a
0)
B :5 26,000 L-
‘51 g / . 1
13 a)
9 s: 1
«I on I O
53.: 22,000 1+ ++~ 1 9
—D a ' o 1 1
11% A ~
0 :2 18,000 ' .
2 '9 18,000 22,000 26,000 30,000

1 Average backcalculated MR of roadbed soils supporting rigid
pavement (psi)

Figure 4.20 Flexible vs. rigid backcalculated. roadbed soil MR

IFlexible pavefmgitfigRigfiid Pavement 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. 1 1 1 1 ‘

. . 1 1
1 S ; 1 1 . 1

a 8 - -- — - 1 1—

. C ‘ 1 - 1

1 :5, 1 1 1 ~ 1

E 1 1 1 1 1 1
4 ~ - 1 1l

1 1 w 1

0 ~ LLI—11- -—~i-- 1 1 - 3

2-4 10-12 18-20 26-28 34-36 42-44 50—52 58-60 66-68 1
Range ofbackcalculated MR (ksi) 1

'Figure 4.2] Frequency of backcalculagd hi1 ofgadbe‘d soils'underflexible andhrigid A

pavements

84

The 1993 AASHTO pavement design guide suggests modifying k values when a
stiff layer is present within ten feet from the pavement surface. Figure 4.22 depicts the
modified k value due to three stiff layer depths versus the k value for an infinite stiff
layer depth and the equation of each trend line. The data in the figure were developed
based on the 1993 AASHTO Guide for Design of Pavement Structures. The noteworthy
observation is that the affect of a stiff layer on the k values increases as the depth to stiff
layer decreases. The implication of this is that the backcalculated k values for rigid
pavements are artificially low for those cases where the stiff layer is located at shallow

depths; the AREA method assumes an infinite depth to stiff layer.

 

 

 

 

 

 

 

 

 

 

 

 

. A Depth to stifflayer=2 ft +5 it -D- 10 fi

2 ' _1 ;"“_*"—“ 1 ~ ,::v"
1 g» 700 1 4 —~ + «y-tl-49}+45_11+ -
1 i551; 600 *1 ~ 1 - * ,.,,-,, 1 r "/1 #- y= 1.26x+ 2111‘
1 m / 1 1 _ ~97 ~ ~~ _

g 500 - 1 » —— + 1 1 »»»»» +74-
1}; -400 _. . __ ._.-:____- L-.- 1 ' , 7 1

5 1 1 1 1 iy=l.01x+6
,: 300 ++ 1» ++ . a - L- . ._
.§§ 200 1 : .LLL

'8 1 1

E 100

100 150 200 250 300 350 400 450 500 1
k value (pci)

Figure 4.22 Stiff layer effects on backcalculated k
The difference between the backcalculated MR values of the SP1 roadbed soils
supporting flexible and rigid pavements is mainly related to the effects of the depths to
stiff layer. To account for the presence of a shallow stiff layer under the rigid pavements

supported by SP1 soil the equations shown in Figure 4.21 were utilized to modify the

85

average MR value for SP1 soil supporting rigid pavement sections. Two and five foot
depth to stiff layer were assumed and the average resultant was 30,303 psi. This results in
the ratio between backcalculated roadbed soil MR supporting flexible pavements to rigid
pavements of 1.01.

Ranges - The maximum, minimum and the average backcalculated MR values roadbed
soils supporting flexible and rigid pavements are shown in Figures 4.23 and 4.24. It can
be seen that the ranges of the backcalculated MR of soils supporting flexible pavements
are, for most soil types, less than those of the same soils supporting rigid pavements. This
is mainly due to the dates (month and year) when the FWD tests were conducted. For
most rigid pavements, the FWD tests were conducted over several year period and from
early summer to late fall. Whereas, most of the FWD tests on flexible pavement were

conducted during the same year and within few months.

 

 

 

   

 

i E Maximum ' flerageflflMinimlim. 7
80,000 " 1
60,000 —- , i1 —— + -- 1
40,000 + ~~~~~~ i w»

  

l .
Ill llll

SM(l) SM(r) SP1(f)

20,000 * ~

Backcalculated MR (psi) '

 

 

   

  

 

 

m
"U
_n
A
"1
V
CI)
0.6
N
A
CD
U)
"U
N
A
3
U)
(I)
"F’

p-
SM(t) SM(r)

Roadbed soils 1

 

 

Figure 4.23 Range of backcalculated MR for SM, SP1, and SP2 soils

86

5 Maximum I Average llIl Minimum ,

 

80,000 +++.-+++._----_---

60,000 , * , 1 + + ,1, Di in.

  

40,000 ,

1
.1

1

1

  
 

     

    

1
1

"—1
||||1 III 111

SC- SC- SC(f) SC(r) CL(f) CL(r) ML(f) ML(r)

      

20,000 -

Backcalculated MR (psi)

    

 

 

 

Roadbed soils

Figure 4.24 Range of backcalculated MR (SP-SM, SC—SM, SC, and CL soil)

The significance of the above scenario is that, for most rigid pavements, the range
in the roadbed soil moisture contents is likely higher than that for flexible pavements.
The larger variation in water content resulted in a larger variation in the backcalculated
MR values. Further, for pavements supported by SP1 soils, the FWD tests conducted on
flexible pavement sections were conducted over more environmental seasons and years
than those on rigid pavements. Therefore, the range of the backcalculated MR values for
the flexible pavement sections is larger than that for the rigid sections. Finally, it should
be noted that no FWD tests were conducted on rigid pavements supported by ML soil.
4.4 Comparison between Backcalculated and Laboratory Determined Resilient

Modulus Values

For a given soil classification, the resilient modulus is a fundamental soil property

controlling its response to the applied stresses. However, this property changes with

87

 

changing soil type, water content, dry density, particle gradation, Atterberg limits, and
stress states. Therefore, in order to compare the backcalculated and the laboratory
measured MR values special care must be taken to match the conditions of the soils in
question. In this study, all laboratory tests were conducted under a stress state that is
compatible to that experienced by the soils in the field during the FWD tests. These
conditions are discussed later in this section.

For each soil classification, Table 4.6 provides a list of the average MR value
obtained in the laboratory and the average backcalculated MR value using the measured
deflection data. The two sets of MR values and the line of equality between the two
average values are plotted in Figure 4.25.

Table 4.6 Laboratory determined and backcalculated roadbed soil MR values

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Laboratory results Backrce:l:llgation fivelragle 03
USCS AASHTO bac ca cu ate to
Number Average Number Average average
of tests MR (psi) of tests MR (psi) laboratory MR
SP1 AA}: 16 28,942 1,499 27,739 0.96
SP2 AA}? 10 25,685 563 25,113 0.98
SP- A-l-b
A—2-4 8 21,147 364 20,400 0.96
SM
A-3
SC- A-2-4
SM A-4 7 23,258 1,872 20,409 0.88
SM A1834 17 17,028 304 25,602 1.50
A-2-6
SC A-6 16 18,756 1,277 23,548 1.26
A-7-6
A-4
CL A-6 9 37,225 97 24,062 0.65
A-7-6
ML A-4 4 24,578 23 15,976 0.65
Average 1.03

 

 

 

88

 

 

 

 

 

‘A 0 SM 9 CIC SP1 8 i ; si>2 l
A SP-SM El SC-SM A SC 1
0 CL 1 0 ML 1 r; —— Line ofequality i“
5 ~ 0 . . - 1- 2
a: 35,000 ,, - , ~ 7* 1 i , ~ 1 f ,, *1
E 1
E I l
E , 1 1
O 1 W, , 2;", ,IL 1 ,L A, . in“, ,___ ,
3 25,000 7‘ ,7 11:1 1 1
5 1 A ,
> _ ' } :0
< - 1 1 1
15,000 1
15,000 20,000 25,000 30,000 35,000 40,000
Average backcalculated MR (psi)

 

 

 

Figure 4.25 Laboratory determined and backcalculated roadbed soil MR
The data in Table 4.6 and Figure 4.25 indicate that the ratio of the two averages of
the MR values for the SP1, SP2, SP-SM, and SC-SM are close to one. Whereas the ratios
for the other four soil types (SM, SC, CL, and ML) vary from 1.5 to 0.65. These values
were expected because:

0 For the SM and SC soils, the average laboratory MR values were obtained as the
average MR values of soil samples compacted at water contents corresponding to
degrees of saturation from about 25 to about 99 percent (which simulate the water
contents throughout one year period). The FWD tests were mainly conducted in the
summer and fall seasons where the water contents of roadbed soils are on the dry side
of optimum. Hence, the backcalculated values are expected to be higher than the

laboratory obtained values as shown in Table 4.6 and Figure 4.25.

89

o For the CL and ML soils on the other hand, the majority of the laboratory tests were
conducted on soil samples that were on the dry side or near the optimum water
content. The water contents of only four out of thirteen test samples were near or
above the optimum water content, whereas the water contents of the other nine test
samples were well below the optimum water content. Therefore, the average
laboratory MR should be expected to be high. Since, the FWD tests were conducted
in the summer and fall (the water content of the roadbed soil is near the optimum) the
backcalculated MR value is relatively low. Hence, the average MR value obtained
from the laboratory tests is higher than the average backcalculated value.

The two reasons are related to the effects of moisture contents of the test samples
on the MR values. To explore such relationship for the ML soils, four cyclic load tests
were conducted on ML soils using four different moisture contents. The test results are
plotted in Figure 4.26. As can be seen from the figure, increasing the water content from
about 11 percent (dry of optimum) to about 24 percent (wet of optimum) causes
decreases in the MR value from about 40,000 to less than 2,000 psi. This more or less
agrees with most results reported in the literature.

Once again, the test results in this research indicate that, if the roadbed soil
samples were tested in the laboratory at similar water contents as the field water contents
at the time when the FWD tests were conducted, then the ratios of the backcalculated to
the laboratory obtained modulus values are close to unity. This finding contradicts those
reported in the literature where the ratio between the backcalculated and the laboratory
determined MR values vary from almost 1.6 to almost 5.0. The discrepancy between the

finding in this study and the literature can be mainly related to the stress boundary

90

 

 

 

 

 

 

 

 

 

60,000
0

A 40,000
@- 2--.
E

20,000

0 fi—
10 12 14 16 18 20 22 24

Moisture content (%)

Figure 4.26 Moisture content affect on MR of ML soils
conditions used in this study. Most laboratory test data reported in the literature are based
on stress ratio (the ratio between the axial cyclic stress and the confining pressure) of 2.0
or higher. Two stress ratios were used in the laboratory testing program of this research
study, 1.33 and 2.0. However, all analyses were conducted on the resilient modulus
values obtained from a stress ratio of 1.33. This ratio was obtained by conducting
analyses of the stresses and strains delivered to the roadbed soil of a 25-inch thick
pavement section due to 9000 pound wheel load (half the standard single axle load of
18000 pounds). The MICHPAVE finite element computer program, which is based on
layered elastic theory, was used in the analyses. Results of the MICHPAVE computer
program indicate that the roadbed soil is subjected to 8 psi vertical stress and to about 7.5
psi lateral stress. It should be noted that, in the analyses, a lateral earth pressure
coefficient of 2.0 was used to simulate the locked-in lateral stress due to compaction. As

stated earlier, for all soil types, the laboratory resilient modulus values obtained from

91

cyclic stress of 10 psi and confining pressure of 7.5 psi were used in the analyses.
Increasing the cyclic stress while keeping the confining pressure at a constant level yields
higher stress ratio and lower resilient modulus values. In this study, the effects of the
stress ratio on the resilient modulus values were analyzed by conducting tests at different
stress ratios. Results of said tests are depicted in Figure 4.27. The figure shows the
resilient modulus value as a function of the stress ratio. It can be seen, from the figure,
that increasing stress ratios result in lower MR values. This in turn would yield higher
ratios between the backcalculated and the laboratory determined MR values. The
important point herein is that the resilient modulus test should be conducted at similar
boundary conditions as those expected in the field. That is, the applied stresses in the
laboratory should resemble those delivered to the roadbed soil due to 9000 pound load
traveling over the pavement section in question. Higher stress ratios should be used when

testing the base and subbase materials.

 

 

 

 

 

 

 

 

 

1 14,000
1 1
f 13,000 » ++ ‘
1 5” 12,000 L 1
1 11,000 -__._, ~
* Confining pressure (G3 = 7.5 psi) " *‘ **

1 10,000 i t

1.0 1.5 2.0 2.5 3.0 .

Cyclic stress ratio (cl/o3) i

Figure 4.27 Laboratory obtained resilient modulus versus the cyclic stress level

92

Ranges -- For each soil type, the ranges of the backcalculated and the laboratory
determined MR values are shown in Figures 4.28 and 4.29. The backcalculated ranges of
MR represent the variability in the soil moisture contents from early summer to late fall
over several years. The ranges in the laboratory determined MR values, on the other
hand, reflect variability in the water content of the soils and the compacted density. As it
was expected, for fine soils (CL, ML, and SC), the effect of the water contents of the
laboratory compacted test samples is higher than the variability in the density of the soils.
For granular samples (e.g., SP1, SP2 and so forth), the effect of the density is higher than

that of the water content.

 

 

 

5 Maximum I Average [ID Minimum

80,000 ~---—-+--—++++++.-----_-_

 

60,000 ~

40,000 g
1 w
‘ 20,000+» ~ a +
‘ 0 :

SM(b) SM(l) SP1(b) SP1(1) SP2(b) spza) SP- sp-
SM(b) SM(l)

 

 

 

 

       

MR range (psi)

 

 

 

 

 

 

 

 

 

Roadbed soils

Figure 4.28 Range of MR values (SM, SP1, SP2, and SP-SM soil)

5 Maximum I Average [[1] Minimum 1

 

80,000 1 1 ,

 

60,000

 
 

40,000

MR range (psi)

 

 
 

 

1111 ‘

so. so. SC(b) SC(l) CL(b) CL(1) ML(b) ML(I) 1
SM(b) SM(I)

1 20,000

 

 

 

 

 

   

Roadbed soils l

 

 

 

Figure 4.29 Range of MR values (SC-SM, SC, CL, and ML soil)

4.5 Damage

A brief summary of seasonal effects on roadbed soil is presented in the next two
subsections. The detailed analyses can be found in (Sessions 2008).
The State of Michigan is located in the AASHTO wet-freeze region. The average annual
rainfall and snowfall in the State varies from one location to another. In the Lansing area,
the average annual rainfall is about 32-inch and the average annual snowfall is about 56-
inch. Further, the frost depth varies from about 7-feet in the Upper Peninsula to about 3-
feet in the Lower Peninsula. These climatic data affect the behavior of the paving
materials and roadbed soils. Because of the variability of the climatic conditions, the
resilient modulus of any given soil is dynamic in nature and changes seasonally with

changing water content and temperatures fluctuating below and above the freezing point.

94

One of the objectives of this study was to investigate the affects of seasonal
variations on roadbed soil MR. In order to study the affects; FWD tests were to be
conducted once in the summer/fall season and once during the spring season. The factor
between backcalculated roadbed soil MR during the summer/fall and spring seasons
would be the seasonal damage factor. However, due to MDOT budget and equipment
restraints only two sets of FWD tests were conducted during both seasons. Figure 4.30
indicates that the data represents partial spring conditions with only 40% and 15%
reductions in MR respectively. The closed symbols represent the summer/fall tests and
the open symbols represent the spring like conditions, while the arrows indicate the
reduction in roadbed soil MR. No reasonable conclusions can be drawn based on the

limited data.

‘II-75 (Fall) [31-75 (Spring) 1'134—(15511)41-94(s§§ihg) j

 

25,000

1)

20,000 -- -—

15,000 - —»—-—

 

10,000' l -——- i ___.— ; ___

_ 15% i
5,000 -—- A-—- ——-— . _ . Aw-.. _ ______

 

Roadbed soil MR (ps

 

 

 

 

Figure 4.30 Partial spring condition FWD testing

95

CHAPTER 5

SUMMARY, CONCLUSIONS, & RECOMMENDATIONS

5.1 Summary

The resilient modulus of roadbed soil plays an integral role in the design of
pavement systems. Currently, the various regions of MDOT use different procedures to
determine the MR. Most of these procedures are applicable to M-E PDG level 3 designs.
Therefore, a consistent, uniform, and implementable procedure that meets the
requirements of M-E PDG for level 1, 2, and 3 designs, must be developed.

To do this in this study, the State of Michigan was divided into fifteen clusters
where the physical and engineering characteristics of the soil were similar. The clusters
were then divided into ninety nine areas to narrow down the ranges of the engineering
and physical characteristics of the soils. Disturbed roadbed soil samples were collected
from seventy five areas, and twelve undisturbed soil samples (Shelby tubes) were
collected from areas with CL and SC roadbed soils. The soil samples were then tested to
determine their moisture contents, grain size distributions, Atterberg limits (when
applicable), and resilient modulus using cyclic load triaxial tests. Correlation equations
(see Table 5.1) were then developed to estimate the MR values of the roadbed Soil based
on the results of the moisture content, degree of saturation, Atterberg limits, dry unit
weight, specific gravity, and grain size distribution data.

Deflection data from FWD tests conducted throughout the state were obtained
from MDOT. The test database consisted of hundreds of FWD tests from previous

projects spanning the last 20+ years as well as fifty six tests conducted as part of this

96

 

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study. FWD data files with sufficient accompanying data were analyzed to backcalculate

the roadbed soil MR.

5.2

Conclusions

Based on the field and laboratory investigations and the data analyses, the

following conclusions were drawn:

1. Most of the roadbed soils in the State of Michigan can be divided into the following

eight soil types:

Gravelly sand (SG)

Poorly graded sand (SP), which can be divided into two groups SP1 and SP2
based on the percent fine contents.

Silty sand (SM)

Poorly graded sand — silty sand (SP-SM)

Clayey sand — silty sand (SC-SM)

Clayey sand (SC)

Low plasticity clay (CL)

Low plasticity silt (ML)

2. In general, the backcalculated MR values of roadbed soil supporting flexible

pavement sections are similar to those of the same soil type supporting rigid

pavement sections.

3. In general, the backcalculated MR values of roadbed soil are similar to those of the

same soil type obtained from triaxial cyclic load laboratory testing.

4. The backcalculated MR values, in this thesis, satisfy the M-E PDG requirements for

level 1, 2, and 3 design.

98

10.

Relatively accurate correlation equations between the laboratory obtained resilient
modulus values and some of the soil parameters were developed and are summarized
in Table 5.1.

MR values obtained from the correlation equations listed in Table 5.1 satisfy the M-E
PDG requirements for level 2 and 3 design.

An average resilient modulus value for each soil type, except the SG, and for the two
SP groups were developed and are listed in Table 5.2 and presented in Figure 5.1.
The MR values in Figure 5.1 satisfy the M-E PDG requirements for level 3 design.
The AREA method does not account for the effects of shallow stiff layers.

Equation 5.1 should be used when converting k, backcalculated from the AREA
method, to MR of roadbed soils.

MR -_- (4)(19.4)k Equation 5.1

Table 5.2 Average roadbed soil MR values

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Roadbed type Average MR (psi)
USCS AASHTO Laboratory Backcalculated
Deterrnlned

SM A-2-4, A-4 17,028 25,602
SP1 A-l-a, A-3 28,942 27,739
SP2 A-l-b, A-3 25,685 25,113
SP-SM A-l-b, A-2-4, A-3 21,147 20,400
SC-SM A-2-4, A-4 23,258 20,409
SC A-2-6, A-6, A-7-6 18,756 23,548
CL A-4, A-6, A-7-6 37,225 24,062
ML A-4 24,578 15,976
SC/CL/ML A-2-6, A-4, A-6, A-7-6 25,291 23,459

 

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5.3 Recommendations
Based on the results and conclusions of this study, it is strongly recommended
that:

0 Additional deflection data should be collected during spring conditions and used to
calibrate the seasonal damage factors that were developed based on laboratory data.

0 MDOT implements the findings of this study by using deflection data collected at the
project level to backcalculate the resilient modulus of the roadbed soil to meet the
requirements of M-E PDG design levels 1., 2, and 3.

o MDOT implements the findings of this study by adopting the correlation models
presented in Table 5.2 for M-E PDG design levels 2 and 3.

o MDOT implements the findings of this study by adopting the data presented in Figure
5.1 for M-E PDG design level 3.

o For rigid pavements, MDOT uses Equation 5.1 to convert backcalculated k of
roadbed soil to MR and vice versa.

0 Backcalculated MR needs not be converted to laboratory MR values, the two are the

similar if the laboratory test boundary conditions are similar to those under FWD in

the field.

104

APPENDICES

105

APPENDIX A

Laboratory and field test results

106

This appendix houses the laboratory and field test results arranged in table format as

follows:

For each of the 15 clusters, Table A.1 provides a list of the various percentile of soil
types found in each area within the clusters.

.Table A2 provides a lists of the results of pocket penetrometer and vane shear tests
for each of the 99 areas within the 15 clusters.

Table A.3 provides a list of the moisture content, sieve analyses, and Atterberg limit
test results for each soil type within the 99 areas.

Table A.4 lists the results of the triaxial cyclic load tests.

Table A.5 lists the MR results for each triaxial cyclic load test.

107

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Table A.3 Moisture content, sieving, and Atterberg limit results

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

118

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Natural Sample Percent passing sieve # Atterberg limits C : CC = Classification
Sample number Shelby water weight 3/8 4 10 20 40 100 200 D D D DU / D302/
tube content (g) inch LL PL PI 1° 30 6° D60 (D60) AASHTO USCS
(%) 9.500 4.750 2.000 0.850 0.425 0.150 0.075 1° (D10)
M—045—S (01—01) 11.5 298.8 99.5 99.3 98.9 96.8 96.7 77.2 66.7 26 16 10 0.0030 0.006 0.040 13.33 0.30 A-6 CL
U—002—E (02-01) 16.8 303.3 99.1 97.8 96.6 92.3 68.1 46.4 39.2 18 - NP 0.008 0.040 0.300 37.50 0.67 A-4 SM
M—028-W (02-02) 21.0 200.0 100.0 99.4 98.0 93.4 83.2 64.5 56.1 23 - NP 0.0080 0.024 0.110 13.75 0.65 A—4 ML
M-028—W (02—03) 6.6 535.8 100.0 99.3 97.2 92.1 81.8 23.4 6.1 16 - NP 0.091 0.175 0.285 3.13 1.18 A-I-b SP—SM
U—002—E (02—04) 10.8 200.0 100.0 99.4 98.0 93.4 83.2 64.5 54.1 19 - NP 0.0100 0.050 0.110 11.00 2.27 A—4 ML
U—002-E (03—01) 5.0 525.3 100.0 99.8 99.6 98.5 92.6 15.8 6.5 13 — NP 0.130 0.190 0.275 2.12 1.01 A-3 SP—SM
M-028-W (03-02) 3.1 519.1 99.9 99.6 99.3 97.9 89.7 14.0 3.0 NA NA NP 0.150 0.190 0.280 1.87 0.86 A-3 SP
U-002-E (03—03) 13.1 222.9 100.0 96.8 93.7 88.7 77.8 31.7 25.1 15 - NP 0.002 0.120 0.300 150.00 24.00 A-2-4 SM
M~028-W (03-03) 4.8 520.2 94.1 87.5 82.6 71.2 45.5 11.1 6.4 21 ~ NP 0.140 0.285 0.600 4.29 0.97 A-3 SP—SM
I—075—N (03—04) 9.4 549.2 99.9 99.8 99.5 98.4 91.3 10.0 1.5 NA NA NP 0.160 0.200 0.280 1.75 0.89 A-3 SP
I—075—N (03-05) 21.2 197.8 100.0 99.9 94.1 92.4 80.9 60.3 48.2 55 22 33 0.001 0.002 0.150 150.00 0.03 A-7-6 SC
U-023-S (04-01) 22.0 547.2 98.8 98.8 98.5 96.4 90.3 10.3 4.3 NA NA NP 0.170 0.200 0.280 1.65 0.84 A3 SP
M—068-W (04-02) 4.0 205.0 99.9 98.6 91.0 51.3 25.2 16.0 14.1 18 12 6 0.040 0.500 1.000 25.00 6.25 A-2-4 SC—SM
M—068—W (04-03) 33.3 515.6 100.0 100.0 99.7 98.7 89.8 14.3 3.7 NA NA NP 0.160 0.190 0.280 1.75 0.81 A-3 SP
M-065-S (04—04) 8.1 201.5 99.3 95.4 91.3 87.5 72.7 30.4 21.5 30 - NP 0.001 0.150 0.300 300.00 75.00 A-2-4 SM
M—032-W (04—05) 9.6 203.4 100.0 99.8 99.6 99.0 95.0 64.6 48.7 19 12 7 0.001 0.006 0.130 130.00 0.28 A4 SC—SM
U—131—N(05—01) 13.1 199.4 99.8 99.2 96.4 95.0 78.7 43.5 29.2 14 - NP 0.016 0.140 0.280 17.50 4.38 A—2-4 SM
U—127-N (05—04) 8.9 527.6 91.8 84.4 79.1 73.3 53.6 6.4 3.7 NA NA NP 0.180 0.260 0.500 2.78 0.75 A-3 SP
M-033~S (05-05) 3.5 525.7 63.1 57.5 45.4 35.7 26.7 7.8 4.6 NA NA NP 0.185 0.510 6.000 32.43 0.23 A-l-a SG
M—072-W (05-06) 14.3 201.0 100.0 99.6 98.8 97.3 91.4 56.1 39.9 22 11 11 0.0070 0.035 0.160 22.86 1.09 A-6 SC
M-132-N (06-01) 15.0 521.7 99.5 99.0 98.5 96.8 78.7 8.8 4.2 NA NA NP 0.160 0.220 0.320 2.00 0.95 A-3 SP
I-075—N (06—02) 3.4 518.0 95.1 93.7 92.8 90.4 63.4 5.8 4.1 NA NA NP 0.170 0.260 0.400 2.35 0.99 A-3 SP
U-031-N (06—03) 5.8 1060.3 99.5 99.1 98.4 97.4 87.2 7.9 0.5 NA NA NP 0.170 0.210 0.300 1.76 0.86 A-3 SP
1-196-N (06-05) 10.5 1085.6 99.6 98.4 96.2 91.2 84.4 26.5 5.9 15 — NP 0.089 0.160 0.275 3.09 1.05 A—2-4 SP-SM
M—020~W (07-02) 4.2 1003.7 99.6 99.3 98.7 97.9 88.0 2.1 0.8 NA NA NP 0.180 0.220 0.300 1.67 0.90 A—3 SP
M-020—E (07—03) 4.5 513.3 99.2 97.9 96.8 94.5 89.6 21.2 3.3 NA NA NP 0.110 0. 0.280 2.55 1.17 A-3 SP
U—127-N (07-04) 10.9 200.8 100.0 98.8 96.6 95.4 90.3 38.3 26.9 22 12 10 0.001 0.100 0.230 230.00 43.48 A-2—6 SC
U—127—N (07-05) X 11.2 203.9 100.0 98.3 92.6 87.3 79.9 53.7 40.5 23 14 9 0.0011 0.006 % 172.73 0.17 A-6 SC
U-127—N (07—05) 14.4 213.7 99.8 98.2 85.2 81.0 74.8 52.1 43.7 24 14 10 0.0010 El 0.210 210.00 0.30 A—6 SC

 

 

 

 

 

Table A.3 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Natural Percent passing sieve# Atterber limits — ‘ '
Saml 6 Shelby water Sample 3/8 g C“: CC; ’ ClaSSIficatlon
penum er tube content welght . 4 10 20 40 100 200 D10 D30 D60 D60/ D30/
0 (g) inch LL PL PI D (D60) AASHTO USCS
(4) 9.500 4.750 2.000 0.850 0.425 0.150 0.075 1° (D10)
M-061—E(07-06) 22.1 198.5 100.0 98.8 93.3 84.7 59.3 23.7 17.9 19 — NP 0.040 0.190 0.430 10.75 2.10 A-2-4 SM
M-061—E(08—02) 20.3 223.1 100.0 99.7 93.9 77.8 51.9 26.1 23.2 11 — NP 0.050 1.000 0.520 10.40 38.46 A24 SM
U—010-W(08-03) 21.4 200.2 100.0 100.0 99.8 99.7 97.6 61.0 55.2 32 14 18 0.001 0.002 0.140 140.00 0.02 A-6 CL
U-010-W(08-04) 8.2 200.1 99.9 99.9 98.8 96.6 84.5 48.8 36.7 29 13 16 0.001 0.011 0.200 200.00 0.61 A-6 sc
U—010—W(08-04) X 15.0 205.1 98.0 98.9 96.5 95.8 80.3 42.5 33.3 27 13 14 0.0009 0.018 0.200 222.22 1.80 A-6 sc
I-O75—S(08—05) 8.9 201.0 100.0 99.9 97.7 94.5 69.4 40.3 33.5 25 12 13 0.001 0.011 0.300 300.00 0.40 A26 SC
I—O75—N(08-06) 11.8 201.5 100.0 99.2 96.8 93.7 85.4 36.6 26.2 17 10 7 0.001 0.011 0.270 270.00 0.45 A24 :54
U—131-S (09-01) 4.6 1056.3 99.0 98.0 97.4 97.0 83.7 2.5 0.5 NA NA NP 0.180 0.220 0.300 1.67 0.90 A—3 SP
I-096—W(09-02) 9.9 206.2 100.0 99.0 97.3 93.8 82.7 40.9 30.5 17 13 4 0.001 0.075 0.240 240.00 23.44 A24 :54
U-131—S(09—03) 1.9 530.4 100.0 100.0 99.9 99.8 97.2 6.0 0.4 NA NA NP 0.180 0.200 0.290 1.61 0.77 A-3 SP
U—131—S(09—05) 3.6 1025.6 97.5 90.2 80.8 69.5 45.8 3.1 1.3 NA NA NP 0.185 0.295 0.605 3.27 0.78 A-3 SP
M—044-E(09—07) 8.7 206.5 100.0 99.5 97.7 94.1 85.5 37.7 26.7 14 _ NP 0.020 0.110 0.250 12.50 2.42 A24 SM
I-075—S(09~08) 20.2 216.1 99.1 96.1 91.8 89.7 85.5 62.3 45.8 31 14 17 0.001 0.004 0.140 140.00 0.11 A-4 SC
M-024-S(09-09) 13.3 198.6 100.0 99.6 97.6 95.4 93.2 45.0 24.1 20 — NP 0.012 0.090 0.200 16.67 3.38 A-2-4 SM
I—069-E(09—10) 7.1 527.8 98.3 93.4 83.0 66.3 36.8 5.2 3.1 NA NA NP 0.190 0.340 0.700 3.68 0.87 A-3 SP
I-O69-N(10-01) 10.1 534.1 94.9 88.7 81.1 67.6 49.2 16.7 8.0 16 11 5 0.093 0.230 0.600 6.45 0.95 A-3 SP-SM
I—096—W(10—03) 14.7 199.7 100.0 98.4 93.9 90.1 82.0 29.5 17.5 29 14 15 0.0600 0.150 0.280 4.67 1.34 A26 SC
I-069—N(10—04) 11.1 198.5 100.0 99.3 94.1 86.4 74.9 30.1 17.6 16 — NP 0.010 0.150 0.200 20.00 11.25 A24 SM
I—069-N(10~05) 24.0 204.0 100.0 100.0 97.8 87.6 54.9 43.2 37.3 19 — NP 0.010 0.070 0.500 50.00 0.98 A24 SM
I-O96-W(10-09) 15.1 200.9 100.0 99.6 93.7 91.0 61.1 38.0 30.4 19 — NP 0.006 0.075 0.410 68.33 2.29 A24 SM
I—O69-E(10-10) 12.8 204.9 98.0 96.1 92.4 90.5 84.7 57.2 37.7 26 15 11 0.001 0.009 0.170 170.00 0.48 A—6 SC
M—021-E(10-11) 15.0 230.2 99.4 92.1 85.9 79.5 72.2 46.3 33.8 23 14 9 0.001 0.030 0.270 270.00 3.33 A24 sc
I—069—N(11-01) 9.1 1032.9 90.3 87.1 83.0 77.8 63.9 15.9 6.9 14 — NP 0.120 0.210 0.390 3.25 0.94 A-3 SP-SM
1—094—W(11—02) 7.1 1022.7 95.0 91.7 87.1 77.5 51.2 6.2 2.7 NA NA NP 0.170 0.270 0.510 3.00 0.84 A—3 SP
M-060-W(11—03) 10.5 199.3 99.7 99.0 97.4 90.6 67.0 37.6 31.1 22 15 7 0.004 0.025 0.330 82.50 0.47 A24 3 I
so
I-069-S(11—05) 6.6 201.1 100.0 99.1 93.9 86.9 77.3 49.3 38.6 15 11 4 0.002 0.034 0.210 105.00 2.75 A-4 SL1
——’— sc-
I—O94—W(12—01) 8.6 199.8 100.0 95.2 81.8 73.9 51.8 26.5 20.0 16 12 4 0.038 0.180 0.560 14.74 1.52 A24 SM
I—094—W(12—03) 13.2 527.4 97.4 95.4 91.6 83.0 68.3 18.7 7.4 161 _ NP 0095 0.195 0.345 3.63 1.16 A-3 SP—SM
U—012—E(12—04) 4.9 200.4 99.9 98.9 94.2 89.4 73.7 36.6 23.0 16] — [NP 0.003 0.110 0.300 100.00 13.44 A24 SMJ

 

 

 

 

 

119

 

 

 

Table A.3 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Natural Sample Percent passing sieve # Atterberg limits _ CC 2 Classification
Sample number Shelby water weight 3/8 4 10 1 20 40 CU — D302/
tube content (g) inch 100 200 LL PL PI D10 D30 D60 1360/ (D60) AASHTO USCS
(%) 9.500 4.750 200010.850 0.425 0.150 0.075 D“) (D10)
I—094—W(12—06) 12.1 213.7 100.0 99.8 92.2 90.5 86.0 35.2 23.8 15 — NP 0.005 10.130 10.2501 50.00 1 13.521 A-2—4 SM
U—012—E(12~07) 7.0 513.8 67.5 57.0 42.2 25.8 16.0 10.0 8.1 18 — NP 0.160 1 1000160001 37.50 1 1.04 1 A-1-a SG
M—024-S (13—01) 10.6 196.0 100.2 98.4 93.4 90.2 85.2 59.4 45.1 18 15 3 0.001 1 0.013 1 0.150 1 150.00 1 1.13 A-4 SM
M-059—W(13—02) 11.6 1033.3 99.4 97.9 95.1 91.2 65.7 8.9 1.7 NA NA NP 0.160 10220103801 2.38 0.80 A—3 SP
M—014-W(13—03) 9.3 198.1 100.0 99.1 94.0 1 90.0 1 85.7 1 62.7 49.2 22 13 1 9 1 0.001 10006101301130.00 0.28 A—4 SC
1-094—W(13—04) 8.0 1005.6 98.1 95.8 90.5 1 82.8 1 65.9 1 13.1 3.5 NA NA1 NP 1 0.140 10210103901 2.79 0.81 A-3 1 SP
U—012—E(13—05) - 14.9 205.0 100.0 99.9 99.01 97.8 1 95.5 1 65.6 56.7 33 17 1 16 1 0.001 10002101001111.11 0.04 1 A-6 1 CL
U—023—N(13—07) 9.8 529.5 94.1 83.4 66.2 53.5 1 43.3 1 12.0 5.7 13 1 — NP 10.130 10280113501 10.38 0.45 1 A—3 1SP-SM
M—010—E(13—08) 14.0 201.0 100.0 99.7 98.1 95.0 90.8 1 74.3 59.9 24 14 10 1 0.0010 1 0.003 10.075 1 75.00 0.12 1 A—6 1 CL
M—OlO-E(13—08) X 12.3 207.0 100.0 98.0 95.6 93.5 88.3 1 72.6 54.8 23 14 9 0.0009 0.015 10.0901 100.00 2.78 1 A6 1 CL
I-O75—S(14-01) X 18.4 204.5 100.0 99.9 89.4 87.9 67.6 1 54.2 48.2 42 21 21 0.0090 0.015 10.2501 27.78 0.10 1 A—7-6 1 SC
I—075—S(14—01) 25.4 200.6 100.0 96.9 78.9 76.2 68.4 47.8 41.2 45 19 26 0.0007 0.003 0.270 385.71 0.051 A-7-6 1 SC
I—075—S(14—02) 18.7 201.0 100.0 98.3 97.6 92.6 85.5 64.1 46.1 41 19 22 0.001 0.003 0.190 211.11 0.061 A-7-6 SC
U—O24—S(14-03) 19.2 202.3 100.0 99.4 98.8 91.8 79.7 55.3 41.4 40 13 27 0.001 0.003 0.190 271.43 0.071 A-6 SC
I-O75—S(14-04) 15.8 200.8 100.0 99.9 99.8 99.7 96.4 59.4 46.9 34 17 17 0.001 0.003 0.260 288.89 0.041 A-6 SC
U-024-S(14—04) 22.2 543.7 100.0 100.0 99.8 99.6 96.3 23.3 2.5 NA NA NP 0.100 0.170 0.255 2.55 1.131 A-3 SP
1—094—W(14—05) 21.6 199.0 99.7 97.6 97.5 89.7 78.0 56.7 46.7 34 21 13 0.001 0.013 0.160 160.00 1.061 A-6 SC
M-153—E(14—06) X 26.0 209.4 100.0 99.8 99.0 98.3 92.7 70.1 51.1 51 19 32 0.0090 0.018 0.100 11.11 0.361 A—7-6 1 SC
M-153—E(14—06) 21.6 202.9 100.0 100.0 98.4 98.1 94.1 64.4 49.9 52 20 32 0.0007 0.001 0.140 200.00 0.021 A-7-6 1 SC
M—053—S(14—07) 5.9 529.1 93.1 87.5 81.5 70.3 55.0 9.3 4.7 NA NA NP 0.170 0.240 0.500 2.94 0.68 A8 1 SP
I—O94-W(14-09) X 26.3 205.1 100.0 100.0 98.5 97.9 85.2 59.8 55.8 42 23 19 0.0010 0.010 0.150 150.00 0.67 A-7-6 1 CL
I—094-W(14—09) 21.9 197.3 99.7 99.2 97.7 96.6 90.8 66.8 60.9 44 21 23 0.0010 0.002 0.075 75.00 0.05 A-7-6 1 CL
I-094-W(14-10) 21.5 198.9 100.0 99.5 93.3 91.6 80.3 65.2 56.3 42 19 23 0.001 0.002 0.100 166.67 0.07 A—7-6 1 CL
M—053—S(15—02) 17.2 200.4 100.0 99.5 96.8 94.4 87.5 42.8 26.2 14 - NP 0.008 0.100 0.210 26.25 5.95 A24 1 SM
M-090-E(15-03) 38.0 204.1 100.0 99.9 98.8 96.1 90.7 73.1 55.8 35 20 15 0.001 0.005 0.088 88.00 0.28 A—6 1 CL
M-090—E(15-04) 12.4 199.6 100.0 99.7 97.4 95.0 90.6 67.4 52.8 24 15 9 0.0010 0.006 0.100 100.00 0.36 A—4 1 CL
M—025—S(15—05) 4.4 532.8 99.3 98.7 98.2 97.3 84.4 1.9 1.1 NA NA NP 0.180 0.210 0.300 1.67 0.82 A—3 1 SP
M—25-N(15-06) 16.4 206.4 100.0 98.9 94.0 90.8 85.1 54.2 42.3 24 13 11 0.001 0.007 0.190 190.00 0.26 A—4 1 sC
M-019-S(15-07) 11.4 199.4 99.9 95.1 83.9 76.4 61.5 29.0 17.2 14 - NP 0.065 0.160 0.400 6.15 0.98 A-2—4 1 SM
120

 

 

 

Table A.4 Triaxial cyclic load results

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

T Cyclic stress psi)
Soil Type 10 A MR 15
Sample number £311in Average Average Average (1313318156108 (1 Average Average Average Average MR
cyclic load deformation resilient cycles 500, CyChC deformation re51l1ent (p51) at load
AASHTO U S C S (lbs) (mils) modulus (psi) 800 and load (mils) modulus cycles 500,
1000 (lbs) (p81) 800 and 1000
100 31.6 2.304 35,043 49.0 3.740 31,266
200 32.1 2.202 36,823 50.3 3.774 31,862
M—045—S (01—01) A—6 CL 500 32.2 2.262 36,639 36,543 50.1 3.663 31,747 31,503
800 32.5 2.205 37,056 50.1 3.817 31,297
1000 32.8 2.227 35,934 50.4 3.872 31,465
100 32.5 3.729 13,894 50.3 1 5.850 12,872
200 32.9 3.592 14,285 1 50.1 1 5.727 13,150
U-002-E(02-01) A—4 SM 500 32.7 3.442 15,044 15,352 1 50.4 1 5.551 13,686 13,818
800 32.7 3.325 15,708 1 50.4 1 5.496 13,826
1000 33.3 3.415 15,305 1 49.9 1 5.364 13,942
100 32.0 1.741 48,422 50.7 2,777 45,310
200 32.5 1.650 50,092 51.0 2.801 44,090
M—028—W (02-02) A—4 ML 500 32.7 1.569 53,892 53,824 51.3 2.969 42,510 41,516
800 32.7 1.600 53,350 51.3 3.047 41,331
1000 33.0 1.598 54,230 51.3 3,087 40,707
100 33.9 2.675 19,996 51.4 4.042 16,997
200 33.8 2.698 20,013 51.4 3.956 16,510
M—028-W (02—03) A—l—b :14 500 33.7 2.821 19,057 19,195 52.6 3.873 17,649 17,845
800 33.8 2.796 19,502 51.7 3.733 17,942
1000 34.0 2.792 19,025 51.5 3.774 17,945
100 32.8 2.499 31,653 50.0 3.944 29,991
200 32.8 2.471 33,225 49.8 3.855 30,881 .
U~002—E (02—04) A—4 ML 500 33.7 2.322 36,319 37,012 50.0 3.724 31,614 33,191
800 33.1 2.219 36,874 50.1 3.560 33,569
1000 33.1 2.207 37,843 50.5 3.516 34,390
100 33.3 2.393 22,822 51.0 4.295 18,193
200 33.9 2.412 23,466 50.2 4.135 18,644
U—002—E (03—01) A-3 3; 500 33.9 2.441 23,426 22,830 51.6 4.005 19,685 19,629
800 34.1 2.522 22,465 52.0 4.114 19,323
1000 34.6 2.560 22,598 51.7 3.990 19,880
121
. —-——-—‘

 

 

 

 

 

 

 

Table A.4 (cont’d)

 

  

 

  
    
    
   
 
 
 
 
 
 
 
   
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

1’7 1 Cyclic stress (psi)
Soil Type 1 1 10 15
CYC C Avera e Avera A
Sample number number cyclif dejglrirriag'e resiliei: (piseigaagtelxg Average cyclic Average 2:111??? 11181181216114?
AASHTO USCS load .atlon modulus c 1 500 10 d1b deformauon a Ca
(mils) ’ 3’9 CS 7 a ( 5) (mils) modulus cycles 500,
(lbs) (ps1) 800 and1000 (psi) 800 and1000
100 1 33.1 1 2.429 1 22,556 50.3 1 3.861 1 20,301 1
200 1 33.3 1 2.428 22,706 50.9 1 3.783 1 21,1571
M—028—W(03—02) A—3 SP 500 1 34.1 1 2.460 23,286 23,003 51.3 1 3.731 1 21,61fl 22,536
800 1 33.9 1 2.374 23,167 1 1 51.3 1 3.644 1 228W
1000 1 33.8 2.483 22,555 1 1 52.0 1 3.582 1 23,1?1
100 1 32.7 3.357 15,294 1 1 49.8 1 5.258 1 14,150 1
SP_ 200 33.4 3.283 16,085 1 1 50.3 1 5.113 1 14,855
M-028—W(03—03) A—3 SM 500 33.0 3.059 16,876 1 16,911 1 50.5 1 4.774 1 15,866 15,956
800 33.8 3.094 16,885 1 1 50.9 1 4.876 1 15,840
1000 33.9 3.175 16,971 1 1 50.9 1 4.722 1 16,162 1
100 31.7 3.230 15,364 50.3 1 5.163 1 14,590 1
200 32.2 1 3.208 1 15,857 50.5 1 5.056 1 15,302 1
U—002—E(03—03) A—2—4 SM 500 32.7 1 3.167 1 16,240 15,984 50.3 4.973 1 15,412 1 15,833
800 32.7 1 3.251 15,919 51.1 4.873 1 15,966 1
1000 32.6 3.286 15,793 51.0 4.793 1 16,12fl
100 33.8 2.198 25,827 51.4 3.419 1 24,035 1
200 33.8 2.255 25,821 51.9 1 3.423 1 24,209 1
I-075-N(03—04) A—3 SP 500 34.0 2.203 25,887 26,140 51.7 1 3.456 240W 24,401
800 34.3 2.156 26,592 V 52.3 1 3.402 24,4741
1000 34.2- 2.263 25,940 f 52.3 1 3.348 24,689 1
100 33.6 2.390 23,852 1 51.5 1 3.757 21,584 1
200 33.9 2.392 24,136 1 51.7 3.775 21,768 1
U—023—S(04—01) A—3 SP 500 33.7 2.472 23,456 23,060 51.5 3.807 21,5261 21,735
800 33.8 2.440 22,395 51.7 3.700 21,852 1
1000 33.7 2.508 23,330 51.7 3.814 21,828 1
100 34.1 2.034 29,159 51.3 3.595 22,151
200 33.0 2.006 28,338 52.3 3.505 23,435
M-068-W(04-02) A-2—4 2114 500 34.1 1.883 30,987 30,958 52.1 3.377 24,481 24,764
800 34.4 1.861 30,960 51.6 3.383 24,598
1000 34.6 1.980 30,927 51.9 3.299 25,212

 

 

 

 

 

 

 

 

122

 

 

 

 

Table A.4 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cyclic stress (psi)
8011 Type 10 15
Sample number nEEInCSZr fivegi‘fe Average AVPIPag: AV9r3891 Mg Average Average Average Average MR
AASHTO USCS lyoad deformation r6811]? (p811 at500 C1yChC deformation resment (pm at load
(mils) mo UPS CW 95 . 08d (mils) modulus cycles 500, 800
(lbs) (p51) 800 and 1000 (1155) (p31) and 1000

100 29.4 5.139 8,572 46.6 8.078 8,440
200 30.7 4.944 9,491 47.1 7.723 8,966

M—068—W (04-03) A—3 SP 500 31.3 4.879 9,725 9,979 48.6 7.368 9,822 10,013
800 31.7 4.685 10,215 48.8 7.052 10,308
1000 31.6 4.806 9,996 48.5 7.166 9,910
100 31.7 4.463 10,722 48.7 6.850 10,728
200 31.5 4.383 10,903 49.7 6.524 11,210

M-065-S (04-04) A—2—4 SM 500 32.1 4.101 11,945 11,943 50.0 6.427 11,637 11,909
800 32.3 4.157 11,833 50.3 6.268 11,995
1000 32.5 4.190 12,050 49.6 6.038 12,096
100 32.5 2.880 17,806 50.5 4.474 16,758
200 32.3 2.805 17,979 50.7 4.478 17,269

M—032-W (04—05) A-4 if; 500 32.9 2.739 18,915 19,255 50.6 4.283 18,002 18,161
800 33.2 2.725 19,303 50.9 4.267 18,269
1000 33.1 2.708 19,546 50.7 4.208 18,211
100 32.1 2.263 ML 51.4 3.311 24,414
200 32.2 2.284 23,491 51.3 3.281 24,858

U—131-N (05-01) A—2—4 SM 500 33.3 2.257 24,948 24,651 51.4 3.239 26,201 25,604
800 33.6 2.314 24,548 50.9 3.247 25,241
1000 33.8 2.266 24,456 51.9 3.298 25,370
100 34.1 1.757 35,135 52.6 2.846 29,879
200 34.3 1.708 36,388 51.9 2.861 29,921

U—127—N (05—04) A—3 SP 500 34.5 1.687 37,843 37,158 52.9 2.866 30,325 29,949
800 35.3 1.727 36,438 51.9 2.901 fl
1000 35.2 1.766 37,194 52.6 2.850 29,935
100 30.6 3.211 22,91: 48.9 4.652 24,395
200 31.3 3.095 24,442 49.0 __4593___25,0_76_

M—072—W (05—06) A—6 SC 500 31.7 2.941 26,104 26,492 49.8 4.403 26,622 27,193
800 31.9 2.888 27,204 49.8 4.321 27,183
1000 31.2 2.958 26,168 50.2 4.252 27,774 J

 

 

123

 

 

 

 

 

 

 

Table A.4 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cyclic stress (psi)
10 15
Soil Type
Sample number Cycle Average Average Average Average MR Average Average Average Average MR (psi)
number CyChC d f t. res111ent (ps1) at load 1' l d (1 form t‘ n re ilient t1 ad 0 1e 500
load e ”“1181 ion modulus cycles 500, 800 cyc 1C 08 e . a 10 S . a 0 yo s ’
AASHTO USCS (lbs) (mils) (psi) and 1000 (lbs) (mils) modulus (p31) 800 and 1000
100 33.8 2.004 27,798 52.1 3.079 26,746
200 33.9 2.055 29,008 52.7 3.027 27,574
M-l32—N (06—01) A-3 SP 500 34.1 1.984 30,874 31,741 52.6 2.977 28,591 28,997
800 34.4 1.960 31,899 53.2 2.989 29,341
1000 34.0 1.857 32,449 52.0 2.917 29,059
100 33.4 1.616 26,603 51.6 2.882 26,762
200 33.3 1.535 28,072 51.9 2.855 28,300
1—075—N(06-02) A—3 SP 500 33.8 1.461 32,068 32,450 52.3 2.552 31,485 31,187
800 34.5 1.499 32,023 52.1 2.508 31,026
1000 34.4 1.417 33,260 52.7 2.450 31,049
100 34.1 1.933 30,572 52.5 2.814 29,633
200 33.8 1.884 31,084 52.1 2.832 29,692
U—031—N(06—03) A—3 SP 500 34.6 1.808 32,659 31,867 52.6 3:: 33,3): 29,636
800 35.0 1.908 31,347 52.9 . ,
1000 35.4 1.937 31,594 52.6 2.842 29,701
100 33.5 2.456 22,276 51.9 3.650 21,630
200 33.7 2.428 23,097 51.7 3.641 21,694
1—196—N (06-05) A—2-4 :11; 500 34.2 2.386 23,190 23,030 51.5 3.618 22,017 21,985
800 33.6 2.395 22,525 51.7 3.675 21,801
1000 33.9 2.371 23,375 52.1 3.637 22,136
100 33.6 2.112 26,636 51.2 3.135 25,897
200 33.8 2.001 29,046 51.6 3.012 27,403
M-020—W (07—02) A-3 SP 500 34.3 1.969 30,442 31,489 51.8 2.891 28,918 31,766
800 i 34.0 1.902 31,795 52.5 ifl
1000 34.1 1.893 32,230 52.7 2.550 33,084
100 32.8 2.029 27,192 50.6 i 23,445
200 33.6 2.032 28,722 50.5 __3£6_______23_,2£___
M-020-W (07—02) A—3 SP 500 33.8 1.969 30,147 30,272 51.7 3.361 ___25_,(£5__ 24,896
800 34.0 1.971 30,271 51.7 “L31; 24,950
1000 33.9 1.965 30,399 51.6 3.408 24,702

 

 

 

 

 

124

 

 

 

Table A.4 (cont’d)

 

 

D

 

Cyclic stress (psi)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Soil Type 10 15
Sample number 15:31; 1:26;??? Average 1:23:33: 112/831212861088 Average Average Average Average MR
deformation cyclic load deformation resflient (ps1) at 103d
AASHTO USCS load (mils) modulus cycles 500, (lbs) (mils) modulus cycles 500,
(lbs) (p51) 800 and 1000 (p31) 800 and 1000
100 33.7 2.016 28,992 51.2 3.080 25,785
200 33.9 2.064 28,380 51.3 3.000 27,443
M—020-W (07—02) A-3 SP 500 33.9 1.961 29,237 29,446 51.4 2.948 28,001 28,593
800 34.0 2.042 29,357 51.6 2.893 28,741
1000 34.3 1.984 29,743 51.7 2.938 29,037
100 33.2 1.883 19,618 51.0 3.025 16,754
200 33.1 1.884 19,462 51.0 2.949 18,301
M-020-W (07-02) A—3 SP 500 33.6 1.901 20,010 19,693 52.1 2.779 19,917 20,257"
800 33.8 1.922 19,736 52.0 2.722 20,529
1000 33.6 1.876 19,334 51.7 2.723 20,325
100 31.7 2.516 20,521 49.5 4.178 17,679
200 32.8 2.321 22 9 % 50.3 3.959 19,876
M—020—W(07—02) A-3 SP 500 33.1 2.329 1 24360 24,320 51.4 3.364 23,953 24,552
800 33.3 2.344 1 24 ,091J 51.3 3.310 24,799
1000 33.8 2.284 1 24,508 1 51.4 3.307 24,904
100 33.9 1 1.963 1 29 ,497J 52.6 3.106 27,496
200 34.0 1 1.935 1 30, 737 1 52.2 2.999 27,797
M—020—E (07—03) A—3 SP 500 34.4 1.881 32% 32,696 1 51.9 2.992 28,321 28,182
800 34.3 1.941 31,955 F 52.3 1 3.019 1 27,9954
1000 34.2 1.810 33,972 1 1 51.9 1 3.081 1 28,230
100 42.5 11.329 3,466 1 72.2 1 15.047 1 4,432 1
200 43.7 10.944 3,698 P 73.5 1 7.386 1 4,716 1
U—127-N(07—05) A-6 SC 500 44.3 10.593 3,897 3,984 T 75.1 1 6.798 1 5,246 J 5,481
800 44.4 10.260 4,015 F 75.4 6.602 5,455 A
1000 44.2 10.170 4,041 75.4 12.596 5,742
100 52.0 2.068 47,427 82.9 3.013 49,924
200 51.7 1.926 50,103 82.3 2.944 50,430
U-127-N(07-05) A-6 SC 500 52.8 1.878 53,735 54,737 81.6 2.806 51,951 53,030
800 51.5 1.860 54,842 82.5 2.821 53,516
1000 52.3 1.860 55,634 82.0 2.761 53,623

 

125

 

 

 

 

 

 

 

Table A.4 (cont’d)

Soil Type

Sample number Average Average Average Average MR Average Average Average Average MR
. . resrlient (p81) at load cycllc . res111ent (p81) at load
cycllc deformatlon deformation
modulus cycles 500, load (mils) modulus cycles 500,

AASHTO USCS loadabs) (“1115) (psi) 800 and1000 (lbs) (psi) 800 and1000

 

        

 

 

 

 

 

 

 

 

 

 

 

   
   
  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

100 46.3 6.202 7,133 75.8 10.783 6,642
200 46.7 6.185 7,244 76. 7 10.605 6, 765
U—127—N(07-05) A—6 500 1 46.7 1 6.248 7,223 7,323 77.2 1 10.557 1 6,875 6,925
CEO 1 47.2 1 6.196 775 1 10.534 1 6,693
1 1000 1 47.9 1 6.195 7,395 77.9 1 10.543 1 6965
100 1 44.7 1 9.544 4,319 1 L744 1 14.108 1 4,852 1
w 1 45.8 1 9.458 4,487 75.7 1 13.880 1 5,0811
U-127-N(07-05) A—6 SC L00 1 46.2 1 9.290 4,651 4,713 75.8 1 13.294 1 5,33fl 5,358
1L80 1 46.5 1 9.278 1 4718 1 757 1 13.131 1 5,33j
1 1000 1 46.4 1 9.113 1 4,77fl 764 1 13.119 1 5,39fl
L00 1 30.4 1 2.658 1 31,474 1 47.9 1 4.349 1 28 8&1
L0 1 30.9 1 2.535 1 33,999 48.7 1 4.299 1 30151
U-127-N(07-05) A—6 SC 15 500 1 31.5 1 2.333 1 36,628 1 36,054 491 1 4.290 1 27,523 27,729
180 800 1 31.6 1 2.285 1 36,290 1 L490 1 4.221 1 27 ,8?1
110000 1 32.5 1 2.231 1 35,2431 1 50.2 1 4.333 1 27 ,8IT1
1100 1 28.0 1 7.229 1 10,631 1 L118 1 12.878 1 11,660 1
L20 200 1 28.6 1 7.191 1 10,855 1 L 42.3 1 12.581 1 11,83fl
M—061—E(07—06) A24 SM 15 500 1 29.3 1 6.855 1 11,362 1 11,483 L432 1 12.189 1 13,155? 12 907
1 800 1 29.6 1 6.630 1 11,709 1 442 1 11.636 1 12,8311
1 1000 1 28.8 1 6.826 1 11,377 1 1 442 1 11.476 1 12,7361
11100 1 33.1 1 1.937 1 29,999 1 L512 1 2.807 1 30,104 1
1 200 1 32.9 1 1.864 1 30,417 L517 1 2.743, 1 30,51fl
M—061-E(08—02) A24 SM 1 500 1 33.8 1 1.897 1 32,344 1 32,231 1 52.1 1 2.713 131,55fl 31,763
1 800 1 33.8 1 1.930 1 32,106 1 51.9 1 2.701 1 31,7fl
1 1000 1 34.0 1 1.875 1 32,242 1 1 523 1 2.728 1 32,020 1
1100 1 41.4 1 10.662 1 3,592 1 1 709 1 14.499 1 4,516 1
1 200 1 42.3 1 10.310 1 3,829 1 lL717 1 13.972 1 4,771 1
_ - - 4 A—6 SC 500 42.9 9.824 4,076 4,134 728 13.214 5,099 5,268
UOIOWMO) 1 800 1 43.2 1 9.691 1 4,164 1 L71 12.850 1 53231
L000 1 42.9 1 9.608 1 4163 1 1 73.8 1 12.675 1 5,382 1

 

126

 

 

 

 

Table A.4 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cyclic stress (psi)
Soil Type C 1 10 15
Sample number 111111106; Acverlage Average Avelrage Average MR Average Average AVePage Avérage MR
1yc (11c deformation res1 ient (p81) at load cyclic deformation res111ent (ps1) at load
0a .1 ) modulus cycles 500, load (mils modulus cycles 500,
AASHTO USCS (lbs) 1”“ 5 (ps1) 800 and 1000 (lbs) ) (ps1) 800 and 1000
100 43.2 7.759 5,212 71.7 13.897 4,831
200 44.4 7.585 5,439 72.2 13.671 4,937
U—010—W (08—04) A—6 SC 500 45.6 7.430 5,791 5,873 73.0 13.508 5,049 5,106
800 45.9 7.266 5,946 73.6 13.342 5,130
1000 46.1 7.252 5,884 73.4 13.283 5,138
100 32.4 3.493 _~1_4,265_ 51.1 4.992 15,346
200 32.9 3.499 14,932 50.9 4.807 15,758
I—075—N (08—06) A—2—4 2;: 500 33.3 3.406 15,448 15,798 51.4 4.785 16,290 16,577
800 33.3 3.297 15,986 51.2 4.676 16,606
1000 33.1 3.263 15,960 51.3 4.594 16,836
100 33.8 2.123 26,881 52.3 3.220 26,018
200 33.9 2.126 27,797 52.8 3.183 26,982
U—131-S(09—01) A—3 SP 500 34.5 2.127 29,155 28,793 52.8 3.200 27,204 27,732
800 34.3 2.052 29,674 52.6 3.078 27,868
1000 34.6 2.152 27,550 53.2 3.081 28,124
100 33.5 2.694 20,127 52.0 4.254 18,607 *~
200 33.8 2.624 LILOQL 51.6 4.205 18,942
1—096—W (09-02) A-2-4 if; 500 33.7 2.566 _2_L58_8L 22,163 51.5 4.164 19,295 19,597
800 34.0 2.530 22,509 52.0 4.085 19,756
1000 33.8 2.473 22,392 51.2 3.999 19,740
100 33.9 1.997 28,736 LAJQEL
200 34.3 2.019 fl _i1_9_—_L3_34L__2$8_43_
U—131-S (09-03) A—3 SP 500 34.9 1.990 M 30,368 L52L1LL_3_006_____2£25L 28,022
800 34.0 JLM fifljfli
1000 34.4 1.983 _29L6_08__L__5_2i_ 2.953 28,925
100 34-0 $365333. Lifl
200 33.9 ,flo’jjfl flflfi
U—131—S(09—05) A—l—b SP WT 1.978 _38,8_18L 38,498 52.5 2.776 35,389 35,390
800 34.9 1.943 38,902 Lflfl
1000 __34L8_1 -2.-0912. E/ 52.5 2.856 35,340

 

//’——

127

 

 

Table A.4 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1» 1 Cyclic stress (psi) 7
Soil Type Cycle LA 10 1 15 —1
Sample number number Cvecrlaitge Average Avimge Average1M1: Average Average Average Average MR (psi)
1y deformation res11ent (ps1) at oa CyChC deformation res1lient at load cycles 500
oad . modulus cycles 500, load . modulus ’
AASHTO USCS (lbs) (“1115) (psi) 800 and1000 (lbs) (mils) (psi) 800and1000
100 1 33.4 1 2.943 1 17,969 1 51.4 4.275 1 18,433 1
200 1 33.5 1 2.928 1 18,261 1 52.0 4.175 19,068 1
M—044—E(09-07) A—2-4 SM 500 1 33.9 1 2.948 1 18,5341 18,434 51.6 4.086 19,511 1 19,654
800 1 33.7 1 2.841 1 18,7441 51.6 4.043 19,663
1000 34.0 3.046 1 18,023 1 51.9 4.041 19,788
100 33.1 3.415 1 15,1481 50.4 5.279 14,639
200 33.1 3.421 1 15,097 1 50.5 1 5.143 15,004
M-024—S(09—09) A24 SM 500 33.6 3.458 1 15,204 15,156 1 50.6 1 4.889 15,786 15,854
800 32.9 3.427 1 14,945 1 50.8 1 4.853 1 15,880
1000 33.3 3.378 1 15,318 1 51.0 1 4.891 1 15,897
100 34.0 1.985 1 29,263 1 52.2 1 3.321 1 25,428 1
200 34.1 1 2.074 1 29,172 1 1 52.2 3.248 1 25,7091
I—O69—E (0910) A—3 SP 500 34.4 1 2.071 1 28,746 1 28,663 52.3 3.163 1 26,255 1 26,095
800 34.3 1 2.079 1 29,2321 r519 3.231 1 25,8021
1000 34.8 1 2.160 1 28,012 1 52.4 3.192 1 26,227 1
100 33.5 1 3.483 14,917 1 51.2 4.732 1 16,473 1
200 33.5 1 3.542 14,8641 51.1 4.694 1 16,512 1
1-069-N(10—01) A—3 311:, 500 33.1 3.344 15,5511 15,873 51.3 1 4.485 1 17,528 1 17,394
800 33.8 3.457 15,312 1 1 50.8 1 4.533 1 17,1441
1000 34.0 3.162 16,756 1 51.7 1 4.526 1 17,509 1
100 32.9 2.180 41,549 1 50.1 1 3.266 1 40,469
200 33.4 2.210 42,092 1 50.5 1 3.275 41,776
I—096—W(10—03) A—2-6 SC 500 33.8 2.175 43,219 43,824 W5 1 3.167 42,767 37,712
800 34.1 2.196 44,499 49.2 3.779 34,806
1000 34.1 2.203 43,754 48.7 2.686 35,563
100 33.4 2.846 18,890 51.4 4.400 18,049
200 33.5 2.771 19,221 51.8 4.330 18,293
I-069—N(10—04) A24 SM 500 33.5 2.839 19,530 19,190 51.0 4.232 18,653 18,963
800 33.4 2.862 19,049 51.5 4.107 18,952
1000 33.9 2.802 18,990 51.6 4.076 19,284 1

 

128

 

 

Table A.4 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

r Cyclic stress (psi)
Soil Type C 1 10 15
Sample number nuiiib; ACverlage Average Avelrage Average MR Average Average Average Average MR
yc lc deformation res1 1ent (ps1) at load cyclic deformation resfllent (pSl) at load
load . modulus cycles 500, load . modulus cycles 500,
AASHTO USCS (lbs) (”1115) (psi) 800 and1000 (lbs) (mils) (psi) 800 and 1000
100 25.4 8.607 4,2731 37.6 15.895 3,469
, 200 25.9 8.326 4,542 41.3 12.494 4,766
I—069—N(10—05) A—2-4 SM 500 27.0 7.715 5,123 5,295 43.1 11.611 5,377 5,646
800 27.2 7.630 5,241 43.7 11.104 5,712
1000 27.6 7.381 5,521 43.8 11.027 5,850
100 30.1 5.580 8,027 47.9 7.602 9,168
200 30.9 5.176 8,832 48.1 7.430 9,504
1—096—W(10—09) A24 SM 500 31.2 5.002 9,361 9,518 49.5 6.721 10,908 11,394
800 31.0 4.917 9,419 49.5 6.363 11,495
1000 31.6 4.875 9,775 49.8 6.307 11,778
100 32.9 1.119 30,534 51.7 1.595 29,788
200 33.8 1.119 32,960 52.0 1.567 30,484
1—069—N(11-01) A-3 31:4 500 34.0 1.063 30,406 30,733 52.0 2.994 28,203 28,147
800 34.0 1.119 30,967 52.2 2.974 28,154
1000 34.8 1.1171 30,827 51.9 2.995 28,083
100 33.6 1 1.694 1 36mg 51.2 3.205 25,752
200 33.3 1 1.627 1 37.96fl 52.2 3.144 26,35
I—094—W(11-02) A—3 SP 500 34.1 1 1.487 1 45,14L1 44,521 52.8 1 3.102 27,4421 27,372
800 32.6 1 1.432 42,908 L519 1 3.136 1 26,857
1000 34.1 1.453 45,513 1752.6 1 3.020 1 27,817 1
100 31.9 2.614 19,615 1 50.2 1 4.354 1 17mg
200 31.3 2.561 19,255 F507 1 4.426 1 17,262
M-060-W(11—03) A24 2134 500 32.0 2.553 19,808 19,812 171.8 1 4.481 16,817 16,639
800 32.4 2.561 19,861 50.7 1 4.560 16,601
1000 32.2 2.563 19,768 50.9 4.669 16,498
100 33.7 2.252 23,451 52.3 3.358 24,923
200 33.8 2.220 24,393 52.6 3.317 25,291
I—069—S(11-05) A—4 315,, 500 34.0 2.095 25,903 27,303 52.5 3.274 25,489 25,645
800 34.2 2.014 26,908 51.6 3.267 25,632
1000 34.3 1.931 29,098 52.2 3.245 25,814

 

 

 

 

 

 

 

129

 

 

 

 

 

Table A.4 (cont’d)

 

 

 

    

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1 Cyclic stress (psi) fl
1 10 1 15 1
Sam 13 number Cycle Avera e Avera e Avera eMR Avera
p number cyclif (16:11:88.1:011 resiliefit (psi)zigtload cyclicge d fivemg? 8:111:11: [1182;315:3111
load (mil ) modulus cycles 500, load e ornlatlon modulus cycles 500,
AASHTO USCS (lbs) 5 (p31) 800 and1000 (lbs) (mus) (psi) 800 and 1000
1 100 1 33.3 1 1.963 1 28,024 1 L13 1 3.519 1 22,990 1
1 SO 1 200 1 32.5 1 2.028 1 27,129 1 1 52.0 1 3.594 1 23,0241
1-094-W(12-01) A24 SM 500 1 34.1 1 2.041 1 28,985 27,636 1 51.8 1 3.438 1 23,554 1 23,872
800 33.6 2.129 1 26,615 1 52.0 1 3.414 1 24,001 1
1000 33.9 2.113 1 27,308 1 52.4 1 3.534 1 24,0601
100 33.6 2.783 1 19,527 1 50.8 1 4.851 1 15,566 1
SP_ 200 33.6 2.766 19,827 1 1 50.9 1 4.881 1 15,796 1
I—094—W(12—03) A—3 SM 500 33.4 2.814 18,886 1 18,139 1 50.4 1 4.789 1 16,090 1 15,977
800 33.9 3.021 17,8201 1 50.8 1 4.831 1 15,893 1
1000 34.1 3.066 17,711 1 50.8 1 4.798 1 15,947 1
100 33.3 2.862 18,848 1 50.8 1 4.340 1 18,416 1
SP 200 33.3 1 2.930 1 19,047 1 51.3 4.323 1 18,6831
U—012—E(12—04) A24 SM 1 500 33.6 1 2.781 1 19,237 19,234 51.2 4.264 1 18,191 1 18,343
1 800 1 34.1 1 2.881 1 19,210 51.4 4.312 18,324 1
1 1000 1 34.1 1 2.766 1 19,255 51.3 4.266 18,515 1
1 100 1 33.9 1 2.675 1 19,996 51.4 4.042 19,797
200 33.8 1 2.698 1 20,013 51.4 3.956 20,110
I-094—W(12-06) A24 SM 500 33.7 2.821 1 19,357 19,425 52.6 3.873 21,249 21,382
800 33.8 2.796 19,802 1 51.7 1 3.733 21,552
1000 34.0 2.792 19,115 1 51.5 1 3.774 21,346
100 34.4 3.172 17,093 1 51.9 1 5.000 1 15,7461
200 34.0 3.101 17,359 1 1 50.0 1 4.846 1 15,814
M-024—S(13-01) A-4 SM 500 34.8 3.149 17,853 1 17,950 1 51.5 1 4.878 1 16,2131 16,175
800 34.6 3.049 mg W6 1 4.844 1 16,042
1000 35.1 3.052 18,106 1 F518 1 4.844 1 16,271 1
100 33.6 2.042 28,216L1 1 51.7 1 3.362 1 23,959
200 1 33.5 2.112 27,6L1 519 1 3.351 1 24,234
M—059-W(13-02) A-3 SP 500 1 33.9 1 2.186 1 26,464 24,863 17.1 1 3.478 23,699 23,810
1;800 1 33.9 1 2.368 1 24,6i1 L517 1 3.453 23,8&
W000 1 33.8 1 2.439 1 23,502 1 51.9 1 3.436 23,849

 

 

 

 

 

 

 

Table A.4 (cont’d)

 

1 Cyclic stress (psi) j

M 10 1 1s

Cycle Average Average Average MR Average Average Average MR

Soil Type

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sample number number cyclic de101r111312n resilient (psi) at load cyclic de/Everage resilient (psi) at load
load (mils) modulus cycles 500, load gigglon modulus cycles 500,
(lbs) (ps1) 800 and 1.000 (lbs) (psi) 800 and 1000
1 100 1 32.8 1 2.693 1 20,399 1 1 51.2 1 4.441 1 17,533 1
1 200 1 32.5 1 2.615 1 20,565 1 1 50.7 1 4.353 1 17,8571
1—094-W(13—04) A—3 SP 1 500 1 33.2 1 2.592 1 21,384 1 21,470 L 50.8 1 4.245 1 18,355 1 18,859
1 800 1 33.5 1 2.589 1 21,598 1 1 50.8 1 4.133 1 18,8361
1000 33.4 1 2.648 1 21,4271 1 51.2 1 4.040 1 19,3871
100 34.0 1 2.515 1 22,197 1 1 51.6 1 3.907 1 20,649 1
200 33.8 2.443 1 23,009 1 1 51.4 1 3.846 1 20,641 1
U-023—N(13—07) A-3 31:, 500 34.0 2.573 1 22,214 1 22,629 L512 1 3.961 1 20,201 1 20,593
800 33.9 2.428 1 22,768 1 L 52.4 1 3.910 1 20,900 1
1 1000 34.7 2.477 1 22,904 1 1 52.2 1 3.952 1 20,678 1
1 100 29.7 1 4.124 1 16,710 1 1 45.5 1 6.531 1 16,006 1
1 200 30.1 1 4.182 1 16,898 1 1 46.1 1 6.637 1 15,991 1
M—010-E(13—08) A6 CL 1 500 1 30.2 1 4.256 1 16,8551 17,012 1 46.3 1 6.562 1 16,218 1 16,345
1 800 1 30.7 1 4.226 1 16,995 1 1 46.5 1 6.433 1 16,417 1
1 1000 1 30.5 1 4.202 1 17,186 1 1 46.6 1 6.492 1 16,399 1 ‘
1 100 1 48.6 1 3.375 1 14,3741 1 77.7 1 7.441 1 9,934 1
1 200 49.6 1 3.334 1 15053 1 1 78.1 1 7.453 1 9,867 1 .,
M—OlO—E(13-08) A—6 CL 1 500 49.6 1 3.271 1 15,4231 15,561 1 78.2 1 7.743 1 9,627 1 9,553
800 49.8 1 3.258 1 15,631 1 1 78.2 1 7.779 1 9,528 1
1000 49.8 1 3.257 1 15,629 1 1 78.3 1 7.849 1 9,504 1
100 51.5 1 1.331 1 31,968 1 1 83.3 1 1.796 1 36,929 1
200 51.8 1 1.291 1 36,534 1 1782.8 1 1.731 1 38,4881
M—010-E(13-08) A-6 CL 500 1 52.7 1 1.218 1 43,564 44,641 1 82.5 1 1.808 1 40,155 1 41,989
1800 1 52.3 1 1.211 1 45,0891 1 82.2 1 1.629 1 42,399
W00 1 51.8 1 1.152 1 45,271 1 1782.4 1 1.793 1 43,414
1 100 1 39.6 1 7.658 1 8,407 1 1 46.6 1 8.078 1 8,440
200 1 41.3 1 7.157 1 9,399 1 177.1 1 7.723 1 8,966
M-010-E(13-08) A-6 CL 500 1 42.2 1 6.971 1 9,004 9,713 1 48.6 1 7.368 1 8,822 8,280
800 1 43.5 1 6.473 1 9,818 1 1 48.8 1 7.052 1 8,108
1000 1 44.0 1 6.376 1 10,317 1 1 48.5 1 7.166 1 7,910

 

131

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table A.4 (cont’d)
F 1 Cyclic stress (psi) j
Soil Type C cle L 10 1 15 —1
Sample number nuiilber i2??? Average :Z:li:i: gigaafielxg Average Average Avelrage Average MR
deformation cyclic load deformation re51 1ent (p31) at load
load '18) modulus cycles 500, lb .1 modulus cycles 500,
AASHTO USCS abs) (m1 (ps1) 800 and 1000 ( S) (“1”) (psi) 8001111111000
100 1 30.3 1 2.283 1 11,369 48.9 1 3.899 1 14,813 1
200 1 31.0 1 2.259 1 13,560 48.7 3.804 1 15,893 1
I—075—S(14~01) A-7—6 SC 500 1 31.3 2.074 1 17,389 18,221 48.9 3.721 1 16,9?1 17,842
800 1 31.7 1.971 18,449 49.6 3.586 1 18,253
1000 32.0 2.067 18,825 49.6 3.573 1 18,336
100 51.3 2.172 32,901 82.3 2.390 1 32,808
200 51.2 1.994 36,098 82.8 1 2.299 1 31,287
I—O75—S(14—01) A—7-6 SC 500 52.3 1.815 31,799 32,510 82.7 1 2.045 1 29,226 29,860
800 52.3 1.481 32,377 82.4 1 1.858 1 30,295
1000 51.7 1.417 33,354 82.3 1 1.668 1 30,060
100 35.0 10.936 5,114 61.1 14.155 1 6,907 1
200 35.9 9.896 1 5,982 61.6 13.624 7,285 1
I—O75-S(14-01) A-7—6 SC 500 36.6 9.349 1 7,441 7,187 62.5 12.617 7,928 1 8,386
800 36.7 8.808 7,284 63.5 12.002 8,545 1
1000 37.3 8.616 6,835 64.1 11.896 8,685 1
100 32.7 2.313 21,994 51.7 3.526 19,968 1
200 33.0 2.337 22,227 52.0 3.540 20,296 1
U—024-S (14-04) A—3 SP 500 33.5 2.305 22,633 22,765 52.3 3.336 21,874 21,913
800 33.6 2.300 22,813 52.1 3.396 21,707
1000 33.6 2.297 22,849 52.4 3.329 22,159
100 42.5 10.621 3,715 65.6 19.895 3,023
200 42.7 10.593 3,736 65.4 19.906 3,021 _,
M—153-E(14—06) A—7-6 SC 500 42.8 10.681 3,717 3,732 66.4 20,023 3,036 3,015
800 42.9 10.628 3,745 66.4 20.120 3,014
1000 43.1 10.729 3,733 66.0 20.123 2,995
100 29.2 13.397 3,483 65.6 19.995 4,023 ,
200 30.3 12.818 3,798 65.4 19.996 3,821
M-153-E(14—06) A—7—6 SC 500 1 32.1 12.062 1 4,285 4,430 66.4 20.017 3,936 3,915
' 800 1 32.8 11.875 1 4,471 66.4 21.120 3,814
1000 1 33.0 11.708 1 4,535 66.0 21.123 3,995
132

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table A.4 (cont’d)
Cyclic stress (psi) 1
Soil Type Cycle A 1: A 15 1
11M MR
deformat1on yc 10 deformation res1lient (P31) at 103d
load . modulus cycles 500, load . modulus cycles 500,
AASHTO USCS (lbs) (”1113) (psi) 800 anleOO (lbs) (mils) (psi) 800 anleOO
100 33.8 1 2.378 38,348 51.2 3.050 1 42,427 1
200 34.4 1 2.254 139,970 51.5 2.964 1 42,728 1
M-153-E(14-06) A-7—6 SC 500 34.5 2.223 40,365 40,902 51.4 3.004 1 43,684 1 44,483
800 34.0 2.119 41,453 51.5 2.965 1 44,394 1
1000 33.7 2.120 40,889 52.2 2.876 1 45,372
100 33.6 2.237 25,772 51.5 1 3.727 1 21,646
200 33.6 2.150 25,870 1 51.7 1 3.731 1 21,643
M-053—S (14—07) A—3 SP 500 33.9 2.249 26,465 25,738 1 51.9 1 3.688 1 22,217 22,296
800 34.0 2.258 25,493 1 52.0 1 3.646 1 22,403
1000 33.7 2.315 25,255 1 51.8 1 3.622 1 22,268
100 49.1 5.308 8,870 1 77.2 1 9.347 1 7,782
200 49.1 5.217 9,211 1 77.2 1 9.253 1 7,846
I—094-W(14—09) A—7—6 CL 500 49.2 4.966 19,690_ 9,955 77.1 9.107 1 7,995 8,080
800 48.8 4.777 1 9,943 77.8 9.010 8,089
1000 49.2 4.675 10,234 77.8 8.918 8,156
100 51.2 2.114 45,953 81.9 2.609 57,985
200 51.1 1.853 52,917 82.8 2.466 61,580
1-094—W(14—09) A—7-6 CL 500 52.2 1.602 67,009 73,344 82.5 2.327 67,663 70,094
800 52.7 1.426 75,719 82.2 2.190 70,504
1000 51.2 1.383 77,304 81.8 2.205 72,116
100 33.0 1.604 53,229_ 50.7 2.211 57,722
200 32.7 1.585 55,517 51.7 2.228 59,950
I—094—W(14—09) A-7—6 CL 500 33.8 1.530 60,326 60,217 51.7 2.152 60,448 60,303 r
800 34.1 1.462 60,280 51.8 2.104 60,142
1000 34.2 1.459 60,046 . 52.3 2.044 60,318
100 33.3 2.923 18,400_ 51.1 4.424 18,022 .
200 33.2 2.914 18,486 51.0 4.470 18,018
M-053—S(15—02) A—2-4 SM 500 33.4 2.921 18,171 18,342 51.4 4.471 17,918 18,060
800 33.4 2.963 18,372 51.3 4.416 18,1841
1000 33.4 2.894 18,483 51.0 4.372 18,149
133

 

 

 

 

Table A.4 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Cyclic stress (psi)
Soil Type 10 15
Sample number 1133:1045; Average Average AV31age Average MR Average Average “gage Average MR (psi)
013(1) (:1; deformation 55:33:: (013536? 513?? 01:21:: deformation $3353: at load cycles 500,
AASHTO USCS (lbs) (mils) (psi) 8011) and 1000 (lbs) (mils) (psi) 800 and 1000
100 34.6 1.494 65,657 51.5 2.170 60,204
200 34.2 1.492 65,191 51.9 2.192 61,455
M—090—E (15—04) A—4 CL 500 34.6 1.487 67,087 67,841 51.7 2.159 61,666 62,065
800 34.6 1.510 68,335 51.7 2.128 62,105
1000 34.5 1.398 68,102 52.0 2.212 62,423
100 34.0 1.585 37,971 52.6 2.503 35,506
200 34.0 1.601 38,716 52.2 2.445 35,369
M—025—S (15—05) A—3 SP 500 34.1 1.588 39,705 40,152 51.7 2.500 35,195 35,481
800 34.9 1.643 40,506 52.3 2.468 35,680
1000 35.0 1.595 40,246 52.0 2.437 35,567
100 34.3 2.740 19,702 51.3 4.328 18,630
200 35.7 2.770 20,960 51.9 4.203 18,904
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800 35.2 2.539 22,379 51.4 4.096 19,441
1000 34.6 2.572 22,462 53.2 4.183 19,750 1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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139

APPENDIX B

NDT data test results

140

This appendix contains two tables; Table 8.1 provides a list of the results of
backcalculated layer moduli of roadbed soils supporting flexible pavements.
Table 32, on the other hand, provides the results of the backcalculated layer moduli of

roadbed soils supporting rigid pavements

141

Table B.1 Backcalculated results of flexible pavement

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

- - . Pavem t Back I '
Locat1on Ragged FWD F11e Informatlon thicangslgiiir L Error Co::6:1;leacil?oi1Depthto i Resilient modulus (pSi)
. Cluster— . . As halt Base/ RMS Stiff
Reglon Road area USCS F116 we conirete subbase (%) Yes NO 121116; $1322: sfbaljie Roadbed
North US-131 0701 SM flex—N—USI31—CS670l7-05—01—2002 7.25 22 0.63 79 14 l 700 l 1696003 I 26912 I 23263
Superior US—2 0201 SM flex-Su—USZ—CSZ7022—05-20—2008 3.5 26.5 1.47 7 l 250 I 972815 [45256 I 211327
Grand M—57 0901 SP1 flex—G—M57—CS41122-8—23-1994 3 26 1.20 81 | 27 700 2446547 | 44131 l 294%
Grand M-57 0901 SP1 flex-G—M57—C828021-5-23-1995 3 26 1.38 20 l 63 700 3871662 l 33601 32384
Grand M-57 0901 SP1 flex-G—M57—CSS9021—08-23-1994 3 26 1.21 40 13 700 2756285 l 42908 29943
Grand M57 0901 SP1 flex—G-M57—CSS9021—08—23—1994—(2) 3 l 26 1.27 43 10 700 2680244 43546 29965
Grand M67 0901 SP1 flex—G—M57—CSS9021—08—23—1994—(3) 3 l 26 1.32 34 20 700 2657574 44229 32430
Grand M—57 0901 SP1 flex—G-M57—CSS9021—08-23-1994—(4) 3 l 26 1.27 33 20 700 2663880 43749 28829
Grand US- 1 31 0703 SP1 flex—G—US 1 3 1—CS54013—08— 1 8—1994 7.25 | 24 1.13 43 22 700 370266 38527 27557
Grand US-131 0703 SP1 flex—G-USI31—CSS4013—08—18—1994-(2) 7.5 22 1.49 16 16 700 372701 38341 31242
Grand US-131 0703 SP1 flex-G-USI31—CSS4013—08—18-1994-(3) 7.5 22 1.51 18 15 700 351947 38155 I 30740
Grand US—131 0703 SP1 flex—G—Us131—CS54013—08—18—1994—(4) 7.5 22 1.15 47 18 700 354711 37817 I 27911
Grand US—131 0703 SP1 flex—G—USI31-CSS4013—08—18—1994-(5) 7.5 22 1.52 18 15 700 351862 38153 30744 l
Grand M—120 33‘s: :1 flex—G—MlZO—CS61012—07—23-1998 7 24 1.43 28 46 700 191605 28836 18572 1
Grand US-131 0901 SP1 flex—G-USI31—CSS9012—06—25-l998 l 8 24 1.46 20 5 700 529653 38384 29069 I
Grand M—37 0703 SP1 flex—G—M37-C862032-05—18—2000 l 8 25 1.28 25 15 700 433004 21019 20953
Grand US—131 0702 SP1 flex—G-USI3l—CSS4013-08-18—1994 l 7.25 22 1.26 130 51 700 937313 30697 34067
Grand M—20 0703 SP1 flex—G-MZO—CSS4041—O4—09-2002 l 6 24 1.09 48 20 700 592526 24492 25668
North 1-75 06-02 SP1 flex-N-I75-CS69014-11-12—1997 l 6.25 24 1.09 61 l 36 700 1073344 37124 30358
North 1-75 06—02 SP1 flex—N-I75—CS69014—08—03-1999 6.25 24 l 1.34 l 62 l 28 700 460044 49111 31074
North 1-75 06—02 SP1 flex-N-I75-CS69014-08—03-1999—(2) 6.25 24 l 1.36 l 61 l 29l 700 I 516468 55316 40422
North 1—75 06-02 SP1 flex-N-I75-CS690l4—l1-23—1997 6.25 24 1.09 l 71 l 22 l 700 I 976787 | 38138 30700
North 1-75 06—02 SP1 flex-N—I75-CS69014—08-04—1999 6.25 24 1.36 l 65 l 27 l 700 I 364430 [48793 J 30134
North 1-75 06—02 SP1 flex—N—I75-CS69014—08—04-1999—(2) 6.25 24 1.53 l 63 l 48 l 700 I 440817 I 52962 I 40183
North M65 0504 SP2 flex-N—MSS—CS77022-8—20—2001 7 23 1.75 l 32 l 44 l 700 I 253762 I 29680 I 23140

 

 

 

 

 

 

 

 

142

 

 

 

Table B.1 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I¥ Location Roadbed FWD File Information 1113;221:313 Ijnor B:::::::a;1?on DeptfiI Resilient modulus (psi)
‘ type stiff
. Cluster— . . As halt Base/ RMS
Reglon Road area USCS F11et1tle conirete subbase (%) Yes No 1:111]: I $22132: 811135516 Roadbed
North M—55 0504 SP2 flex—N—MS5—CS77022—8—20—2001—(2) 7 23 1.74 35 41 700 250435 29872 I 22953I
Superior M-28 03-01 SP-SM flex-Su—M28-CS75061—05—21-2008 5.5 24.5 0.65 11 0 700 1719937 27402 I 21272
Superior US—2 03—01 SP-SM flex-Su—US2-CS75021—05-22—2008 5.5 24.5 1.28 10 1 300 3987549 60149 I 20953 I
Superior M-28 03-03 SP—SM flex—Su—M28—CS17061—05—22—2008 5 25 I 0.66 10 0 700 2255609 23293 21652 I
North US—23 04—02 SC—SM flex—N—US23—CS4032—06—03—2008 5 25 1.49 9 2 150 2126531 59749 1438fl
North US-23 04—02 SC-SM flex—N—USZ3—CS71073—06—04—2008—(2) 5.5 24.5 1.60 8 3 300 2175426 63071 236m
North US—23 04—02 SC—SM flex—N-USZ3—CS71073—06-04—2008 6.5 23.5 0.87 11 0 700 540464 32021 2072fl
North US:23 04—02 SC—SM flex—N—US23—CS1052—06—03—2008 3.5 26.5 1.77 6 5 200 1292560 62082 16445
Bay M-57 09-08 SC flex-B—M57—CSZ9022—O8—30—1994 5.5 25 1.41 43 23 700 278977 26637 26310 I
Bay M-57 09—08 SC flex—B—M57-CS29022—08-30-1994—(2) 5.5 25 1.39 41 25 700 278587 26544 26385 I
Bay M—57 09—08 SC flex—B—M57—CSZ9022—O8—30—1994—(3) 5.5 25 1.70 25 42 700 265828 27872 2929fl
Bay M—57 0908 SC flex—B—M57—CSZ9022-O8—30—1994—(4) 5.5 25 1.69 24 43 700 266435 27982 296m
Bay M—57 09—08 SC flex-B-M57-CSZ9022—01-28-1993 5.5 26 1.41 65 69 700 269243 26067 25798
Bay M—84 09—08 SC flex-B—M84-CS9011—10—03—2005 4 25 1.52 8 8 200 412843 35590 22034
Bay M—84 09—08 SC flex-B—M84-CS9011—05-17—2005 4 25 1.07 30 9 300 1058438 24543 19099
Bay M-84 09—08 SC flex-B-M84—CS9011—05—17—2005—(2) I 4 25 1.15 52 17 400 1224141 23099 20129
Bay M—84 09—08 SC flex-B-M84—CS9011-10-10—2005 I 4 25 0.97 16 0 275 1179156 34888 25923
Bay M—84 09-08 SC flex-B—M84-CS9011—09-11-2005 I 4 25 1.40 30 2 160 2959369 47342 19575
Bay M-84 09-08 SC flex-B-M84—CS9011-09-13—2005—(2) I 4 25 0.91 16 0 250 774323 32298 27322
Superior 1-75 0305 SC flex-Su-I75—CS49025—05-22—2008 7.5 22.5 I 1.41 I 4 I 7 I 150 I 783951 I35186 55215
University M—52 10-10 SC flex—U-M52~CS33051—11—13—2002 6 24 I 1.14 I 39 I 5 I 250 I 776627 I23650I 23582
Metro M—53 14-08 CL flex—M—M53—CSSOOI5—04—04-2008 8 24 I 1.07 I 9 I 2 I 300 I 1122329 I 16031 I 22259
Metro 194 1409 CL flex—M—I94—CS77111—04—02—2008 4.2 17.5 I 1.78 I 5 I 19 I 100 I 1937770 I 11660 I 4763
Superior M—38 0101 CL flex—Su—M28-CS66042—05—20—2008 3.5 26.5 I 1.58 I 10 I 1 I 350 I 1468878 I 32573 I 18372 I
Superior US—41 0204 ML flex-Su—US41—CS7013—05-19-2008 2.5 27.5 I 1.28 I 11 I 0 I 150 I2059728 I 29874 I 10531 I
Superior US—141 0202 ML flex—Su—US141—CS7022-05-19—2008 4.5 25.5 I 1.10 I 12 I 1 I 700 I 1075462 I 16677 I 21265 I

 

 

 

 

 

 

143

 

 

Table B.2 Backcalculated results of rigid pavement

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Location Roadbed FWD File Information COIICECte
e S a Number Roadbed Roadbed MR
Region Road Chm“ U348 Season Date File tit1e thickness OfteStS Slab (EC) K (pd) (p51)
area (1n)

Bay US—23 09—09 SM Summer 10/21/1998 rigid—B—US23—C82503 1—10-21—1998 9 34 4,320,980 437 33,920
Bay US-23 09—09 SM Summer 5/30/2001 rigid-B-US23—CS25031—05-30-2001 9 46 2,748,666 351 27,250
Bay US—23 09—09 SM Summer 8/23/2005 rigid-B—US23—CS25031—08-23—2005—(2) 9 17 1,792,001 392 30,384
Bay 1—475 09—09 SM Summer 6/26/1997 rigid-B—I475—CS25132-06—26—1997 9 60 3,104,905 283 21,958
Bay I~475 09—09 SM Summer 6/24/2001 rigid—B—I475—CS25132—06—24-2001 9 66 2,263,476 307 23,832
Grand 1—96 09—07 SM Summer 6/27/2001 rigid—G—I96—CS34044—06-27-2001 9 21 1,268,974 347 26,950
UniVerSity 1—69 10-04 SM Summer 9/10/2007 rigid—U-I69-CSZ3063-09-10—2007 10 30 2,199,553 298 23 132
Grand US-131 07-03 SP1 Summer 4/9/1998 rigid-G—USI31—CSS9012—04-09—1998 9 22 782,808 338 26:229
North 1-75 05—02 SP1 Summer 9/17/2001 rigid-N—I75-CS16091—09—17-2001 9 69 1,501,914 259 20,106
North 1—75 0502 SP1 Summer 10/26/2001 rigid-N—I75-CS16091—10-26—2001 9 53 1,779,633 267 20,708
North 1—75 05—02 SP1 Summer 9/18/2001 rigid—N—I75—CS16092-09—18-2001 9 98 1,283,968 289 22,414
North 1—75 0502 SP1 Summer 9/27/2001 rigid-N—I75—CS160992-09—27—2001 9 86 1,370,042 273 21,186
Superior M—28 03—04 SP1 Summer 5/8/2001 rigid-Su—M28—CS17062-05—08-2001 8 80 1,874,921 235 18,226
Superior 1—75 03—04 SP1 Summer 5/31/2000 rigid—Su-I75-CS17033-05-31—2000 9 49 1,199,440 218 16,931
Superior 1—75 03—04 SP1 Summer 5/25/2000 rigid-Su—I75-CS17034-05-25—2000 9 16 1,330,163 247 19,141
Superior I-75 03—04 SP1 Summer 5/22/2000 rigid-Su—I75—CS17034—05~22-2000 9 21 1,523,738 224 17,367
Bay US-23 09—10 SP2 Summer 8/30/2005 rigid-B-US23-CS25031-08-30-2005 10 19 1,371,563 407 31,592
Bay US-23 09—10 SP2 Summer 8/23/2005 rigid—B—US23—CS25031—08—23-2005 10 27 1,487,442 386 29,920
Bay US-23 0910 SP2 Summer 11/15/2005 rigid-B-USZ3—CS25031—11-15-2005 10 68 1,082,723 339 26,345
Bay US—23 09—10 SP2 Summer 11/16/2005 rigid-B—US23—C825031—11—16—2005 10 31 1,025,612 234 18,134
Bay US—23 0910 SP2 Summer 11/16/2005 rigid—B—US23—Cs25031-11—16—2005—(2) 10 48 958,993 259 20,107
North 1—75 05—04 SP2 Summer 8/30/1997 rigid—N-I75—CS65041—08-30—2001 9 20 1,333,695 304 23,622
North 1—75 0504 SP2 Summer 9/14/2001 rigid—N—I75—CS65041-09—14—2001 9 29 1,159,426 245 19,038
University 1-94 13—04 SP2 Summer 11/19/2006 rigid—U—I94~C882021—11-19-2006 10 333 2,764,869 311 24,146
Southwest 1-94 12-05 SP-SM Summer 11/18/2002 rigid-So—I94—CSI1081-11-18-2002 9 84 1,402,982 216 16,759
Southwest 1—94 12—05 SP-SM Summer 10/28/2004 rigid-SO-I94—CSI1081—10-28—2004 9 66 1,285,711 223 17,299
Southwest 1-94 1205 SP—SM Summer 10/30/2001 rigid-So—I94-CS1 1081—10-30—2001 9 12 1,247,204 192 14,871
Southwest US—31 06-05 SP—SM Summer 10/9/2001 rigid—SO—US31—CSI1057-10-09—2001 9 28 819,421 194 15,028
Southwest US-31 06—05 SP—SM Summer 10/30/2001 rigid—So-US31-CS11057—10-30—2001 9 27 1,909,724 192 14,879
Southwest US—31 06—05 SP—SM Summer 6/6/2003 rigid-SO—US31—CSI1057-06-06-2003 9 16 1,398,211 240 18,636
Southwest US—31 06—05 SP—SM Summer 4/18/2008 rigid—So—US31—CSI1057-05-14—2008 9 33 3,943,545 218 16,897

 

 

144

 

 

 

Table B.2 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Location Roadbed FWD File Information (101102616 7
e s a Number Roadbed Roadbed MR
Region Road Cluster— US$235 Season Date File title thiclmess 0f tests Slab (EC) K (pci) (psi)
area (1n)

Southwest US—31 06-05 SP—SM Summer 11/9/2007 rigid-So—US31—CS3032—11—09—2007 10 33 2,444,743 390 30 295
Southwest 1—196 06-04 SP—SM Summer 5/14/2008 rigid—So—I 1 96—CS3033-05-14—2008 9 33 7,774,538 303 23 ’527
Southwest 1—196 06—04 SP-SM Summer 9/11/2007 rigid—So—Il96—CS3033-11—09-2007 9 36 5,170,572 445 34,562
Superior M—28 03—01 SP—SM Summer 8/23/2001 rigid—Su-M28—C802041—08—23—2001 10 21 1,288,074 259 20,073

Superior M-28 03—01 SP—SM Summer 8/23/2001 rigid—Su—M28—CSOZO41-08—23—2001—(2) 10 46 1,006,652 209 16,199 i
University US-23 13-06 SP—SM Summer 9/14/2006 rigid-U—US23—CSS 8034—09-14-2006 10 79 931,042 365 28,310
Bay 1—75 08—06 SC—SM Summer 9/13/2001 rigid—B—I75—CS61 11—09—13—2001 9 57 1,617,746 286 22,182
Grand US-131 09—02 SC—SM Summer 11/7/1996 rigid-G—US131-CS41131—07-11—1996—(2) 9 9 2,055,282 313 24,279
Grand M-6 09—02 SC—SM Summer 9/15/2004 rigid—G—M6—CS41064-09-15—2004 10 57 2,657,345 392 30,406
Grand M—6 09—02 SC-SM Summer 9/8/2004 rigid-G-M6-CS41064-09—29-2004 10 653 6,913,721 262 20,344
Grand M—6 09-02 SC—SM Summer 9/8/2004 rigid—G—M6—CS41064-09-08-2004 10 665 6,929,648 262 20,329
Grand M—6 09—02 SC-SM Summer 11/15/2001 rigid—G—M6—CS41064—11—15—2001 10 159 3,091,380 253 19,654
Southwest I-69 11-03 SC—SM Summer 9/11/2001 rigid-So—I69-CS12034—09-11—2001 9 39 2,551,331 384 29,825
Southwest 1—69 11—03 SC—SM Summer 10/8/1998 rigid-So—I69—CS120314—10-08—1998 9 7 1,224,345 342 26,522
Southwest 1—69 11—03 SC~SM Summer 10/9/1998 rigid—So—I69-CS 12034~10-09—1998 9 7 1,385,348 313 24,319
Southwest 1-69 11—05 SC-SM Summer 12/18/2001 rigid—So—I69—CS 12033—12-18-2001 9 65 2,286,690 253 19,637
University US-127 10—02 SC—SM Summer 6/15/1998 rigid—G—US27-CS 19033~06-15—1998 10 249 3,688,356 222 17,215
University US-127 10—02 SC-SM Summer 11/7/2007 rigid-U—US127—CS 19034-1 1-07-2007 10 31 7,943,405 379 29,442
Bay US—127 09—08 SC Summer 6/27/2008 rigid—B—U8127—CS2901 1—06—27-2008 9 33 5,013,736 255 19,785
Bay 1—75 09-08 SC Summer 8/15/2001 rigid—B175—CS73 101—08—15-2001 9 47 1,249,188 244 18,953
Bay 1—75 09—08 SC Summer 11/30/1999 rigid—B175—CS73101—11—30—1999 9 19 2,514,512 257 19,970
Bay 1-75 08-04 SC Summer 7/2/2008 rigid—B—I75—CS3035—07—02—2008 9 36 4,624,514 272 21,138
Bay 1-675 09-08 SC Summer 10/24/2003 rigid—B—I675—CS73101—10-24—2003 9 72 1,298,419 291 22,548
Bay 1-675 09—08 SC Summer 5/26/2004 rigid—B—I675—CS73101—05—26—2004 9 49 1,322,471 285 22,091
Bay I—675 09-08 SC Summer 10/14/2004 rigid—B—I675—CS73101-10—14—2004 9 75 986,784 225 17,439
Bay 1—675 09—08 SC Summer 12/5/2005 rigid—B—l675—CS73101—12—05—2005 9 63 1,634,031 281 21,767
Bay US—10 08-04 SC Summer 12/18/2007 rigid—B—US10—CS9101—12-18—2007 7.3 36 4,976,290 290 22,537
Bay US—127 07—05 SC Summer 12/19/2007 rigid—B—US127-CS37014-12—19-2007 8 45 2,490,183 475 36,844

Metro M—5 13—03 SC Summer 11/29/2006 rigid—M—MS—CSOOOOO-l1—29—2006 10 69 2,378,364 304 23,566 1

Metro M-10 14-06 SC Summer 10-3-2007 rigid—M-MlO-C882l11—10—03—2007 10 44 2,770,674 663 51,486 1

Metro 1—94 14—05 SC Summer 10/6/2005 rigid—M—I94—CS82022—10—06-2005 10 37 2,104,643 340 26,41 1 J

 

 

 

145

 

 

 

Table B.2 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Location Roadbed FWD File Information Concrete

type .Slab Number Slab (EC) Roadbed Roadbed MR

Region Road Cluster- USCS Season Date I File title th1c1<ness OfteSts K (p01) (ps1)
area (m)

Metro 194 1405 SC Summer 1 10/13/2005 1rigid—M-I94—CS82022—10—13-2005 1 10 1 38 1 2,104,704 1 327 1 25,381 1
Metro 1—94 1405 SC Summer 1 10/26/2005 1rigid—M—I94-C882022-10-26—2005 1 10 1 49 1 2,226,098 1 320 1 24,813 j
Metro 194 1405 SC Summer 10/31/2005 1rigid—M—I94-C882022—10—31—2005 10 1 34 1 2,289,527 1 354 1 27,468
Metro 194 1405 SC Summer 9/30/2005 1rigid—M—I94—CS82022—09—302005 10 64 1 2,240,000 1 303 1 23,523 1
Metro 194 1405 SC Summer 11/1/2005 rigid—M-I94-CS82022—11-01—2005 10 79 1 1,980,028 1 258 1 20,003 7
Superior 1-75 0305 SC Summer 6/13/2000 rigid-Su—I75-CS49025-O6-13-2000 9 63 1 1,751,835 1 278 1 21,555 7
Superior 1—75 0305 SC Summer 6/2/2000 rigid—Su—I75-CS49025—06-02—2000 9 40 1,115,443 1 240 1 18,646 7
University L75 1403 SC Summer 10/6/2006 rigid-U—I75—CSS8152-10—06-2006 10 21 1,085,465 1 228 1 17,695 j
University 1-75 1401 SC Summer 12/4/2007 rigid-U—I75-CS58151—12-04-2007 9.3 83 4,002,494 1 297 1 23,071 7
University 1—69 10—08 SC Summer 6/25/2001 rigid—U—I69—CS19043—06—25-2001 1 9 14 1,163,467 1 217 1 16,805 7
University 1—69 10—08 SC Summer 5/14/2002 rigid~U—169—CS19043-05—14—2002 1 9 1 98 1,895,200 1 326 1 25,285 W
University 1—69 10-08 SC Summer 9/18/1998 rigid—U—I69—CSl9042—09-18—1999 1 9 1 10 1 1,687,833 1 339 1 26,277 1
University 1—75 1401 SC 7 3/31/2008 rigid—U—175—Css8151—03—31—2008 1 10 1 57 1 4,346,544 1 175 1 13,580 1
Metro 194 1405 SC Summer 9/16/2008 rigid—M~I94—CS82022—O9—16—2008 12.25 1 78 1 2,982,552 1 310 1 24,056 1
Metro 194 14-06 SC Summer 9/16/2008 1rigid—M-I94-CS82022-O9-16-2008—(2) 12.5 66 1 3,536,866 1 373 1 28,945j
Metro 1—75 14—06 SC Summer 1 9/16/2008 1rigid—M—I75—CS82194—09—16—2008 12 62 1 3,246,240 1 300 1 23,300j
Metro M-14 13—08 CL Summer 1 11/29/2006 1rigid-M—M14—CS82102—11-29-2006 10 66 1 4,335,070 335 1 25,963 7
Metro 1—69 1511: CL Summer 1 7/2/1997 lrigid-M-I69-CS77023—07—02—1997 9 18 2,283,001 233 1 18,1077
Metro 1-69 1503 CL ? 1 4/2/2008 1rigid—M-I69—CS77024—04-02-2008 10 39 1 2,442,439 118 1 9,181 1

 

 

 

146

 

 

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