Evaluation of NDTE Technologies
for Airport Pavement Maintenance
and Acceptance Activities
Imad L. Al-Qadi
John S. Popovics
Wei Xie
Sara Alzate
University of Illinois at Urbana-Champaign
Outline
• Project Scope and Objectives
• NDTE State-of-art report: Promising NDTE
technologies to assess existing and new airport
pavements
• Future Work
Objectives
• To determine the effectiveness and
practicality of new and existing NDTE
technologies for maintenance, evaluation,
quality control and acceptance of flexible
airport pavements
• To evaluate and recommend appropriate
NDTE technologies to the FAA based on field
evaluation results
Scope of work
Review and summarize
existing and new NDTE
technologies
State-of-the-art
report
New research
Identify current NDTE
needs for airport pavements
and facilities
Identify promising NDTE
technology
(technical and
practical suitability)
Field testing and
analysis of promising
NDTE
technology
Final
report
NDTE State-of-the-art Report
• Existing NDTE methods are summarized in a
draft report, for FAA review and comment
• Each method is presented in a chapter:
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–
–
–
–
–
–
–
1) Impact-echo
2) Surface waves
3) Sonic/ultrasonic
4) Nuclear radiometry
5) Infrared thermography
6) GPR
7) Laser profiling
8) Digital imaging
NDTE State-of-the-art Report
• Each chapter discusses the following:
–
–
–
–
–
Theory
Equipment
Benefits and applications
Limitations
Recent developments
Nuclear Density Gauge
•
•
The radiation intensity of gamma rays that passes
through a medium, or is scattered back from a medium,
is used to measure density.
Nuclear density gauges are compact and provide direct
and rapid measurements
Application of Nuclear Density
Gauge
• Measuring in-situ HMA, concrete and
solid densities
• Suitable for both thin and thick layers;
better for thick layers.
Limitations of Nuclear Density
Gauge
• Need for calibration
• Affected by lift thickness and variability of
supporting layer
• Difficulties in identifying levels of
segregation
• High initial cost, certification requirement,
periodic inspection, and difficulties in
shipping and transport and disposal.
Impact Echo
Resonant frequency interpreted for thickness information
Application of Impact-echo
• Measuring concrete slab thickness
• Identifying location and depth of
delamination defects in concrete
Limitations of Impact-echo
• Local, point contact measurement
• Not effective for HMA pavements
• Only effective for top layer in pavement
system
• Difficulties in locating small defects
Surface Waves
(Spectral/Multiple Analysis of Surface Waves
(SASW/ MASW)
Measure dispersion of surface waves in layered media
Application of surface waves
• Estimate pavement layer properties
(thickness and modulus)
Estimated
stiffness
profile
Portable Seismic
Pavement
Analyzer (PSPA)
for SASW
Interpretation of MASW
Lamb wave curve best fit to data to give layered structure
6000
Impact-echo mode
5000
Phase velocity (m/s)
distance(cm)
50
100
150
4000
3000
2000
200
1000
250
0
0.5
1
1.5
2
Time(s)
2.5
3
3.5
x 10
Stacked multiple signal data
-3
2
4
6
8
10
12
14
16
18
20
Frequency (kHz)
MASW mapping of signal data
Limitations of surface wave
• Local, point contact measurement
• Data inversion is complicated (MASW
approach has sounder technical basis
than SASW)
• Not reliable for accurate thickness
measurements of a specific layer
Sonic/ Ultrasonic
Measure velocity
of various
wave modes
propagating in
pavement
and relate to
mechanical
properties
http://www.cflhd.gov/agm/engApplications/Pavements/413S
pecAnalySurfWaveandUltrSonicSurfWaveMethods.htm
0.04
0.03
0.02
Amplitude
0.01
0
0.01
0.02
0.03
0.04
5
1 10
2 10
5
Near sensor
Far sensor
3 10
5
Δt
Δt
4 10
Time ( s)
5
5 10
5
6 10
5
7 10
5
Application of sonic/ ultrasonic
• Estimate mechanical properties of
pavement (Modulus, strength, damage
level, etc.)
• Locate voids/ interfaces
Limitations of sonic/ ultrasonic
• Local, point contact measurement
• Estimation of absolute values of modulus
and strength of concrete is not accurate
Digital Imaging Technology
• Automated digital imaging system consists of
image acquisition and distress image processing
After Huang et al. 2006
Equipment and Data Collection
• DMI is used to control the acquisition of
digital image
• Distress detection, isolation, classification,
segmentation, and compress
• Fast wavelet transform for the wavelet-based
distress detection, isolation, and evaluation
Video
Application of Video Imaging
• Segregation measurement:
– Identify texture variation related to HMA segregation
– Use GLCM technique to identify segregation
• Crack Detection/ Surface Distress
– Individual crack information can be vectorizing
– WiseCrax is used to automatically detect cracks,
classify and generate crack map
– Recent development uses processing algorithm for
high-speed, real-time inspection of pavement
cracking
Limitations of Imaging
Technique
• Video image can only detect surface
distress
• There is environmental requirement
during data collection
• The system is vulnerable to vehicle
vibration
• Video image can measure gradation
segregation level; but not temperature
segregation
Laser Technique
•
•
Pavement surface information can be determined by the
movement of reflected beam spot on the detector
It can supply rapid, continuous, and high accurate
measurement
Laser Beam
Detector
Lens
Pavement Surface
Equipment and Data Collection
Two types of laser camera are available to digitally image
pavement surface: area scan and line scan
Line scan and area scan laser systems (Xu et al. 2006)
Friction and Roughness Measurements
• For friction use high-pass filter with 50mm
wavelength cutoff
• For roughness use low-pass filter with 0.5m
wavelength cutoff
Texture Classification
Microtexture
Macrotexture
Megatexture
Roughness
Relative Wavelength
λ<0.5 mm
0.5mm < λ < 50mm
50mm < λ < 500mm
0.5m < λ < 50m
Applications
• Detect segregation:
– texture ratio of segregated to non-segregated area
to measure segregation level
• Rutting measurements:
– Automatic, rapid and continuous
• Crack measurements:
–
–
–
–
Valley detection of candidate cracks
Validation algorithm
Characterize crack types and pattern
3D laser imaging has been introduced
Limitations
• It provides pavement surface condition
only
• Difficult to distinguish between texture
and crack
• Transversal cracks are likely to be
detected, while longitudinal cracks are
easily missed
• Narrow and shallow cracks may be
filtered out during data processing
Infrared Thermography
• Infrared thermography is standardized by ASTM
D4788. It includes passive and active methods
• Subsurface changes in pavements generate surface
temperature variations
Equipment and Data Collection
Infrared sensors bar
Applications
• QC/QA
• Segregation measurement
• Crack and defect measurement
detection
Defect
Limitations
• It is applied for near-surface surveys
• It cannot distinguish between gradation
and temperature segregation
• For existing pavements, it depends on
solar energy
Ground Penetrating Radar
• Ground Penetrating Radar (GPR) is a
special kind of RADAR
• Purpose of using GPR:
– Detect targets buried in a dielectric
medium
– Estimate their depths
• GPR applications: geophysics,
archeology, law enforcement,
evaluation of civil structures (buildings,
bridges, pavements)
Principle of GPR
Transceiver
Control Unit
Antenna
Layer 1
Layer 2
DMI
GPR Antennae
• Ground-coupled antenna: in contact with ground
surface
• Air-coupled antenna: 1 to 2 ft above surface
Ground Coupled Antenna
Horn Antennae
Typical GPR Response (scan)
Amplitude
12000
10000
8000
6000
4000
2000
0
-2000
-4000
-6000
-8000
0
2
A0
6
A1
8
t2
Base
4
Time (ns)
10
Base
HMA
HMA
t1
12
Subgrade
14
16
Subgrade
A2
GPR Data Collection
HMA
Base
Subgrade
HMA
Base
Subgrade
Layer Thickness Estimation
Thickness of i
di 
th
t1, d1
HMA
r,1
2  r ,i
 Ap  Ao 

εr ,1  
A A 
o 
 p
ε r ,n
layer:
cti
  A  2 n2
1  0   γ
i
 A  
i

1
p
 εr ,n-1    2
  A  n2
 1   0    γi
  Ap 
i 1
  
A0
A1
Base
Ai An1 

Ap
Ap 

Ai An1 


Ap
Ap 
t2, d2
r,2
2
A2
Subgrade
2
r,3
i 
 r ,i   r ,i 1
 r ,i   r ,i 1
New Pavements (QC/QA )
Classic GPR thickness estimation gives accurate results:
Depth (mm)
40
0
50
100
150
200
250
300
350
400
450
500
42.5
45
Distance (m)
47.5
50
52.5
55
HMA
Base
HMA Design
Base Design
57.5
60
GPR Accuracy: New Pavements
Dielectric Constant Using CMP
Common midpoint (CMP) technique (or commondepth point, CDP) is used as follows:
x
T
HMA
r1
T/R
vt1  2h
R
vt 2  2 h 2  ( x / 2) 2
t1
h
t2
P
 : EM velocity in the layer
v
c
r

x
t 22  t12
c 2 (t 22  t12 )
r 
x2
Modified CMP Technique
Modified common midpoint technique:
Snell’s law of refraction:
x0
T
air
r0=1
PCC
r1
(1)
R
x1
qi
h0
T/R
t1
qt
(2)
t2
P
Using the figure:
h1
(3)
(4)
Modified CMP Technique
Modified common midpoint algorithm:
1. Measure the reflection times t1 and t2
2. Calculate the transmission angle qt using:
3. Find the angle qi by solving numerically
 sinθ i
4. Solve for r1 using:  r1  
 sinθ t




2
5. Compute HMA thickness using t1 and r1
h1  ct1 2  r1
Modified CMP Setup
Depth Resolution Enhancement
WS
Amplitude
BM-25.0
OGDL
Base
12000
10000
8000
6000
4000
2000
0
-2000
-4000
-6000
-8000
Surface
Reflection
10000
Base/Subgrade
Reflection
Reflection
Overlap
0
12000
HMA/Base
Reflection
5
10
15
Time (ns)
Surface Reflection
Amplitude
8000
WS/BM-25.0
Reflection
6000
Measured Signal from:
OGDL/Base
Reflection
4000
Thin layer interfaces
not visible because of
reflection overlap
2000
0
-2000
Base/Subgrade
Reflection
BM-25.0/OGDL
Reflection
-4000
-6000
0
5
10
Time (ns)
15
Synthesized Signal
Measured vs. Simulated Signal
Layer Thickness Estimation by
Iteration
Raw GPR
Data
Preprocessing
Layer
Thicknesses
Layer Interface
Detection
Dielectric
Properties
Estimation
Detection Results
Distance (m)
20
30
40
0
Time Delay (ns)
2
WS
4
6
8
10
12
BM-25.0
OGDL
Base
Copper plates
14
16
Detected Layer Interfaces
50
60
GPR Data Analysis Software
Channel 1
Channel 2
Channel 1
Channel 2
Density Measurement with GPR
• According to volumetric mixture theory, HMA dielectric
constant depends on aggregate, binder and air volumes
void(%)  a  e
b a
Note: calibration coefficients (a and b) are determined
from field cores.
•
•
•
A drop in dielectric value may indicate a density
change
2GHz antenna is preferred
It has potential….it requires more investigation
Defects Detection with GPR
• Segregation: locations of course-graded and
dense-graded mixes has been reported
• Stripping: additional reflections appear
between surface and layer interface
• Moisture content: relationship between
dielectric constant and moisture content
moisture(%)  C  D   b
Locating Reinforcement (CRCP)
Transversal Reinforcement
Concrete
Asphalt OGDL
Longitudinal Reinforcement
Copper Plate under Slab
Ground-Coupled Data, CRCP,
VA. Smart Road
GPR Application on Composite Pavement
Measure overlay thickness and detect overlaid joints:
Surface
8 in
Overlay
3 ft
3 ft
Rebar
100 ft
Joint Spacing
Interface of HMA and PCC
ISAC
Limitations of GPR Technique
• Air-coupled antenna has limited penetration
depth
• GPR survey requires dry pavement condition
• Errors may result from dielectric constant
estimates from surface reflection
• Cores may be needed to determine
calibration coefficients
• Strong reflection may mask weak signals
• Accuracy of GPR results depends on
adopted data analysis technique
Future Work
• During this project year, we aim to
– Identify current NDTE needs for
airport flexible pavements
– Identify promising NDTE technology,
and carry out new research efforts to
meet those needs