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CPWA INNOVATIONS IN URBAN INFRASTRUCTURE NRCC

53

A Non-Destructive Pavement Evaluation Tool forUrban Roads

By

K. O. Addo1

Introduction

Highway authorities and local municipalities periodically assess the condition of roads intheir various jurisdictions and update their databases with new information. The keypieces of required information are remaining life and rehabilitation strategy. Thisinformation enables engineers to identify, prioritize and schedule roads that requirerehabilitation as well as estimate costs. The process of determining prevailing roadconditions is called pavement evaluation. The total length of road to be evaluated is oftenlarge and techniques that are fast, economical, repeatable and cause little delay to themotoring public are preferable. A requirement that is becoming increasingly popular withengineers is that the evaluation technique be objective enough to generate results that canbe processed within a computerized framework.

Like most roads, an urban road or street is a multi-layered flexible or rigid structure builton a subgrade. Typically, a road structure consists of an upper layer of asphalt or concreteoverlying a gravel base/subbase on fill or native soil. Buried within this road structure aregas, water mains, sewers, cable TV and telephone conduits of different diameters atvarious depths and orientations. The presence of underground services makes itpreferable to use non-destructive tests to evaluate urban roads. Four tools available forconducting non-destructive tests on roads are the

1. Benkelman beam,2. Road Radar,3. Falling Weight Deflectometer (FWD) or dynaflect, and4. Spectral or Seismic Pavement Analyzer (SPA).

The Benkelman beam test procedure involves the measurement of pavement surfacerebound with a cantilevered beam when a truck loaded to 8180 kg on its rear axle movesfrom rest. Measurements are made between the dual tires on the rear axle at specifiedintervals in the outer wheel path and are then corrected for temperature and seasonalvariation. The corrected rebound values are used in a statistical manner to determine a

1. MTL (Metro Testing Laboratories) Engineering, Burnaby, BC

most probable spring rebound (MPSR). The MPSR value, a specified design reboundand traffic number are used to enter a design chart (based on an accumulated experience


55

on similar roads) to determine the overlay required to extend pavement life to 20 years.This test is fast, simple and inexpensive. However, it does not provide thicknessinformation and must be accompanied by other tests that provide this information. Ingeneral, Benkelman beam tests are performed if an overlay is the preferred rehabilitationstrategy.

The road radar is a sophisticated non-destructive tool for measuring pavement layerthickness. It uses a hybrid antenna system (comprising an air launched and surface-coupled antennae) to emit and receive electromagnetic waves. By measuring radar signalvelocity and travel times, the depths to interfaces of materials with unequal electricalproperties are determined. The technique is fast since it is performed from a vehicle inmotion at about 20 km/hr. The road radar can also be used for identifying delaminationsand cracks perpendicular to the direction of travel. However, it does not provide strengthor deformation properties.

The dynaflect and Falling Weight Deflectometer are tools that measure surfacedeflection. In this technique, a number of geophones are used to determine the staticdeflection basin resulting from a vertical impact. A back-calculation procedure is thenused to infer the thickness and resilient modulus of the constituent layers of the pavementstructure. Due to the nature of the back-calculation algorithm, reliable layer thicknessinformation is required to control the inversion process. Thus supplemental coring orroad radar tests are required.

The Seismic Pavement Analyzer (Nazarian et al, 1993) or the Spectral PavementAnalyzer – SPA – (Metro Testing Laboratories, 1994) uses a suite of wave propagationtechniques to determine shear modulus, layer thickness, support conditions and to detectdelamination. The acoustic contrast at layer interfaces is used to determine layerthickness. Shear modulus is calculated from wave propagation velocities. The ability ofthe SPA to simultaneously determine thickness and deformation modulus, withoutrecourse to coring and drilling, makes it an attractive tool for evaluating urban roads.Coring and drilling may therefore be reserved for calibration and verification purposesonly and do not have to be performed on a routine basis.

This paper presents two case histories on the use of the SPA to evaluate urban roads.Layer thickness determined from the SPA is compared with core thickness. The SPAinformation is used to estimate remaining life on one road while it is compared withBenkelman beam rebound curves measured on the other. For the sake of completeness,an overview of the SPA and its basic concepts are also presented.

Equipment Description

The SPA equipment comprises a trailer towed by a van. The steel-framed single-axletrailer is approximately 3.2 m long and 1.0 m wide. Figure 1a shows a picture of the SPAat work on an urban road.

An array of sensors, two impact hammers, a temperature sensing system, a hydrauliccontrol system, an electrical unit and power source are mounted on the trailer. Table 1shows the positions of the sensors relative to the impact hammers.


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Table 1Sensor – Hammer Configuration

Sensor Number Distance from Hammer to Sensor(mm)

Hammer HF Hammer LF

A1 76.2

A2 152.4

A3 304.8

A4 609.6

A5 1219.2

G1 139.7

G2 984.2

G3 2178.2

G4 Adjustable

The trailer is particularly designed and built for rapidly collecting wave propagation dataon roads and runways. The trailer is fitted with a special lighting system that redirectsvehicular traffic away from the testing lane. The sensor array consists of fiveaccelerometers and four geophones that are acoustically shielded from its support throughenclosure in PVC holders and special vibration isolators. These are fitted with rubber feetfor better energy transfer. Two instrumented hammer sources (high and low frequency)with adjustable but limited strokes are also housed on the trailer. Sensors and hammersare independently raised or lowered by a hydraulic system via mechanical springs.

The SPA equipment comprises a compressor-charged air tank that supplies power forraising, lowering and firing the hammers. A pressure-sensing switch automaticallycontrols the compressor. Pressure for raising, lowering and holding down the receivers aswell as firing the hammers are individually controlled and monitored. Activation of thehammers and sensors may be enabled from hardware or software. Coupled with leadsfrom the hammers and sensors, the hardware control is a lightweight box that permits theuse of the trailer with third party data acquisition systems and interpretation software.

The tow vehicle is equipped with an optional Global Positioning System (GPS) and adistance-measuring device. This arrangement permits the operator to reliably identify teststations on the road and eliminates the need to manually mark locations for testing.Recently, a video camera system has been installed to take still photographs of testlocations. Such photographs are valuable tools in the interpretation of complexwaveforms measured on urban roads. A twin temperature-sensing device is also mountedbeside the hammer assembly for measuring air and pavement temperatures. The latter isused for adjusting measured modulus to the standard 20°C.


57

The field microcomputer is equipped with analogue-to-digital and signal conditioningboards. A software program is used to collect and interpret data in real time on the road.The software also saves all raw and processed data to disk for further review andreanalysis if necessary. Figure 1b shows the control computer displaying intermediatespectral analysis of surface waves (SASW) results in real time.

For off-road and other locations that are inaccessible to the SPA, a portable onboardgeophone and hammer system may be used for testing. This off-road system comprises alaptop equipped with an A/D card in an expansion chassis, geophones, an interface unitthat links the laptop and geophones.

Basic SPA Concepts

Compared with other techniques of evaluating pavements, the analysis of SPA data iscomplex. The entire analysis is therefore done with a computer program. For thepurposes of completeness, a brief overview of the methods used in this computer programis outlined. These are

1. Impact echo2. Impulse response and3. Spectral-analysis-of-surface-waves (or SASW).

Impact Echo

This test is used for determining the thickness of the paving interface or depth to defect inthe paving layer. The defect could be a void, crack or a deteriorated zone.

An impact echo measurement is made with a geophone placed close to the wavegeneration point. The trace recorded by the geophone is converted to displacement andFourier transformed to determine the relevant resonant frequency. The thickness or depthto reflector is determined from the following relationship.

zv

fp=

2[1]

where z = depth to reflectorf = resonant frequencyvp = compression wave velocity

The principle underlying this equation is that the stress wave undergoes multiplereflection between the surface and the interface. On each arrival at the surface, acharacteristic displacement is produced, thus setting up a periodic waveform. The period,(T), of this wave equals the ratio of the length of the total travel path (2 z ) to thecompression wave velocity ( vp ) or

Tz

vp

= 2[2]


58

Substituting frequency for the reciprocal of the period ( fT

= 1) in equation [2] yields

equation [1].

To obtain the compression wave velocity, the arrival times of P-waves at two knownsensor stations are used in the calculation process. Usually, these arrivals are readilypicked off at stations further from the impact point. Distance from the source is requiredfor the wave energy to fractionally separate into the component wave types. Thecompression wave velocity is calculated from the following equation

vd

t tp =−2 1

[3]

where vp = compression wave velocity

t2 = arrival time at far receivert1 = arrival time at near receiver andd = distance between sensors.

The compression wave velocity computed from equation [3] may be used directly inequation [1] to calculate depth to the reflector or to calculate Young’s modulus as shownin equation [4]

E vp= ρ 2 [4]

where E = Young’s modulusρ = mass densityvp = compression wave velocity

Figure 2 shows typical power spectra and coherence plots used in data reduction.Sansalone and Carino (1988) described the impact echo test in detail.

Impulse Response

This test is performed to determine the shear modulus of the subgrade and the dampingratio of the pavement system. The magnitudes of these parameters are measures ofsubgrade competence and condition of support respectively.

The test is similar to the impact echo test except that the force-time function f t( ) of theimpact and the geophone response, x t( ) , are recorded. The impulse response spectrum,or mobility spectrum in this case, is calculated as follows.

H fX f F f

F f F f( )

( ) ( )

( ) ( )

*

= [5]

where H f( ) = mobility spectrum

F f( ) = Fourier Transform of f t( ) , and

F f*( ) = complex conjugate of F f( ) .

= Fourier Transform of X f x t( ) ( )


59

The flexibility spectrum, from which conditions of support and the existence of voidsmay be determined, is then computed from equation [5] using numerical integration.Figure 3 shows typical complex stiffness (the reciprocal of flexibility) and coherenceplots.

Due to background and other noise, the flexibility spectrum is curve-fitted beforederiving the modal parameters. For analytical simplicity, the road structure is assumed tohave a single-degree of freedom defined by a natural frequency (f), a gain factor and adamping ratio. Higgs (1979) presented details of the impulse response test.

The shear modulus (G) of the subgrade may then be calculated equations given by Dobry& Gazetas (1986) and Richardson and Formenti (1982).

Spectral Analysis of Surface Waves (SASW)

This is the main method for determining resilient modulus and thickness profiles inlayered systems such as pavements. The key principle is the dispersion of surface waves -which means that surface waves of different frequencies propagate at different depths.Thus by measuring the propagation velocity of waves of different frequencies, thevariation of velocity (or stiffness) with depth is obtained. An impact with certain desiredcharacteristics is used to generate waves that are monitored at two or more receiverstations. The computations involved in carrying out an SASW analysis may be outlinedas follows. For simplicity, only two sensors are used but the procedure is readilyapplicable to multiple pairs of receivers at different spacing.

1. Transform the pairs of signals ( xt and yt ) into the frequency domain ( X f and Yf ).

2. Compute the mean of the cross-spectrum in the frequency domain and extract thephase (φ( )f ) information as a function of frequency

S f X f Y fxy ( ) ( ) * ( )= [6]

where S fxy ( ) = cross-spectrum of xt and yt

X f( ) = Fourier Transform of xt

Y f*( ) = complex conjugate of the Fourier Transform of yt

The function φ( )f is bounded between +π and -π and may be unwrapped using thefollowing equation

φ φ πu f k( ) = + 2 [7]

where k is an integer. If the given pair of sensors is a distance d apart, then the phasevelocity is given by

vd

r = ωφ

[8]

where vr = phase velocity,

ω = angular frequency, 2πf .


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A plot of phase velocity versus frequency is called a dispersion curve and containsstiffness and layering information. However, not all the dispersion points thus calculatedare valid. A parameter called root mean square coherence is used to define dispersionpoints that may be invalid.

3. Calculate the root mean square coherence

γ xyxy

xx yy

fS f

S f S f( )

( )

( ) ( )= [9]

where γ xy f( ) = root mean square coherence,

S fxx ( ) = Auto power spectrum of xt andS fyy ( ) = Auto-power spectrum of yt .

The root mean square coherence is a measure of signal quality and values of 0.95 orhigher may be used to filter out suspect dispersion points. Figures 4a, 4b, 5a and 5b showtypical spectral functions used in the analysis of SASW data.

An iterative numerical process called inversion is then used to determine the variation ofshear wave velocity ( vs ) with depth. The references at the end of this paper may beconsulted for further information on this numerical procedure.

The shear modulus ( G ) and the dynamic Young’s modulus (E ) (which is equivalent tothe resilient modulus) may then be determined from the following equations

G vs= ρ 2 [10]

E G= +2 1( )ν [11]

where ρ = mass density,vs = shear wave velocity andν = Poisson’s ratio.

The modulus of asphalt layers is strongly dependent on temperature. This temperaturedependency has been well documented by many researchers (Witczak, 1972) and isincorporated into post-processing software.

The above is a simplified explanation of the concepts SASW. The actual numericalroutines deployed in the computer programs used in analyzing the data reported in thispaper are more sophisticated. In addition, special add-on programs are used to read thelarge volume of numerical data into spreadsheet software for further processing andautomated plotting.

Test Sites

The two pavement sites tested with the SPA are both located in the City of Surrey inBritish Columbia. Surrey is reported to be the fastest growing city in Canada and itspopulation has increased substantially in the last five years. Consequently, traffic loadson its arterial, collector and local roads have exceeded anticipated growth and pavement


61

life is expected to be much shorter than initially designed for. One such road is 72Avenue, a two-lane wide collector. The section on this road from 145th Street to 152nd

Street was tested with the SPA in the spring of 1997. The length of the test section wasapproximately 1300 meters.

144A Street is the second test section. This two-lane 400 meter local road links 144 Streetand Highway 99A. It also provides a more direct access to City Hall from the highway. Anumber of distress characteristics such as surface depressions, longitudinal and alligatorcracks were observed on the road.

According to the city’s pavement management system, these two roads were due forevaluation and the SPA was used in conjunction with the Benkelman beam.

A sketch of the relative locations of the two test sections is shown in Figure 6.

Field Procedure

A trained technician typically conducts the field tests and is responsible for ensuring thatthe appropriate traffic control measures are in place. Once positioned at a test location, aGPS (global positioning system) reading may be taken.

On activation from the keyboard, the array of seismic receivers and hammer source arelowered onto the pavement surface. Three sets of up to eight hammer impacts aregenerated. For each set, the output of the hammer load cell and designated sensors arerecorded and saved during the last three impacts. The designated group of sensors isactivated as required by a multiplexer. The first few hammer hits in each set are used forsetting the gains of the amplifiers. When the impacts are completed, the sensors andhammers sources are automatically raised. While the sensor array is in contact with thepavement surface, the ground and air temperatures are recorded. A photograph of the testlocation may be then be taken.

The operator then examines the recorded waveforms and either moves on to the nextlocation, repeats the test or takes a core sample. A distance-measuring device is used forpositioning at the next location. It takes less than a minute to test a given location.

Results

The layer and stiffness information determined from the SPA tests are presented inFigures 7, 8, 9 and 10. Layer thickness information available from coring and drilling hasalso been indicated on the figures. Figure 11 shows Benkelman Beam results on 144 AStreet. Table 2 shows a summary of the thickness information presented in Figures 7 –10.


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Table 2

Comparison of Asphalt Thickness from SPA and Coring

Site Lane Station(100 m)

Asphalt Thickness(mm)

Difference(%)

CoreCondition

SPA Coring

72 Ave. North 3.30 195 185 5.4 Coarse

9.80 95 100 (+35) 5.3 2 overlays

South 1.20 115 120 4.3

6.40 190 185 2.7 Coarse

144A St. Northbound 1.60 60 60 (+85) <0.01 2 overlays

3.30 70 85 21.4 Degraded

Southbound 0.90 115 140 21.7 Degraded

2.40 87 100 14.9 Degraded

3.90 50 60 20.0 Degraded

During field testing, it was noted that the paving layer on 72 Avenue was in a much bettercondition than 144A Street. There were less pavement distress characteristics (cracks,surface depressions, etc.). The results in Table 2 indicate that asphalt core thickness wasin better agreement with the SPA results on 72 Avenue. The presence of cracks and otherdistress features cause complexity in waveform shapes that ultimately affect datainterpretation and the significance of the measured parameters. For example, onpavements with multiple overlays or delaminated paving layers, the SPA gives thethickness of the uppermost overlay or the depth to the shallowest delamination and notthe total asphalt thickness. Station 1+60 on 144A Street and 9+80 on 72 Avenue areexamples.

On resurfaced older roads, the lower half of the asphalt layers is degraded. Thisdeterioration sets up an acoustic contrast that causes changes in wave propagation. This isequivalent to material boundary resulting in an underestimation of the asphalt thickness.The underestimation of asphalt thickness on 144A Street was partly due to poor asphaltquality in the older overlays.

The shear modulus determined from SASW tests have been compared in the past withmodulus determined from other methods (such as the down-hole, cross-hole seismic conepenetration tests) and found to be reliable (Addo and Robertson, 1992). Since mostpavement engineers are familiar with the Benkelman beam, results of this test on 144 AStreet is presented in Figure 11. The decline in base and sub-base modulus towardsStation 4+00 in the subsurface layers supports the high rebound values similarly recordedby the beam. Ongoing studies appear to indicate that the Benkelman beam deflections


63

may be predicted by softening the shear modulus from SPA tests to about 20% of itsinitial value.

The shear modulus of the subgrade on the entire test section (determined from theimpulse response test) varies only slightly but the rebound values are very different fromone end to the other. While there was other evidence to support high rebound values, thelow rebound values may partly be attributable to thicker asphalt layers.

Remaining Life

The key question in most pavement evaluation work is “How bad is it?” If the answer canbe given in terms of a numerical rating, then the task of prioritizing roads forrehabilitation becomes easier.

As a preliminary procedure, the design traffic was used in conjunction with the averagethickness and modulus of the worst 20% of the test locations. Based on previousexperience, the 20th percentile value (i.e. 80% of the data is better) was picked to be morerepresentative of the weaker locations and at the same time avoids outliers. Using damagemodels, elastic layer theory and traffic data provided by the City of Surrey, the 20th

percentile values of shear modulus and thickness were used in a computer program toestimate remaining life based on fatigue and rutting. This computer program, similar toexisting programs such as the Chevron N-Layer, BISAR or DAMA from the AsphaltInstitute, uses a mechanistic-empirical approach to predict remaining life by computingthe strains at layer interfaces. The use of shear modulus instead of resilient or Young’smodulus in these computations is equivalent to a softening factor of about 2 - 5. Thissoftening factor accounts for the low strain level at which seismic wave propagation testsare conducted (10-4 %) and the loading frequency.

On 72 Avenue, the remaining life was calculated to be 3.3 years. This value agreed verywell with the prediction of the Pavement Management System. It must be emphasizedthat this is only preliminary. Further verification is required before any generalizationscan be made.

Conclusion

The case histories presented indicate that asphalt thickness can be estimated from SPAtests to an accuracy of less than 6 % if the asphalt is in good condition. Further researchis required to improve the estimation process and to reliably determine the thickness ofthe remaining pavement layers.

Based on previous correlation, the shear modulus of the pavement layers determinedfrom the SPA was adjusted for strain level and used to determine an acceptable remaininglife that was in close agreement with an independent pavement management system.Further work is required to statistically account for the wide variations in pavementproperties, a factor that seems to have significant effect on the estimated remaining life.


64

In the 1993 AASHTO Guide for Design of Pavement Structures, the inability todetermine layer thickness and material type from NDT was one reason cited in support ofdestructive testing (page III-49). While destructive testing is good practice, the use ofNDT to simultaneously determine thickness and modulus will ultimately reduce thefrequency of coring and drilling.

Acknowledgements

The research and development of the SPA equipment was undertaken by Metro TestingLaboratories and was financially sponsored in part by the Industrial ResearchAssistantship Program of the National Research Council of Canada. I thank mycolleagues Drs. Soheil Nazarian, Mark Baker and Kevin Crain for their assistance. Thefield support of Curtis Syrnyk and Paul Hii are greatly appreciated. Finally, I thank BrianSnow of Web Engineering, John Paley of R.F. Binnie & Associates and the City ofSurrey for sponsoring the road evaluation projects.

ReferencesAddo, K. O. and Robertson, P. K. (1992), Shear Wave velocity Measurement of Soils

using Raleigh waves, Canadian Geotechnical Journal, Vol. 29, No. 4, pp. 558-568.

Dobry, R. and Gazetas, G. (1986), Dynamic Response of arbitrary shaped foundations.ASCE Journal of Geotechnical Engineering, Vol. 112, No. 2, pp.109-135

Higgs, J., (1979), Integrity testing of piles by the shock method. Concrete October, 1979,pp. 31.

Metro Testing Laboratories (1994), Development of an automated SASW TestEquipment. Research Report Submitted to the Industrial Research AssistantshipProgram, National Research Council, 35 pp.

Nazarian, S., Baker, M. and Crain, K. (1993), Development and Testing of a SeismicPavement Analyzer. National Research Council, Report No. SHRP-H-375, 165 pp.

Richardson, M.H. and Formenti, D.L. (1982), Parameter Estimation from FrequencyResponse Measurements Using Rational fraction polynomials. Proceedings of the 1st

International Modal Analysis Conference (Society for Experimental Mechanics,Orlando, FL, pp. 167 – 181.

Sansalone, M. and Carino, N. J. (1986), Impact Echo – A method for flaw detection inconcrete using transient stress waves. Report NBSIR 86-3452, National Bureau ofStandards, Gaithersburg, MD.

Witczak, M. W. (1972), Design of full-depth asphalt airfield pavements, Proceedings ofthe International Conference on the Structural Design of Asphalt Pavement, London,England, Vol. 3, pp. 550–567.


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a. Hardware

b. Software

Figure 1. The SPA equipment


66

-0.4

0

0.4

0.8

1.2

0 5 10 15 20 25

Impact

Coherence

Loga

rithm

of P

ower

Spe

ctru

m

Frequency (kHz)

a. Coherence and Power Spectrum of Impact

-6

-5.5

-5

-4.5

-4

-3.5

-3

0 5 10 15 20 25

Sensor

Loga

rithm

of P

ower

Spe

ctru

m

Frequency (kHz)

b. Power Spectrum of Sensor Signal

Figure 2. Typical power spectra from Impact Echo test.


67

0

5

10

15

0 50 100 150 200

Measured

Curve Fit

CoherenceS

tiffn

ess

(MP

a)

Frequency (kHz)

a. Measured and fitted real stiffness

0

5

10

15

0 50 100 150 200

MeasuredCurve Fit

Stif

fnes

s (M

Pa)

Frequency (kHz)

b. Measured and fitted imaginary stiffness

Figure 3. Typical stiffness and coherence plots from Impulse Response test


68

0

0.2

0.4

0.6

0.8

1

0 2000 4000 6000 8000

Roo

t Mea

n S

quar

e C

oher

ence

Frequency (Hz)

a. Coherence Function

-4

-3

-2

-1

0

1

2

3

4

0 2000 4000 6000 8000

Pha

se (

radi

ans)

Frequency (Hz)

b. Phase of the Cross-Spectrum Function

Figure 4. Typical spectral functions used in SASW


69

-25

-20

-15

-10

-5

0

0 2000 4000 6000 8000

Unw

rapp

ed P

hase

(ra

dian

s)

Frequency (Hz)

a. Unwrapped Phase

0

0.5

1

1.5

20 500 1000 1500 2000 2500

Wav

elen

gth

(m)

Raleigh Wave Phase Velocity (m/s)

b. Raleigh Wave Dispersion Curve

Figure 5. Unwrapped phase and dispersion curves


70

7 2 Av en u e

15

2 S

t.

N

C ity H a ll

H w y 1 0

14

4 A

St.

14

4 S

t.

H w y 99 A

Figure 6. Location of test sites (not to scale)


71

0

50

100

150

200

250

300

350

4000 2 4 6 8 10 12 14

Asphalt

BaseD

epth

(m

m)

Station (100 m)

Asphalt Core

a. Layer Thickness

101

102

103

104

0 2 4 6 8 10 12 14

Asphalt

Base

Subbase

She

ar M

odul

us (

MP

a)

Station (100 m)

b. Stiffness Profile

Figure 7. SPA test results in the North Lane of 72 Avenue


72

0

50

100

150

200

250

300

350

4000 2 4 6 8 10 12 14

Asphalt

Base

Dep

th (

mm

)

Station (100 m)

Asphalt Core

a. Layer Thickness

101

102

103

104

0 2 4 6 8 10 12 14

Asphalt

Base

Subbase

She

ar M

odul

us (

MP

a)

Station (100 m)


Figure 8. SPA test results in the South Lane on 72 Avenue


73

0

0.1

0.2

0.3

0.4

0.50 1 2 3 4

Asphalt

Base

Dep

th (

m)

Station (100 m)

Asphalt

Base/Subbase

a. Thickness from SASW and Coring / Drilling.

106

107

108

109

1010

0 1 2 3 4

AsphaltBaseSubbaseSubgrade

She

ar M

odul

us (

Pa)

Station (100 m)


Figure 9. Thickness and stiffness profiles on 144 A Street (Northbound).


74

0

0.1

0.2

0.3

0.4

0.50 1 2 3 4

Asphalt

Base

Dep

th (

m)

Station (100 m)

Asphalt

Base

Subbase

Cores

a. Thickness Profile

106

107

108

109

1010

0 1 2 3 4

AsphaltBaseSubbaseSubgrade

She

ar M

odul

us (

Pa)

Station (100 m)


Figure 10. Layer thickness from SPA and Coring/Drilling on 144 A Street (Southbound)


75

0

0.5

1

1.5

2

2.5

0 1 2 3 4 5

Northbound

Southbound

Unc

orre

cted

Reb

ound

(m

m)

Station (100 m)

a. Rebound Curve.

0

0.5

1

1.5

2

2.5

3

0 1 2 3 4 5

Northbound Lane

Southbound Lane

Mos

t Pro

babl

e S

prin

g R

ebou

nd (

mm

)

Station (100 m)

Pavement Temperature = 25 deg. CSeasonal Correction Factor = 1.20

Design Rebound = 1.4

b. Most Probable Spring Rebound (MPSR)

Figure 11. Benkelman Beam test results on 144A Street

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