The Virginia Smart Road - The Impact of PavementInstrumentationon

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The Virginia Smart Road: The Impact of Pavement

Instrumentation on Understanding Pavement Performance

Imad L. Al-Qadi1, Amara Loulizi2, Mostafa Elseifi3, and Samer Lahouar4

Abstract

This paper presents the description, calibration procedures,

installation, and performance of the instrumentation used at the Virginia

Smart Road to measure flexible pavement response to loading. Also

presented are the measured horizontal transverse and longitudinal strains

induced in the hot-mix asphalt (HMA) during compaction with a steel

drum compactor both with and without vibrations. In addition, this paper

presents the data collected and used to determine the vertical

compressive stress pulse induced by a moving truck at different locations

beneath the pavement surface. These data were also used to determine

the effects of temperature, speed, and tire inflation pressure on the

measured vertical compressive stress and measured horizontal transverse

strain, induced by a steering-axle tire of 25.8kN, under the HMA layer.

The data were used make a comparison between measured pavement

responses to truck loading with those calculated using linear elastic

theory. It was found that HMA is subjected to very high horizontalstrains during compactionespecially when vibration is used. It was

also found that a haversine equation well represents the measured

normalized vertical compressive stress pulse for a moving vehicle.

Haversine duration times varied from 0.02s for a vehicle speed of

70km/h at a depth of 40mm to 1.0s for a vehicle speed of 10km/h at a

depth of 597mm. As expected, temperature was found to significantly

affect the measured vertical compressive stress and measured horizontal

transverse strain under the HMA layer. Although speed was found not to

affect the magnitude of the measured vertical compressive stress, it was

found to affect the loading time. On the other hand, speed was found to

significantly affect the measured horizontal transverse strain under the

HMA layer. Variation in tire inflation pressure from 552kPa to 724kPa

was found not to affect the measured vertical compressive stress and the

measured horizontal transverse strain at the bottom of the HMA layer. A

comparison between the measured responses and those calculated using a

finite element model that uses linear elastic theory indicated that the

elastic theory overestimates pavement responses at low temperatures butsignificantly underestimates these responses at high temperatures. An

1The Charles E. Via, Jr. Professor of Civil and Environmental Engineering, 2Research Scientist, 3,

4Senior Research Associate, Virginia Tech Transportation Institute

The oral presentation was made by Professor Al-Qadi


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improved prediction of pavement responses was achieved by modifying

the bonding conditions at the interfaces, and by modeling HMA as a

viscoelastic material.

Key Words:Hot Mix Asphalt, Pavement Instrumentation, LongitudinalStrains

Introduction

Pavement instrumentation has recently become an important tool to

monitor in-situ pavement material performance and quantitatively

measure pavement-system response to truck and environmental loading

(1,2,3,4,5). Parameters that need to be measured in the field include

strains, stresses, deflections, moisture, and temperature. In-situ

measurements of these parameters allow for the development of accurate

pavement response models, which leads to better mechanistic pavement

design approaches. Measuring pavement response to loading is feasible

given the recent development in instrumentation technology and the

experience gained by many researchers in installing such instruments in

real pavement structures.

In 1998, the Virginia Department of Transportation began the

construction of a new test road, the Virginia Smart Road, to be an

adaptable facility for transportation research and evaluation.Construction of the 3.2km Test Facility ended in November 1999. The

pavement test road includes flexible-pavement test sections, a

continuously reinforced rigid pavement, and a jointed plain rigid

pavement. The flexible-pavement portion of the Virginia Smart Road

includes 12 sections, as shown in Table 1. Each section is approximately

100-m-long. The first seven sections are located on a fill, while the

remaining five sections are located in a cut. Seven different wearing-

surface mixes were used: five different SuperpaveTM

mixtures, an open-

graded friction course (OGFC), and a Stone Matrix Asphalt (SMA). A

HMA base with a maximum nominal aggregate size of 25mm (BM-25.0)

was used in all sections, with different thicknesses varying from 100 to

225mm. An open-graded drainage layer (OGDL) was incorporated in

nine sections at a thickness of 75mm. This drainage layer was stabilized

with asphalt cement in seven sections and with Portland cement in two

sections (K and L). A Portland-cement-treated aggregate (CTA) base

was used at a thickness of 150mm in ten sections. An unbound

aggregate subbase layer was placed above the subgrade in all sections,with thicknesses varying from 75 to 175mm. Different types of

geosynthetics and reinforcing steel nettings were also incorporated in

some sections.

All 12 sections are closely monitored through a complex array of

sensors located beneath the roadway. All instruments, which include

Al- Qadi, Loulizi, Elseifi, Lahouar


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different types of strain gauges, pressure cells, thermocouples, time-

domain reflectometry (TDR) probes, and resistivity probes, were

installed during construction of the road. Description of these elements,

calibration procedures, installation procedures, performance issues, and

pavement response to loading are discussed in this paper.

Table 1. Virginia Smart Road 12 Flexible-Pavement Designs

HMA

Sec. WS

(mm)

BM-25.0

(mm)

SM-9.5A

(mm)

OGDL

(mm)

CTA

(mm)

Unbound

Aggregate

(mm)

A 38 150 - 75^ 150 175

B 38 150 - 75^ 150 175/ GT

C 38 150 - 75^ 150 175/ GT

D 38 150 - 75^ 150 175/ GT

E 38 225 - - 150 75/ GT

F 38 150 - - 150 150

G 38 100 50 - 150 150/ GT

H 38 100 50 75^ 150 75

I 38* 100/RM 50 75^ 150 75

J 38 225 - 75^/MB - 150

K 38 225/SR - 75+ - 150

L 38 150/RM - 75+ 150 75

* High laboratory compaction ^ Asphalt treated + Portland cement

treated

WS: Wearing surface; SR: Stress Relief Geosynthetic; GT: Woven

Geotextile/Separator; RM: Reinforcing Steel Nettings; MB: Moisture

Barrier

Instrument Description, Calibration, Installation, and Performance

A brief description of the instruments is presented below. Also

presented is a description of the data-acquisition system used and the

developed software used to acquire, manage, and analyze the data. All

instruments were embedded in the pavement sections during

construction. Environmental instruments were installed in the centerline

of the two-lane road, while load-associated instruments were installed inthe wheel path (0.5, 1, and 1.5m from the shoulder) to account for traffic

wander and for replications.

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The RST pressure cells were selected to measure the vertical

compressive stress under all the layers of the pavement sections in the

Virginia Smart Road. A cell consists of two circular steel plates welded

together around their rims to create a cell approximately 150mm or225mm in diameter and 12.5-mm-thick. The space between the plates is

liquid-filled. A steel tube connects the liquid to an electrical pressure

transducer. The transducer consists of two basic elements: one

mechanical and the other electrical. The mechanical, or force-summing

element, converts the applied pressure into a deflection or displacement

that is proportional to the pressure. The mechanical displacement is

transmitted to the strain-sensing element, thus changing the electrical

resistance of the sensing element. The strain gauge in the transducer isbonded to a diaphragm that flexes with pressure. A pair of gauges (one

on each side) is mounted at the center of the diaphragm, and two

mounted in the comparatively unstressed area at the edge of the

diaphragm. The unstressed gauges are known as dummy gauges and are

included in the bridge circuit to provide automatic temperature

compensation. Two different sizes of pressure cells were selected. The

pressure cells were placed in the upper layers of the pavement structure

(i.e., HMA layers have a diameter of 150mm and can measure up to

690kPa). They have been specially designed to withstand hightemperatures during the HMA laydown. The wires used are also for

direct burial and can withstand a temperature up to 200C. The pressure

cells that were placed in the base layers and subgrade have a 225mm

diameter and can measure up to 414kPa.

Calibration curves were developed by the manufacturer to convert

the measured voltage into pressure. The calibration performed by the

manufacturer consisted of placing the cell between two rigid plates,

which have inflatable rubber membranes. The pressure in thesemembranes was gradually increased and held constant for a specific time

before the voltage was measured. This process was repeated until the

full range of the pressure cell was covered. To evaluate this procedure,

the testing of some pressure cells in a Gyratory Compactor (GC) and in

an Instron machine was conducted at Virginia Tech. The pressure cells

were placed in the Gyratory compactor, a static load was applied, and the

output voltage was measured. This process was repeated at different

pressure levels to obtain the curve of voltage versus pressure. The

difference between the calibration curves obtained with this procedureand that used by the manufacturer were found at low pressure values. At

high pressure values, there were no differences. The difference at low

pressure values was attributed to the edge effect and contact areas

between the GC puck and the pressure cell.

Pressure Cells



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that the relationship between the pressure cell output voltage and the

applied pressure is linear and independent of the loading rate. The

calibrations by the manufacturer were deemed acceptable and were usedfor the field-embedded pressure cells. Pressure cells were installed at

many locations in different layers of the Virginia Smart Road pavement.

For the cells placed in the subgrade and the unbound aggregate subbase

layer, the following steps were carried out:

The subgrade was dug using a small shovel to allow the

instrument in the subgrade to be placed at 25mm below the

interface. A circular hole was excavated at the proposed location

of the sensor. The diameter of the excavation was roughly the

same diameter as a cell load-sensing element. A trench

approximately 75mm wide by 381mm long and 127mm deep

was excavated to accommodate the transducer housing.

Trenches for the wires were dug to the location of the sensor.

They were then filled with a thin layer of sand.

Any particles greater than 6mm in diameter were removed from

the bottom of the hole. A smooth surface at the bottom of the

excavated area was prepared by tamping the soils with a tamper.

A thin layer of sand was placed at the bottom of the preparedhole. The sand was again smoothed and tamped with a tamper.

The cell was placed with the sensitive surface of the cell facing

downward. Good contact between the cell face and the sand

layer was ensured. Good contact between the transducer housing

and the soil was also established. The leveling was checked by

placing a small bubble level in the center of the cell.

Subgrade and subbase materials that were removed prior to

installation were placed back into the hole and were compactedusing a 200mm square steel-plate tamper.

The wires were placed in the trench, which were then backfilled.

For the Pressure cells placed on top of the CTA layer and on top of

the OGDL layer, a geosynthetic layer was used to protect the sensitive

surface of the pressure cell. For HMA layers, the layer underneath the

pressure cell was dug and a thin layer of a mixture of PG 64-22 binder

and sand was placed to protect the sensitive side of the pressure cell and

level the pressure cell with the surface of the existing layer. The pressurecell transducer was buried approximately 50mm deeper than the circular

plate. All pressure cells were checked for response after installation.

Figure 1a, b, and c show pressure cells installed in the subgrade, on top

of cement treated OGDL, and under the HMA wearing surface,

respectively.

The pressure cells were then tested using an Instron servo-hydraulic

machine and were evaluated at different loading rates. It was concluded

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A pressure cell was defined as failing if the sensor gave a constant

out-of-range reading or if its response became too active even though it

was not triggered by any load.

(a) (b) (c)

Figure 1. Installed pressure cells: (a) subgrade (b) top of OGDL (c)under wearing surface

To study the performance of the pressure cells, their failure

percentage was monitored during construction, after one year of service,

after two years of service, and after three years of service. During

construction, only six percent of the pressure cells failed; after one year

of service, the failure percentage increased to 28 percent; then to 41

percent after two years; and finally, 45 percent after three years. Figure2 shows the failure percentage of the pressure cells by section. There

was no clear indication whether the section affected the performance of

the pressure cells. After three years of service, Sections C and I have the

highest failure percentage, while Section H has the lowest failure

percentage during the same three-year period. No pressure cells failed

during the construction of the last five sections, except for one pressure

cell in Section K.



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0

10

20

30

40

50

6070

80

90

100

A B C D E F G H I J K LSection #

%Failure

During Construction

1 year

2 years

3 years

Figure 2. Failure percentage of the pressure cells by section

HMA Strain GaugesThe Dynatest PAST-II-AC strain gauge is an H shaped precision

transducer, specifically manufactured for strain measurements in HMA.

The strain gauge is completely embedded in a strip of glass-fiberreinforced epoxy, a material with a relatively low stiffness and a high

flexibility and strength. Each end of the epoxy strip is securely fastened

to a stainless steel anchor to ensure proper mechanical coupling to the

HMA material after installation. The PAST transducer has a resistance

of 120 and a gauge factor of two.

To convert from the measured voltage reading, Vout, to strain values

Equation 1 is used:

in

out

VGFxV= (1)

where Vinis equal to 10V.

To check Equation 1, a caliper was designed and manufactured at

Virginia Tech. The caliper is capable of applying a uniformly static or

dynamic tension/compression force to the gauge by means of a screw

shaft that moves in both directions without torsioning or bending the

gauge. A sensitive micrometer head is connected to the system to

measure the exact amount of applied displacement to the gauge. Testingconsisted of tensioning and/or compressing the tested strain gauge,

measuring the mechanically induced strain and, comparing it with the

strain obtained with Equation 1. Readings from the caliper were in goodagreement with those obtained using Equation 1; therefore, this equation

was used for all field-embedded strain gauges.

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The strain gauges were installed in the field, Figure 3, using the

following steps:

A small piece of geosynthetic was placed on the finished OGDL

layer. The geosynthetic was cut to the smallest size possible,

which was done to protect the sensor from any sharp aggregates.

A thin layer of bitumen primer was applied to the area where the

transducer was to be placed. It was then left to cure.

A thin layer of 3-4mm sand/binder mix was applied on the cured

binder primer. The anchor bars of the transducer were pressed

by hand into the sand/binder mix until contact between the strain

gauge bar and the sand binder mix was established. Again, it

was left to cure.

The wires were wrapped with geosynthetic and nailed to the

OGDL layer.

Figure 3. HMA strain-gauge installation under HMA layer on top of

OGDL

Hot-mix asphalt was taken from the paver. Large size aggregate

were removed, then a 20 to 30-mm-thick layer was placed on topof the transducer to cover it.

The material was compacted first by applying a static pressure

and a steel plate on the HMA. The compaction was completed using a solid hand roller. The

HMA was rolled in the direction of the anchor bars.

The HMA layer was placed and compacted using regular

construction practices

For the strain gauges located at the bottom of the wearing surface,

the following steps were followed:

A 25-mm-deep hole was dug in the HMA base layer. The

bottom of the hole was smoothened by a concrete grinder.



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A thin layer of binder primer was applied to the area where the

transducer was to be placed. It was then left to cure. A thinlayer of sand/binder mix was applied on the cured binder primer.

The anchor bars of the transducer were pressed by hand into a

sand/binder mix, until contact between the strain gauge bar and

the sand/binder mix is established. Again, it was left to cure.

The wires were wrapped with geosynthetic and nailed to the

finished HMA base layer.

Hot-mix asphalt was taken from the paver. Large size aggregate

were removed, then a 20 to 30-mm-thick layer was placed on topof the transducer to cover it. The material was compacted first

by applying a static pressure and a steel plate on the HMA. The

compaction was completed using a solid hand roller. The HMA

was rolled in the direction of the anchor bars.

Similar to the pressure cells, failure in the HMA strain gauges was

defined when the sensor start to give a constant out-of-range reading or

when its response becomes too noisy all the time even though it is not

triggered by any load. During construction, only 6 percent of the HMAstrain gauges failed. After one year of service the failure percentage of

the HMA strain gauges increased to 26 percent, then to 62 percent after

two years, and finally the failure percentage reached 71 percent after

three years. Figure 4 shows the failure percentage of the HMA strain

gauges by section. There was no clear indication whether the section

affected the performance of the strain gauges. Section I has the lowest

failure percentage after the three year period. It is to be noted that there

was no failure of the HMA strain gauges during construction except for afew in sections B and K.

Temperature SensorsT-type thermocouples were used to measure the temperature in the

pavement sections of the Virginia Smart Road. The thermocouple

consists of a twisted-stranded-shielded soldered pair of wire (constantan

and copper). After the wire pair was twisted and soldered, the exposed

end was surrounded by 6.4mm inside-diameter copper tubing. The

tubing was then attached to the cable insulation by heat shrinkableTeflon tubing, which was done to insulate the tubing from the exposed

wire pair and to provide a reservoir for epoxy. Epoxy was used to

surround the thermocouple and to serve as a barrier to environmental

effects.

A small piece of geosynthetic was placed in the hole. The

geosynthetic was cut to the smallest possible size to protect the

sensor from sharp aggregates.

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0

10

20

30

40

50

60

70

80

90

100

A B C D E F G H I J K LSection #

%Failure

During Construction

1 year

2 years

3 years

Figure 4. Failure percentage of the HMA strain gauges by section

After fabrication, the response from the thermocouples was checked

at two reference temperatures: Ice-water and boiling water. The

response from each thermocouple was recorded and compared to a

reading from a calibrated thermometer. From this procedure, it was

determined that the thermocouples yielded results that were withinoperational ranges (the largest difference between measured and actual

temperature was 2oC).

Prior to installation, all thermocouples were wrapped inside a sheet

of geosynthetic material and were then placed in the desired location

before pavement material was placed on top of them, Figure 5.

All thermocouples performed well, as only 2 percent were damaged

during construction and 5 percent were damaged after one year of

service. After the first year, no more thermocouples were damaged.

Resistivity probes were used to measure frost penetration.

Resistivity probes rely on the measurement of electrical resistance

between the conductors mounted along a cylindrical probe to determine

where the soil is frozen and where it is thawed. This concept is based on

the wide difference between the volume resistivity of frozen soil (from

500,000 up to several million ohms) and thawed soil (normally 20,000 to

50,000 ohms). Frost penetration is determined by making sequential

resistance measurements between adjacent pairs of electrodes down the

resistivity probe and documenting at what depth the resistance goes froma high to a low value.

Resistivity probes are made from PVC rods. The diameter of the rod

used in this study is 25mm, but it can be as small as 6.35mm. The bare

copper rings, spaced at 25mm, on the probe must be in actual electrical

contact with the soil particles over their entire surface area to insure that



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a representative resistivity value is obtained. A probe length of 600mm

was selected for use at the Virginia Smart Road. The probes were

flushed with the subbase layer.

An ERB-20 interface is connected between the resistivity probe and

the Campbell Scientific CR10X Data Logger to apply a sine wave signalto successive coil pairs of the resistivity probe. No failures in the

resistivity probes since construction.

Figure 5. Installation of thermocouples

Time Domain Reflectometry Probes

One method for continually measuring the moisture content of

pavement systems nondestructively is time-domain reflectometry (TDR).

Time-domain reflectometer employs an electromagnetic wave that is

transmitted along a set of metallic conducting rods (or waveguides). The

velocity of the pulse is influenced by the dielectric constant () of thematerial surrounding the waveguides. The dielectric constant is a ratio of

the permittivity of the material to the permittivity of a vacuum (0=

8.8542 x 10-12

F/m) and is dimensionless. Developed to measure faults in

communication cables and transmission lines by applying pulses to a

cable and collecting the reflected waveform, TDR has been adapted by

agricultural researchers to measure the moisture content of soils during

irrigation.

Two types of TDR soil moisture measurement instruments were usedin this study: CS610 and CS615. The CS610 is comprised of three

parallel conducting rods that are 300mm in length. A distance of 22mm

separates the rods, and the rods are held rigidly in place on one end by an

epoxy head that is 111- by 63- by 20-mm in size. Output using the

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CS610 TDR is usually displayed as a voltage or reflection coefficient

versus time. The travel time of the reflected signal is computed and, in

conjunction with a velocity of propagation constant, the distance to the

discontinuity can be determined. When the TDR probe is inserted into

soil, the travel time of the applied pulse along the probe length isdependent upon the soil water content. Soil moisture content possesses

an inverse relationship with the velocity of propagation; therefore, the

relationship is directly related to time.

The CS615 TDR probe is comprised of two parallel conducting rods

that are 300 mm in length. A distance of 32mm separates the rods. The

rods are held rigidly in place on one end by an epoxy head that is 110- by

63- by 20-mm in size. The epoxy head contains electronic components

configured as a bistable multivibrator. Changes in soil water content

affect the transit time of the electromagnetic wave along the 300mm

rods. The sum of the rod transit time and the inherent delay of the

electronic components determine the oscillation frequency of the

multivibrator. A scaling circuit is used to scale the measured frequency

to a value compatible with data acquisition devices. The final probe

output is a square wave with a frequency that varies with water content

and has an approximate range of 700 to 1500Hz.

Calibration measurements were performed on the unbound base

layer material. Measurements were performed for a volumetric moisturecontent ranging approximately from 1 to 20 percent and were compared

with values obtained from oven drying samples taken from near the

probes. A wooden calibration box (0.84- by 0.85- by 0.45-m) was

constructed using none metallic fasteners and was used in the calibration

process. The calibration box allows four probes, as shown in Figure 6, to

be tested simultaneously without adversely affecting the measurements.

To evenly mix water with soil, a 0.4m3concrete mixer was used to mix

approximately 40kg of soil per batch. Soil was placed in the calibration

box in three layers. Each layer, approximately 150mm thick, was placed

and compacted before the following layer was placed. The probes were

placed within the second layer, separated by at least 150mm before this

layer was compacted. After testing, a sample of soil (approximately 3kg)

was removed from the middle layer and placed in an oven at 110oC to

determine the gravimetric moisture content.

An equation was developed for each type of TDR that relates the

21B volumetric moisture content with the measured property (effective

length, le, for TDR CS610 and period of oscillation, t, for TDR CS615)based on the calibration testing (6).

The probes were handled carefully during installation so that the

metallic waveguides would not be bent. The following steps were

followed during installation:



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A hole that allows the placement of the TDR horizontally was

prepared.

If large aggregates were present, sand was placed under the TDR

head.

After placing the TDR, the soil was compacted very carefullyaround and over the probe. The response of the probe waschecked.

All cables were protected by nonwoven geotextile all the way

until it reaches the conduit.

Figure 6. TDR calibration box

All TDR probes performed well, as only 2 percent were damaged

during construction, 5 percent were damaged after one year of service,

10 percent were damaged after two years of service, and 12 percent were

damaged after three years of service.

Vibrating Wire Strain Gauges

The Geokon model VCE-4200 Vibrating Wire Strain Gauge wasselected to be installed in the subgrade and in the cement-stabilized

aggregate layers of the pavement sections. This model is designed

primarily for long-term strain measurements in mass concrete. It is

152mm long and is widely used for strain measurements in different civil

engineering applications. It is extra rugged to resist bending and has

relatively large flanges to provide sufficient engagement area. The

advantage of the vibrating wire strain gauge over more conventional

electrical resistance (or semi-conductor) types lies mainly in the use of

frequency, rather than voltage, as the output signal from the strain gauge.Frequencies may be transmitted over long cable lengths without

appreciable degradation caused by variations in cable resistance, contact

resistance, or leakage to ground. Vibrating wire gauges also have

excellent long-term zero stability.

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The principle of vibrating wire is that a length of steel wire is

tensioned between two end blocks that are firmly in contact with the soil.

Deformations in the soil would cause the two end blocks to move relative

to one another, altering the tension in the steel wire. This change in

tension is measured as a change in the resonant frequency of thevibration of the wire. Excitation and readout of the gauge frequency is

accomplished by electromagnetic coils that are located close to the wire.

Calibration of the vibrating wire strain gauges was performed using

the same procedure performed for calibrating the HMA strain gauges.

Trenches for the wire were dug to location of the sensor (Figure 7).

They were then filled with a thin layer of sand. For each gauge, the

smallest possible hole was dug (just enough to fit the sensor) in the

finished subgrade layer. During excavation, extra care was taken to

minimize the disturbance of the soil and keep the size of the hole to a

minimum. The gauge was placed on a very thin layer of sand, then back-

filled with the excavated material in small layers and was hand compact

carefully. The wire was run through the trenches and covered with a

layer of geosynthetic, previously cut to the right size.

Figure 7. Installation of vibrating wire strain gauges

The vibrating wire strain gauges had a mediocre performance, as 11

percent were damaged during construction, 16 percent were damaged

after one year of service, 35 percent were damaged after two years of

service, and 61 percent were damaged after three years of service.

Data Acquisition SystemThe data acquisition system used in the Virginia Smart Road is

shown in Figure 8. It consists of two main Analog-to-Digital units

(DaqBook 200 and WaveBook 512). The DaqBook 200 is used to

acquire static data (e.g., temperature, moisture, frost depth), while the



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WaveBook 200 is used to acquire dynamic data induced by moving truck

loads (e.g., pressure and strain)

The DaqBook 200 module, from IOtech Inc., is a standalone device

that connects to a PC through its parallel port and can transfer data

bidirectionally at a speed up to 800kbytes/s for an enhanced parallel port(EPP). Data is stored in the PCs memory or hard disk rather than in the

DaqBook. In order to make the transducer output signal compatible with

the Analog to Digital Converter (ADC) input signal, signal-conditioning

cards are used. These cards were provided by the same manufacturer,

thus they are fully compatible with the DaqBook 200.

The signal-conditioning cards, referred to as DBK cards, are daisy-

chained in a special expansion chassis that is connected to the DaqBook

through a single cable that provides both the analog inputs and the

control signals. To guarantee a correct communication with the

DaqBook, each DBK card mounted in the daisy chain has its unique

channel number (fixed using a jumper on the card).

Figure 8. Data acquisition system

The WaveBook 512, also a product of IOtech Inc., is a Digital Signal

Processing-based, 12-bit, one million samples per second data

acquisition system. It connects to a PC via an ISA plug-in interface card

(WBK21) containing an enhanced parallel port (EPP) for a bi-directional

data transfer speed up to 2000 kbytes/s.

In order to make the transducer output signal compatible with the

ADC input signal, signal-conditioning modules are used. These modules

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were provided by the same manufacturer, IOtech Inc., thus they are fully

compatible with the WaveBook 512.

The signal-conditioning modules, referred to as WBK modules, are

daisy-chained using two different sets of cables: expansion control cables

used to carry the control messages and coax cables with BNC connectorsused to carry the analog signal from the input channel to the ADC. The

order in which the WBK modules appear in the daisy chain fixes their

respective channel numbers. The main unit (i.e., the WaveBook 512) is

always number 0. Two WBK types were used: WBK 10 for pressure

measurements and WBK 16 for strain measurements.

To further protect the whole system, spike protection cards were

inserted between the transducers and signal conditioning modules. These

cards also provide the proper power supply to the transducers.

Developed SoftwareIn order to collect the data, organize it, display it for analysis, and

store it in a database, several software were developed. The first, called

SmartAcq, acquires the data with the desired settings. The second, called

Smart Organizer, manages and organizes the collected raw data. The

third, called Smart Wave, displays and processes the raw data. Two

databases were also developed using Microsoft Access to store the

temperature data and the dynamic data (from the truck test) in order toeasily retrieve any needed information.

SmartAcq: In order to provide more customized control on the data

acquisition proceduresuch as collecting the static data at specific

intervals, collecting the dynamic data only when there is a traffic load,

applying the different control signals for a proper operation of the

transducers, and specifying the names assigned to the different output

filesa special data acquisition software, SmartAcq, was developed

along with other utilities to manipulate the collected data. SmartAcq is a

Windows-based Single Document Interface (SDI) program that provides

a user interface to configure and operate the whole data acquisition

system (DaqBook and WaveBook) at the same time. SmartAcq was

created with Microsoft Visual C++ 5.0; the control of the data acquisition

system was done through a library provided by the manufacturer, which

communicates directly with the device drivers.

Smart Organizer: Considering the large number of instruments used

at the Virginia Smart Road, a large amount of data is collected and stored

every day. Therefore, the need of managing the data is required tosimplify data analysis. For that purpose, a software, Smart Organizer,

was developed. Using the Smart Organizer Software, all raw files are

divided into several files according to the section number, the date of

data collection, and the collected data type (temperature, moisture,



17/39

dynamic data, etc). All these files are automatically stored in specially

named folders.

SmartWave: Dynamic data consists of strain and pressure

measurements collected during controlled truck testing. During the test,

the data is saved in the form of waves representing strain or pressureversus time. The collected waves are typically sampled at a frequency of

500Hz and a duration of two seconds starting 0.2s before the trigger

point. Therefore, for each instrument triggered during the test, a 1000-

sample wave is stored in a dynamic data binary file. At an early stage in

the project, these waves were visualized using a spreadsheet application.

This solution was found to be cumbersome because of the large number

of waves collected during each test. For that reason, a program called

SmartWave was developed specifically to process these binary files.

SmartWave is a Windows based Multiple Document Interface (MDI)

application that allows visualization and analysis of the dynamic data

stored in the binary files. SmartWave provides a set of commands to

easily navigate among the different waves stored in the binary file along

with some commands for customizing data display and for data

processing. The program also provides general information about the

test in conjunction with information specific to the displayed wave.

There are mainly two purposes for data processing: enhance the

quality of the collected data and automatically extract interesting featuresfrom it. Data enhancement consists mainly of filtering the wave to

remove any unwanted noise, which becomes significant when the

instrument response is relatively low.

One of the interesting features that could be extracted from the

instrument responses is the extremum value corresponding to each axle.

The extremum could be a maximum for pressure cells and either a

maximum (corresponding to compression) or a minimum (corresponding

to tension) for strain gauges. Automatic extraction of these extremum

points was developed in the software specifically for a six-axle truck.

The extremum extraction procedure could be customized to extract data

corresponding only to a range of waves. Moreover, the extracted peaks

could correspond to the single, tandem, or tridem axles or in any

combination. The output of the extraction procedure is saved into a file

that could be either in a table format, easily incorporated in reports, or in

a database format to be imported to the global database developed to

store the instrument responses.

Databases: The collected data is organized into two interconnecteddatabases: Loading database and Environmental database. The loading

database mainly contains the peak responses (maxima for pressure cells

and minima/maxima for strain gauges) collected from every triggered

instrument in the pavement and for each axle in the truck and trailer.

Each data record has a timestamp corresponding to the trigger time of the

Virginia Smart Road


18/39

instrument in addition to the instantaneous speed of the truck.

Furthermore, this database contains static information about the test

characteristics, sections, layers and instruments to help the user in

extracting the data.

The environmental database contains temperature and moisture datacollected for each instrument at regular time intervals (15 min for

temperature and one hour for moisture). For this case also, each record

will contain a timestamp corresponding to the data collection time. This

database shares the information about sections, layers, and instruments

with the loading database.

A set of simple queries was developed to let the user extract data

based on a given search criteria, such as instrument type, test properties,

sections, layers, etc. Besides the detailed output of the queries, the user

is given the option to extract grouped data. For the loading database,

responses from repeated runs can be grouped together to yield a single

minimum or maximum point per test, layer, and axle. For the

environmental database, the user can group the data to get the minimum,

maximum, or average point per layer for time intervals much larger than

the acquisition intervals. In addition, a query will provide the

temperature/moisture profile for a given time.

These two databases were developed using Microsoft Access. Since

the data search using this software needs prior knowledge of thissoftware, a user interface was built, using visual C++, to facilitate data

search criteria input and therefore data extraction.

Measured Horizontal Transverse Strain in the

HMA Layer during Construction

During the construction of the 38-mm wearing surface of Section B,

the strain gauges placed under this layer were activated to measure how

much horizontal strain the material undergoes during compaction using a

steel drum compactor. The compactor operator was not aware that data

was being collected and was performing the compaction according to the

specified pattern. Data was collected during the whole compaction

process and thousands of waveforms were collected from the strain

gauges. SmartWave was then used to analyze the data and to extract the

maximum measured horizontal transverse strain and the maximum

measured horizontal longitudinal strain. Figure 9 shows the acquired

waveform for the maximum measured horizontal transverse strain. Inthis Figure, the strain on the vertical axis is in micro-strain ( m/m),

while the time on the horizontal axis in seconds (sec). The measured

horizontal transverse strain is in tension. After passage of the compactor,

the strain slowly decreased but did not reach zero. The measured

maximum horizontal transverse strain was 1,090 m/m. After the



19/39

compactor passed, this strain decreased to 37 m/m. In some of the

compaction passes, the compactor operator used vibrations. Figure 10

shows the acquired waveform for the maximum measured horizontal

transverse strain when vibrations were used. It is interesting to note that

the frequency of vibration could be measured for the acquired waveformand it was determined to be 40Hz (2,400 vibrations per minute). The

shape of the horizontal transverse strain curve is the same as in the case

when no vibration was used. However, the maximum tensile strain when

vibration was used was 1,630 m/m, which is around 1.5 times the

measured strain when no vibration was used. When vibration was used,

the strain decreased to 73 m/m, which is around two times the strain

measured for the case when no vibration was used.

0

200

400600

800

1000

1200

1400

1600

1800

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Time (sec)

Strain(m/m)

Figure 9. Measured horizontal transverse strain under the wearing

surface during compaction (no vibration)

Virginia Smart Road


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0

200

400

600

800

1000

1200

1400

1600

1800

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Time (sec)

Strain(m/m)

Figure 10. Measured horizontal transverse strain under the wearing

surface during compaction (with vibration)

Figure 11 shows the acquired waveform for the maximum measured

horizontal longitudinal strain. The measured horizontal longitudinal

strain is compression strain, then it becomes a tensile strain, and finally it

ends as a compression strain. The longitudinal strain returns to its initial

value, which means no permanent deformation has been developed. The

measured maximum horizontal tensile longitudinal strain was

4,356 m/m, which is around 3.9 times more than the measured

horizontal transverse strain. This variance is explained by the fact that

the contact area of the steel drum compactor is almost rectangular in

shape with the smaller dimension in the longitudinal direction, which

means that greater strain is induced in this direction because of

compaction. Figure 12 shows the acquired waveform for the maximummeasured horizontal longitudinal strain when vibration was used. The

measured frequency of vibration from this graph was also 40Hz. The

shape of the horizontal longitudinal strain curve is the same as in the case

when no vibration was used. However, the maximum tensile strain when

vibrations were used was 7,214 m/m, which is around 1.7 times the

measured tensile strain without vibration. The same was found for the

compression part of the longitudinal strain. When no vibration was used,

the maximum compression part was 1,314 m/m, while a maximum

compression strain of 2,246 m/m was measured when vibration wasused.



21/39

-2500

-1500

-500

500

1500

2500

3500

4500

5500

6500

7500

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Time (sec)

Strain(m/m)

Figure 11. Measured horizontal longitudinal strain under the

wearing surface during compaction (no vibration)

These measurements of horizontal strain during the construction of

the wearing surface showed that the HMA is subjected to very high

horizontal strains during construction, especially when vibration is usedin the compaction process. A question emerges as to how these high

strains affect the long-term performance of the pavement. It is

anticipated that these high strains may induce microcracks during the

compaction process, which may grow and propagate during the life of

the pavement. Since vibration was found to induce much higher strains

in the HMA, its use during compaction should be carefully studied to

evaluate its overall effectiveness and benefits to the pavement

performance.

Virginia Smart Road


22/39

-2500

-1500

-500

500

1500

2500

3500

4500

5500

6500

7500

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Time (sec)

Strain(m/m)

Figure 12. Measured horizontal longitudinal strain under the

wearing surface during compaction (with vibration)

Pavement Loading

Once all the pavement sections were constructed, a testingexperimental program was conducted at the Virginia Smart Road with an

overall purpose of quantifying the pavement response to truck loading

under different environmental conditions. The truck used for testing was

an International 8200 Class 887 with an engine power of 350hp at

2,100rpm. Michelin 11R22.5 XZA-1 tires supported the steering axle

and General 11R22.5 tires supported the tandem axle. The trailer had

Goodyear 10.00R15TR tires for its tridem axle wheels. The

experimental program consisted of three different tire inflation pressures

(724kPa, 655kPa, and 552kPa), three different load configurations (L1,L2, and L3), and four different speeds (8km/h, 24km/h, 40km/h, and

72km/h). Concrete barrier walls (Jersey walls) were used to load the

truck. Load L1 used nine barrier walls, Load L2 used four barrier walls,

and for load L3, no barrier walls were used. Each barrier wall weighs

approximately 2,265kg. Speed is measured using a global positioning

system (GPS), with an accuracy of 0.4km/h.

Results and Analysis

This paper presents findings from the measured flexible-pavement

response to truck loading under different environmental conditions as

obtained from Sections A and L of the Virginia Smart Road. These

findings are essential for flexible-pavement analysis and design. The

first part of the Results and Analysis Section shows how the vertical



23/39

compressive stress pulse induced by truck loading varies with truck

speed and depth below the pavement surface. The measured pulse is

important for laboratory testing of HMA as well as for theoretical

modeling. The second part of the Results and Analysis Section deals

with the effects of temperature, speed, and tire inflation pressure on themeasured vertical compressive stress and horizontal transverse strain

under the HMA layer. The last part of the Results and Analysis Section

compares the measured horizontal strain and measured vertical

compressive stress under the HMA layer with those calculated using

finite element (FE) modeling.

Measured Vertical Compressive Stress Pulse versus Depth and SpeedLaboratory measurements of HMA mixes as well as advanced

theoretical modeling of pavements make use of a Haversine or a

sinusoidal type of loading to study the behavior of HMA. This loading

shape and its duration were mainly developed based on research

performed in the 1970s. In 1971, Barksdale used finite element (FE)

modeling and elastic theory to calculate the vertical compressive stress

pulse width as a function of speed and depth (7). He found that the pulse

shape varies from approximately a sinusoidal one at the surface to nearly

a triangular one at depths below approximately the middle of the base.

The pavement geometry was found not to affect the pulse shape andduration. Change of the resilient modulus values of the pavement

materials because of a change in environment was found also not to

affect the pulse shape and duration. With these findings, Barksdale was

able to develop a chart of the vertical sinusoidal and vertical triangular

pulses time as a function of vehicle speed and depth beneath the

pavement surface. These pulse times were empirically corrected for

viscous effects and inertia forces using results from field measurements

at the AASHO Road Test.

Data collected from the Virginia Smart Road allowed the

reinvestigation of this topic. In fact, data from truck tests using a tire

pressure of 724kPa and a front tire weight of 25.8kN performed at four

different target speeds of 8km/h, 24km/h, 40km/h, and 72km/h were

analyzed to measure the pulse duration versus speed at five different

locations underneath the pavement surface: 40mm, 190mm, 267mm,

419mm, and 597mm. Figure 13 and Figure 14 show the measured

compressive stress pulse at 40 mm, 190mm, 267mm, 419mm, and

597mm underneath the pavement surface, at speeds of 8km/h and72km/h, respectively. In these figures, the x-axis represents the time in

seconds, while the y-axis represents the normalized vertical compressive

stress (vertical stress divided by maximum measured vertical stress).

The normalization was performed to be able to compare between the

different tests. Since the tests were performed at different periods during

Virginia Smart Road


24/39

the day, the testing temperature was different, which affects the resilient

modulus of the HMA layer. This change in the modulus produces

different vertical stress values, but it was found that this change does not

affect the shape and duration of the normalized compressive stress pulse

(8). This finding is in agreement with Barksdale findings.The measured pulse shape for all performed tests was not

symmetrical. Before the wheel reaches the location of the pressure cell,

the pulse is flat around zero. As soon as the wheel approaches the

instrument location, the vertical stress increases until it reaches a

maximum when the wheel is right above the pressure cell itself (loading).

When the wheel is moving away from the instrument (unloading), the

shape of the pulse does not follow the exact same path acquired during

the loading phase (asymmetry of the response). The shape of the pulse is

more elongated during the unloading phase due to the viscoelastic nature

of the material. In addition, the vertical compressive stress does not

return to zero after unloading. Some residual vertical stresses occur in

the pavement materials. These residual stresses increased with a

decrease in the speed as shown in the figures.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.80.9

1

-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4Time (sec)

Nor.Vert.Comp.Stress

40mm

190mm

267mm

419mm

597mm

Figure 13. Measured normalized compressive stress pulse at 8km/h



25/39

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1

Time (sec)

Norm.Vert.Comp.Stre

ss

40mm

190mm

267mm419mm

597mm

Figure 14. Measured normalized compressive stress pulse at 72km/h

A haversine equation, Equation 2, was used to represent the normalized

compressive stress pulse, where d is the duration of the pulse.

)d

t

*2(siny(t)

2+

=

(2)

Figure 15 and Figure 16 show the measured normalized compressive

stress pulse and its chosen haversine representation for the 8km/h test at

a depth of 40mm and 597mm below the surface, respectively. From

these figures, it can be seen that Equation 2 is a good approximation of

the normalized compressive stress pulse, especially near the pavement

surface. Haversine load durations at all the speeds were used to develop

power regression equations relating the haversine duration pulse with

speed for each location underneath the pavement surface, Figure 17.Haversine duration times obtained from the developed regression

equations were compared to those suggested by Barksdale in 1971, Table

2. From this table, it is noted that Barksdale duration times are similar to

the ones obtained from the Virginia Smart Road for the 40mm and

190mm deoths. At greater depths, Barksdale duration times are almost

half of those obtained from the Virginia Smart Road.

Effect of Speed and Tire Inflation Pressure on Measured Vertical

Compressive Stress and Measured Horizontal Transverse Strain underthe HMA Layer

Instrument responses from Section A, induced from the steering axle

tire with a load of 25.8kN, were used to study the effect of speed and tireinflation pressure on the measured vertical compressive stress and

measured horizontal transverse strain under the HMA layer.

Virginia Smart Road


26/39

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1

Time (s)

Norm.Vert.Comp.Stre

ss Measured

Haversine

Figure 15. Measured normalized compressive stress pulse and its

haversine representation for the 8km/h test at 40mm

0

0.10.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6

Time (s)

N

orm.Vert.Comp.Stress

Measured

Haversine

Figure 16. Measured normalized compressive stress pulse and its

haversine representation for the 8km/h test at 597mm



27/39

y = 9.426x-0.979

y = 7.306x-0.974

y = 2.558x-0.903

y = 1.896x-0.958

y = 1.663x-1.041

0.01

0.1

1

10

0 10 20 30 40 50 60 70 80Speed (km/h)

HaversineTime(sec)

597mm419mm267mm190mm

40mm

Figure 17. Haversine pulse duration versus speed for different depths

Table 2. Comparison between haversine loading times suggested by

Barksdale with those obtained from the Virginia Smart Road

72km/h 24km/h

Depth (mm) Smart Road Barksdale Smart Road Barksdale

40 0.019 0.023 0.06 0.075

190 0.031 0.032 0.09 0.10

267 0.054 0.038 0.14 0.12

419 0.113 0.055 0.33 0.15

597 0.142 0.075 0.42 0.21

Effect of Speed on Measured Vertical Stress: To study the effect of

speed on the measured stresses under the HMA layer, data from testswith similar load and tire inflation pressure performed at different speeds

were compared.

Data obtained from the tests performed at the same target speed was

correlated with temperature measured under the HMA layer. The

measured vertical stress under the HMA layer was found to increase

exponentially with an increase in the measured temperature. Figure 18

shows the measured data for a tire inflation pressure of 724kPa. From

this figure, it is concluded that speed does not affect the magnitude of the

compressive vertical stress under the HMA layer, which is demonstratedby the developed regression equation for all tested speeds. The high R

2

value (0.92) indicates that the measured vertical compressive stress is

independent of the truck speed. On the other hand, the pulse width ofthisvertical stress increases with a decrease in speed as shown in Figure 17.

Virginia Smart Road


28/39

= 28.3e0.0565T

R2= 0.92

0

20

40

60

80

100

120

140

160

180

200

0 5 10 15 20 25 30 35 40

Temperature (C)

VerticalStress(kPa)

8km/h

24km/h40km/h

72km/h

Figure 18. Measured vertical compressive stress under HMA layer

for all tested speeds

Effect of Speed on Measured Horizontal Transverse Strain: The

procedure discussed for evaluating the effect of speed on the measuredvertical stress was also used to evaluate the effect of speed on the

measured horizontal transverse strain under the HMA layer. Figure 19

shows the variation of the horizontal transverse strain under the BM-25.0

because of the front tire for truck speeds of 8km/h, 24km/h, 40km/h, and

72km/h. As expected, the strain was found to increase exponentially

with an increase in temperature. It was also found that speed does affect

the measured horizontal transverse strain: as speed decreases, the

measured strain significantly increases. Exponential regression

equations were developed for each speed, see Figure 19. When these

equations are used with a temperature of 25oC, the strain measured at

8km/h was found to be 2.7 times greater than that at 72km/h.

Effect of Tire Inflation Pressure on Measured Vertical Stress and

Measured Horizontal Transverse Strain under HMA Layer: To study the

effect of tire inflation pressure on the measured vertical compressive

stress and measured horizontal transverse strain under the HMA layer

because of the front axle, all tests performed at different tire inflation

pressures (724kPa, 665kPa, and 552kPa) were analyzed. It was foundthat tire inflation pressure in the range of 552 to 724kPa did not affect the

measured vertical compressive stresses; neither did it affect the measured

horizontal transverse strain under the HMA layer.



29/39

0

20

40

60

80

100

120

140160

180

200

10 15 20 25 30 35 40

Temperature (C)

Strain(m/m)

8km/h

24km/h40km/h

72km/h

Figure 19. Measured horizontal transverse strain under HMA layer

at different speeds

Comparison between Calculated and Measured Pavement Responses

A 3D finite element (FE) mesh, simulating Section A, was developedto run with ABAQUS version 6.3, Figure 20. The assumptions made in

the presented FE model were intentionally simplified to exactly resemble

the layered elastic theory, which is among the most popular methods for

pavement response prediction. Eight-node, first-order brick element with

reduced integration (C3D8R) was selected for use in this study. In

addition, infinite elements (CIN3D8) were used in all models to simulate

the far-field region in the horizontal directions. CIN3D8 is an 8-node 3D

linear infinite element. All interfaces were modeled as fully bonded.

Using the symmetry in loading and geometry, only half the model was

simulated, which required imposing a boundary on the plane of

symmetry (plane in the longitudinal direction) in the transverse direction.

The contact area of the applied load was modeled using a rectangular

shape with a width to length ratio of 0.82.

Elastic material properties of the different layers were determined

either from FWD testing or from laboratory testing. The resilient moduli

of the different layers, except for the HMA layer, were kept constant and

were not changed as a function of temperature. On the other hand,resilient modulus of the HMA layer was changed with temperature

according to laboratory-determined results at 5oC, 25

oC, and 40

oC.

Virginia Smart Road


30/39

Figure 20. 3D finite element mesh

Figure 21 shows the measured and calculated horizontal transverse

strain under the HMA layer induced by the single load of 25.8kN. It is tobe noted that the graphs of the measured horizontal transverse strains at a

truck speed of 8km/h and 72km/h represent the regression equations

found to best fit the measured data (Figure 19). The calculated

horizontal transverse strain under the HMA layer was found to vary

linearly with temperature under the HMA layer. The calculated

horizontal transverse strain is not a function of the truck speed since the

load is assumed to be stationary. However, the measured horizontal

transverse strain was found to vary significantly with truck speed. From

Figure 21, one can note also that the measured horizontal transversestrain at a truck speed of 8 km/h is smaller than the calculated one using

the elastic layered theory at temperatures below 15oC. Above 15

oC, the

measured strain at a truck speed of 8km/h becomes much higher than the

calculated one. At a truck speed of 72km/h, the measured horizontal

transverse strain is smaller than the calculated one at temperatures below

approximately 28oC, above which the measured strain becomes much

higher. From Figure 21, it is also noted that the calculated horizontal

transverse strain is not as much affected by change in temperature as wasmeasured in the field. In fact the calculated strain approximately

doubled from 0oC to 40

oC. On the other hand, the measured horizontal

strain increased by approximately 117 times from 0oC to 40

oC when

driving at a speed of 72km/h and increased by approximately 35 times

when driving at 8km/h.



31/39

0

50

100

150

200

250

300

0 5 10 15 20 25 30 35 40

Temperature (C)

Strain(m/m)

3D FE

Measured 8km/h

Measured 72km/h

Figure 21. Measured and calculated horizontal transverse strain

under the HMA layer for a single load of 25.8kN

Figure 22 shows the measured and calculated vertical compressive

stress under the HMA layer induced by the single load of 25.8kN.

Again, the graph showing the measured vertical compressive stress

corresponds to the best regression equation that represents the measured

data (Figure 18). It was found that the calculated response varies linearlywith temperature. The calculated vertical compressive stress was found

to be higher than the measured one for temperatures below 35oC, above

which the measured one becomes higher.

Improved Modeling Approach:Based on the results of the presentedFE model, it was clear that to accurately simulate field conditions,

several assumptions made in the modeling process need to be adjusted.

Hence, to improve the accuracy of the theoretical approach in predicting

pavement response, the following modifications were incorporated into

the FE model, which simulates Section L (see Table 1).

While an elastic constitutive model was still assumed for the

granular layers and subgrade, a viscoelastic constitutive model was

selected to simulate the behavior of HMA layers. Characterization of the

viscoelastic properties of HMA was conducted in the laboratory on field

cores. Testing of the HMA surface and base mixes was performed using

indirect creep compliance test. Experimental data was first obtained by

performing creep compliance tests at different temperatures, then shifting

the data to a reference temperature. For the viscoelastic behavior,ABAQUS assumes that a Prony series expansion adequately describes

the material response with respect to time:

=

+=

N

1i

/t

i0 )e-(1DDD(t)i (3)

Virginia Smart Road


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0

50

100

150

200

250

300

0 5 10 15 20 25 30 35 40Temperature (C)

Stress(kPa)

3D FE

Measured

Figure 22. Measured and calculated vertical compressive stress under

the HMA layer for a single load of 25.8 kN

To obtain the material constants in Equation (3), a set of relaxation

times were assumed to cover the range of testing, and the fitting process

was then reduced to find the coefficients of the Prony series through a

linear least squares curve fit. In general, seven to ten Prony series terms

were used to obtain an accurate fit; see Figure 23 for illustration.

The creep compliance was then used to predict the relaxation

modulus, E(t). The interconvension process was based on the

approximation developed by Park and Kim (9). Assuming that both the

creep compliance and the relaxation modulus may be described by apower law model, the relationship between the two material properties is

defined as follows (9):

=

n

nsin)t(D)t(E (4)

where D(t) is the creep compliance at time t; and D i(Prony series

coefficients) and i (relaxation times) are material constants.

where n are positive constants, obtained by fitting a localized power law

model (D(t) = D1tn) to the different regions of behavior, see Figure 24 for

illustration.



33/39

1.0E-12

1.0E-11

1.0E-10

1.0E-09

1.0E-08

1.0E-07

1.0E-04 1.0E-02 1.0E+00 1.0E+02 1.0E+04 1.0E+06 1.0E+08

Reduced Time (sec)

CreepCompliance(1/Pa)

Measured-25

Model-25

Figure 23. Prony series fitting of the measured creep data (surface

mix T = 25C)

y = 2E-10x0.5389

R2= 0.98

0.0E+00

2.0E-11

4.0E-11

6.0E-11

8.0E-11

1.0E-10

1.2E-10

1.4E-10

1.6E-10

1.8E-10

2.0E-10

0.00E+00 2.00E-01 4.00E-01 6.00E-01 8.00E-01 1.00E+00 1.20E+00

Time (sec)

CreepCompliance(1/Pa)

Figure 24. Localized power law model fitted to the creep compliance(surface mix T = 25C)

Virginia Smart Road


34/39

Similarly, a Prony series function was fitted to the relaxation

modulus variation with time. Then, the bulk [K(t)] and shear [G(t)]

moduli variation with time were estimated using the following relations

assuming that Poissons ratio ( ) does not change with time (9):

)21(3

)t(E)t(K

= (5)

)1(2

)t(E)t(G

+= (6)

To accurately simulate the movement of the tire over the loading

area, vertical stress measurements at the Virginia Smart Road at the

bottom of the wearing surface (depth = 38.1mm) were discretized intosmall rectangular shapes in the longitudinal direction. For the simulated

speed (8km/hr), measured vertical stress was considered after first being

normalized with respect to the maximum-recorded value. The

normalized vertical stress was then multiplied by the average tire

pressure expected during movement.

Elastic element foundations were used to simulate the subgrade

support of the pavement structure. These elements, which act as

nonlinear springs to the ground, provide a simple way of including the

stiffness effects of the subgrade without fixation of nodes at the bottom

of the model. A medium level of resistance corresponding to a modulus

of subgrade reaction of 175N/cm3was assumed for the considered

section. All contacts between the layers were assumed to be of a friction

type (Mohr-Coulomb theory), with a friction angle of 45deg.

Results of the developed FE model were compared with actual stress

and strain measurements from truck testing at the Virginia Smart Road.

Pavement responses to vehicular loading were compared at a speed of

8km/hr. Figure 25 compares the measured and calculated transversestrain under the HMA layer for a single load of 25.8kN. Again, the best

regression equation that represents the measured transverse strain for this

section was used. As Figure 25 indicates, the use of a viscoelastic

constitutive model to simulate HMA materials provided a more accurate

rendition of the pavement response at low and intermediate temperatures

(below 20oC). However, some discrepancies were still observed between

the measured and the calculated transverse strain at high temperatures

(above 20oC).



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0

50

100

150

200

250

300

350

400

450

500

5 10 15 20 25 30 35 40

Temperature (C)

Strain(m/m)

3D FE

Measured

Figure 25. Measured and calculated horizontal transverse strain at

the bottom of the BM-25.0

Conclusions and Recommendations

Testing at the Virginia Smart Road allowed verification of several

hypotheses related to flexible-pavement design. The following findings

and recommendations are presented:

Virginia Smart Road

With proper calibration procedures, installation, and good data

management, instrumentation is a feasible tool to measure pavement

response to loading.

Compaction produces high horizontal strains in the HMA, especially

when vibration is used. It was found that a haversine equation well represents the measured

normalized vertical compressive stress pulse for a moving vehicle.

As would be expected, temperature significantly affects measured

vertical compressive stress and measured horizontal transverse strain

under the HMA layer.

Speed significantly affects measured horizontal transverse strain

under the HMA layer. Speed does not affect measured compressive

vertical stress in pavement layers, but it affects the loading pulse

duration.

It appears that tire inflation pressure has little effect on pavement

measured stresses and strains at a depth of 190 mm.

Even though the resilient modulus of HMA varies exponentially with

temperature, the calculated responses using linear elastic theory were


36/39

References


found to vary linearly with temperature. However, measured

responses were found to be better represented as a function of

temperature using exponential regression equations.

The linear elastic theory appears to overestimate pavement responses

at low temperatures, but significantly underestimate these responsesat high temperatures.

An improved prediction of pavement responses was achieved by

modifying the bonding conditions at the interfaces, and by modeling

HMA as a viscoelastic material.

Although modeling HMA using the viscoelastic theory provides an

improved description of the material response at low and

intermediate temperatures (below 20oC), some discrepancies were

still noticed at high temperatures. It is recommended that moretheoretical modeling, which considers the anisotropic behavior of the

material, and the dynamic nature of the load, be performed to

improve the accuracy of theoretical models.

1. N. Tabatabaee, I.L. Al-Qadi, and P.E. Sebaaly, Field Evaluation of Pavement

Instrumentation Methods, Journal of Testing and Evaluation, JTEVA, ASTM, Vol.

20, No. 2, pp. 144-151, March 1992.2. H.B. Baker, M.R. Buth, and D.A. Van Deusen, Minnesota Road Research Project:

Load Response Instrumentation Installation and Testing Procedures, Final Report

No. MN/PR-94/01, Minnesota Department of Transportation, 1994.3. S. Sargand, Development of an Instrumentation plan for the Ohio SPS Test

Pavement, Final Report No. FHWA/OH-94/019, Ohio Department ofTransportation, 1994.

4. WesTrack Team, Accelerated Field Test of Performance-Related Specifications ForHot-Mix Asphalt Construction, Interim Report for Contract No. DTFH61-94-C-

00004, 1996.5. T.L. Brandon, I.L. Al-Qadi, B.A. Lacina, and S.A. Bhutta, Construction and

Instrumentation of Geosynthetically Stabilized Secondary Road Test Sections,Transportation Research Record 1534, pp. 50-57, 1996.

6. B.K. Diefenderfer, I.L. Al-Qadi, and A. Loulizi, Laboratory Calibration and FieldVerification of Soil moisture Content Using Two Types of Time-Domain

Reflectometry Probes, Transportation Research Record 1699, pp. 142-150, 2000.7. R.G. Barksdale, Compressive Stress Pulse Times in Flexible Pavements for Use in

Dynamic Testing, Highway Research Record 345, Highway Research Board, pp.

32-44, 1971.

8. A. Loulizi, I.L. Al-Qadi, S. Lahouar, and T.E. Freeman, Measurement of Vertical

Compressive Stress Pulse in Flexible Pavements and Its Representation for Dynamic

Loading Tests, Transportation Research Record, No. 1816, pp. 125-136, 2002.9. Y.R. Kim, J.S. Daniel, and H. Wen, Fatigue Performance Evaluation of Westrack

Asphalt Mixtures Using Viscoelastic Continuum Damage Approach, Final Report,Report No. FHWA/NC/2002-004, 2002.


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Discussion

PROFESSOR STEPHEN BROWN In my experience, one needs to

follow rather careful calibration techniques for stress cells or pressurecells. You mentioned that you have been taking measurements in asphalt,

which incidentally we have also done at Nottingham but not very

comprehensively and also some time ago. Can you say something about

the steps you took to calibrate your pressure cells? The reason I ask is

that I am slightly puzzled by the fact that the stress measurements did not

respond to changes in speed the point you made in your conclusions. It

seems to me illogical.

PROFESSOR IMAD AL-QADI First of all, I truly believe that the

speed should not affect the pressure unless you have dynamic movement.

However, it is the duration of loading that gets affected in hot-mix

asphalt rather than the magnitude. As the speed increases, the loading

pulse becomes narrower, and as the speed decreases, the loading pulse

becomes wider (or the loading time becomes greater). A couple of years

ago at TRB, we presented a paper on this matter and it was published in

TRR 1806. As for the calibration of the pressure cells, calibration curves

were developed by the manufacturer in order to convert the measuredvoltage from the pressure cell to pressure. The manufacturer calibration

procedure consisted of placing each pressure cell between two rigid

plates, which had inflatable rubber membranes. The pressure in these

membranes was gradually increased and held constant for a specific

time, and then the voltage was measured. This process was repeated

until the full range of the pressure cell was covered. Other approaches

involved placing the pressure cells in pressurized chamber and changing

the pressure. To evaluate the manufacturer calibration curves, testing

was performed at Virginia Tech using a Gyratory compactor first, then a

servo-hydraulic machine was used for the calibration. Small differences

were found between the manufacturer calibration curves and those

obtained using the Gyratory compactor. This difference diminishes at

high pressure values. At low pressure, the difference is considered

significant due to the edge effect and contact areas between the puck and

the pressure cell. Therefore, another test is needed in order to verify the

manufacturer calibration curves. The pressure cells are then tested using

a servo-hydraulic machine. This machine can apply a constant rate ofloading and unloading. The pressure cells were evaluated under a

combination of different metal loading plate sizes, different layers of

rubber membrane are placed between the pressure cells and the loading

Virginia Smart Road

plates, and different loading rates. It was concluded that the relationship

between the pressure cell output voltage and the applied pressure is


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indeed linear and independent of the loading rate, and that the calibration

curves provided by the manufacturer were acceptable. As mentioned in

the paper, the pressure cell transducer, which is a way from the circular

plate, was buried approximately 50mm deeper than the circular plate to

prevent any interference of measurements at the interface. All pressurecells were checked for response after installation. Of course, the

sensitive side is the pressure cell that we placed facing down. Im not

sure if thats how you used it in your case or not.

PROF. BROWN We always have it facing up so that you can see what

you are putting on top of the diaphragm.

PROF. AL-QADI Thats most definitely true when measuring the

pressure in soils; but I have to disagree when it comes to hot-mix asphalt.

To prevent any high-pressure concentration due to sharp aggregate, while

ensuring accurate measurements, the cell sensitive surface must face

down. For subgrade, a sand layer can be used under the sensitive

surface to protect it from sharp large angular aggregate; a good contact

between the cell face and the sand layer should be ensured. When the

cell was placed on top of CTA or OGDL, a geosynthetic layer was used

to protect the sensitive surface of the pressure cell. For HMA layers, the

layer underneath the pressure cell was dug and a thin layer of a mixtureof PG 64-22 binder and sand was placed to protect the sensitive side of

the pressure cell. This pressure cell is 9-in for subgrade and granular

material and 6-in diameter for hot-mix asphalt. They are much bigger

than the ones used at Nottingham in the past.

PROF. BROWN I dont want to prolong this discussion chairman, but

the point that I think I was trying to make in relation to calibration is that

in our experience it is quite important that pressure cells should be

calibrated in the material they are going to be installed in within the road.So if you are wanting to take measurements in asphalt, you must have

some arrangement in the laboratory (maybe a triaxial cell) where you

install the instruments inside the asphalt to get the correct calibration

factor, since the cells are very sensitive to the stiffness of the medium in

which you install them, as I am sure you know.

PROF. AL-QADI I agree if the pressure cell is a small one,

approximately 2-in in diameter or so; however, ours were much larger, 6-in diameter for hot-mix asphalt and 9-in diameter for granular material.

Filz presented a paper on the effect of the measured medium on the

pressure cell measurement a few years ago at TRB; but again that was


for 2-in diameter pressure cells. In addition, vehicle and FWD testing

was applied to the pressure cells after installation; FWD results are


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presented at the GeoDenver conference in 2000. Calibrating pressure

cells in a triaxial chamber is valid and needed for small pressure cells,

which I do not recommend using for pavements.

MR. RICHARD DAVIS I want to congratulate you on your study.When I first entered the highway pavement field I felt that it suffered

from a great number of unwarranted assumptions. I tried to extrapolate as

little as possible from the roadway and it seems to me that you have

made the same effort. I was always concerned about the instrumentation

and you showed concern in your statement. I was not surprised that the

elastic theory was not a good measure at high temperatures. After all,

asphalt changes by a factor of 10 million and it is the cementing material

and so it gets far out of what I would consider the elastic range when you

get to the high temperatures. I try to make my measurements at high

temperatures and low temperatures to get the extremes. I was struck by

the fact that you said that elastic theory underestimated the stresses, the

strength of the pavement at low temperatures. I was wondering, to what

do you attribute that?

PROF. AL-QADI Thank you Dick, I think at the time that you looked

into this I wasnt born; thats why I didnt refer to it. Let me get that

figure. If you look at the values that we have measured compared to thevalues that we calculated, above 35, the measured values are higher than

what we calculated. However, if you go to the low temperature, what we

measured is lower than what we calculated. That makes sense in my

opinion.

MR. DAVIS I saw the figure and I would think that the asphalt would

be at 0 C would be just about elastic, but not quite. I know finite element

analysis is an estimate for the solution of a differential equation, and it

may be that that is the reason, but I wondered what your explanation

was.

PROF. AL-QADI Let me share my opinion about that. In the case that

we run the BISAR or similar programs (including finite elements subject

to the same loading characteristics), we have a contact area that is

circular while the load is static. When we measure the pavement

response to loading, the tire is not circular and is moving. So, this will

most definitely impact the measurements. This explains our efforts forusing finite elements with a moving load.

MR DAVIS Th k

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