An accurate accounting of the locations of the GPR measurements is critical to an
effective investigation. The system employs an integrated WAAS DGPS, a backup
distance measuring instrument (DMI) synchronized with the vehicle transmission for
where GPS signals are unavailable, and wide area as well as antenna field-of-view digital
video systems. The DGPS can provide location information with accuracy error of less
than 3 ft (1 m), but it can be adversely affected by bridges, tunnels, and radio frequency
interference. The DMI provides continuous positioning information to supplement the
DGPS data but with an accumulating error of about 0.2 percent. Digital video images of
the track are collected to further refine location information through identification of
fixed assets along the track. The location data are verified against 1-meter USGS aerial
or satellite DOQ maps. Even with this redundancy, an instance occurred during this
project where no positioning information was obtained due to a combination of high RF
interference in a urban environment (a lightning storm and strong solar activity creating a
geomagnetic storm) making DGPS worthless, the DMI slipped on rain slick rails, and a
spider crawled into the digital video camera lens and blocked the view.

In addition to QA/QC of the antenna field of view and help in positioning, the digital
video can also help to assess ties condition and other visual conditions along the track.

3.4 Project Surveys

As part of this multiple phase project to develop GPR for railroad use, over 230 miles
(370 km) of track has been surveyed. In order to gather GPR experience on prevalent
substructure conditions, the GPR testing first focused on the heavy haul coal lines in the
western United States. Subsequent GPR surveys were performed in Mississippi and
Arkansas, where chronic substructure problems were also prevalent and maintenance and
repairs were imminent. Further tests were performed in North Dakota and along
electrified urban commuter lines in New Jersey. Table 1 lists the general location, survey
mileage, and general site conditions at locations surveyed during this project.

14


6. Recommendations

The continued development of GPR for railroad application should focus on automation
of data processing and interpretation to provide fast, automated investigation of track
substructure conditions. The continued development of absolute calibration procedures
will produce the ability to quantify the moisture content of various substructure layers. In
addition, methods are currently being developed to determine the fouling condition of the
ballast by extracting statistical scattering textures from the GPR images. Follow-on
phases have been planned to include installing the radar on hi-rail TGMVs and use it to
collect radar images routinely and to provide automating the calculation of the depths,
densities, and moisture contents of the substructure layers.

Key components of follow-on work are:

1) Increasing the rate of radar data acquisition.

- Requires the purchase of existing, off-the-shelf hardware components.

2) Completion of GPR data calibration and processing automation (including
location).

- Calibration requires using multiple antenna geometries, polarizations,
and/or frequencies. This requires purchase of additional hardware,
software development, and field testing.

- Processing automation requires standardization of the data acquisition
process and therefore requires gaining experience by collecting data in a
wide variety of field conditions (both environmental and subsurface),
thereby encountering unforeseen conditions or problems that affect the
data collection process. Processing is presently automatic for the
conditions already encountered.

3) Completion of automation of GPR data modeling to density and water content.

- Requires the completion of the calibration and processing automation.

- Once automatic processing and calibration are complete, then the GPR
data can be automatically modeled with known and proven full
waveform modeling techniques. These techniques are presently used in
highway applications where the calibration automation is more
straightforward.

35


To get the greatest benefit from the GPR, the radar information must be integrated with
other information such as track geometry, track asset features, track stiffness
measurements, maintenance records, and geo-environmental information. The geo-
environmental information includes geology, terrain, depositional environment, clay type,
(expansive versus non expansive, dispersive versus flocculated) drainage characteristics,
and climate factors. This integration can result in a holistic Substructure Maintenance
Management (SuMM) program through which correct decisions on maintenance and
capital improvements can be made. The ORIMTM system has been used to help correlate
the substructure characteristics derived from GPR with these other condition indicators.
Geographical information systems tools and linearized, track-chart based tools, such as
ORIM, allow the viewing of the relationship of GPR to track condition and features, as
well as visualizing substructure effect on geometry trends and maintenance effort.

Another example of a BP Index condition index based on GPR information is depicted in
the ORIM screen grab in Figure 21. Figure 21 shows an integrated image showing two
parallel longitudinal GPR profiles along a 1.5 mile (2.4 km) section of heavy-tonnage
freight mainline. The images, shown with the digitized layer boundaries, indicate ballast
pockets that have developed in an embankment under the influence of heavy axle load
traffic. A Ballast Pocket Index was derived to indicate where the ballast pocket condition
has developed. Figure 21 shows the Ballast Pocket Index matched with the track layout
and track geometry data, and review of Figure 21 reveals that many of the geometry
rough spots are being driven by the ballast pocket problem. A common remedy to
minimize the continued development of the ballast pocket is to drain the ballast pocket
with a cross drain (essentially a ballast-filled trench) excavated perpendicular to the track.
GPR can delineate the bottom of the pockets to ensure that lateral drainage is put at the
most effective location (i.e., at the lowest point of the ballast pocket).

31


The extracted radar information is then analyzed with other available information, such
as assets, geometry, and work history to determine substructure conditions. The GPR
data, location information, and digital video were integrated together with track features,
milepost and offset, and track geometry data from TGMV using Optram, Inc.’s Right-of-
Way Infrastructure Management (ORIM) database and viewer. This integrated view of
conditions can then be used to define problem sites and to develop substructure indices
that are referenced to location along the track in a track chart view. The output can be
viewed in many ways, including GIS, track chart view, or exception report.


Drainage Pipes

150.00 feet 300.00
Jt (file 1611G) scans 18570

Figure 8. GPR Image of Access Road Along Track.

The scan in Figure 9 shows the varying thickness of ballast and subballast, which, in this
example, is an indication of a problem associated with lateral subballast spreading on top
of aclay subgrade. This spreading occurred because the clay surface softened to a
toothpaste consistency from the presence of water and the repeated train loading caused
the subballast to flow laterally.

High Ballast;12in

EN oe Ballast, 20in.

Subballast,.10in.

Clay.Subgrade

Figure 9. GPR Profile Showing Effects of Spreading Subballast.


4)

5)

6)

7)

8)

Completion of GPR data textural analysis processing to fouling index
automation.

- Requires further correlation of known textural analysis techniques on the
data with ballast fouling condition obtained from field investigations.

Automate QA/QC processing.

- Requires standardization and automation of current manual process.

Improve data management and archival storage systems.

- Requires applying known, robust information management techniques.

Automate layer detection and definition.
- The existing GRORADAR software used in this project has this
capability and must be fully automated.
Improve accuracy and reliability of position location system.

- Requires the purchase and integration of inertial guidance
instrumentation with existing hardware components.

36


Lists of Figures and Tables

Table of Contents

iii

Preface.

Summary

1. Introduction

2. GPR.
2.1 Applications .......ccecesseessesesseeseessesscsscsesssesscsnessssnessssessessessesesessssseessesnsaennes 3
2.2 PrInciples.......cecesssssssssssssesesesssesssessetescsceeseecscscneneacaesceescesecucasacssacscueseneeeseasseaeeeee 3
2.3 Data Processing..........cccccsscssssssssesessssssessssessssssssssecsssesesassessacseescaesessesesessesesseenees 5
24 — Data Modeling ...c.ccccccscssecsessesesseesesssssessessessessessssnesesessesssesessessssesseaseeseseeenees 6

3. GPR for Railroad Applications........c.cccsssssssssssssesseseeessenesesesssseseesesesneneneseeneseeneeeenes 10
3.1 Railroad Substructure Investigation..........sccsecsessessesseesesseessesseensesseenseessessse 10
3.2 Advantages and Limitations ...........ceseesesesssssessesseseesesesessestssecsreseeseeaneneenses 11
3.3. Equipment for Railroad Applications ...........cssesessssesresesesessesssssesseeseeneeseeseee 12
3.4 Project SUIVEYS ......c.sssesesssseeesessssessesessesssessessssseescsessescsesessssnensseensncseenceneneenenee 14
3.5 Example Results... eceseseesssessesseseseesesessesssneaceeenesesesecassnsscsessssesssecaeensneeeaees 16

4. Substructure Management Using GPR ..........sssssssessesssessssesessssssesssssssssesessscssesearenees 22
41 Track Substructure Condition .........csccssssessecsesseeseesesseeesessssesseeseeseeseesesseeneeneeee 22
4.2 Engineering SolUtions..0........ccscesesseeseeseeseeseesessesseeaeessesseseeseseeseeneesssereneeneee 24
4.3 GPR Substructure Indices........c.scessesseeseeseeseeseeseeseeseesseessessseneseeseeseensenesseeneeeeeee 25

5. Conclusions

6. Recommendations + 35

7. References. 37

8. Bibliography 38

9. Acronyms..

ii


on top of a clay subgrade (like Figure 9). The problem with the spreading subballast
shown in Figure 19 was prevalent throughout a 2-mile section of track. GPR data were
used to develop an index based on the relative thickness of the ballast and subballast
layers. The GPR Derived Layer Index in the middle of Figure 19 is the highest when the
subballast is thinnest and the ballast is correspondingly thickest. Conversely, the layer
index is low when the subballast and ballast are near their nominal thickness of
approximately 10 inches and 12 inches, respectively. The index is shown as a continuous
trace on the middle plot in Figure 18 and as a bar-code image in the bottom plot. The
bar-code image is derived by applying thresholds to the continuous layer index plot and is
a convenient way to view the extent of the problem for a particular section of track. The
dark bands in the bar-code image indicate areas where the subballast has thinned
considerably, and similarly, the lighter banding indicates less thinning. Remedial work
was planned based on the condition of the track as depicted by the bar-coded image.

Figure 20 depicts an example of a Ballast Pocket Index showing three parallel
longitudinal GPR profiles indicating ballast pockets that have developed in an
embankment under the influence of heavy axle load traffic. A ballast pocket is formed by
the greater load-induced settlement of the subgrade surface directly under the track. As
downward infiltrating water ponds in the depression that is created, the fill continues to
soften and further deformation occurs. As the track settles due to the fill deformation,
additional ballast is added and tamped under the ties to raise the track, resulting in a thick
ballast pocket. A common, simple remedy to minimize the continued development of the
ballast pocket is to drain the ballast pocket with a cross drain (essentially a ballast filled
trench) excavated perpendicular to the track. GPR can delineate the bottom of the
pockets to ensure that lateral drainage is put at the most effective location (i.e., at the
lowest point of the ballast pocket).

29


Table 1. List of GPR Surveys Performed During Project.

Location Distance Comments
(miles/km)

Initial GPR—single antenna pair. Data processed and used

Crawford, NE 10.4/16.6 for substructure assessment and remedial work planning.

Equipment testing and development along this mainline

Denver, CO 2.1/3.4 track in urban environment.

Equipment testing and development. Repeat survey at

Denver, CO 2.13.4 varying water content and freeze-thaw temperature.

Data processed and used for substructure assessment and
Sheridan, WY 4.3/6.9 remedial work planning for a section of track with poor
drainage and failing clay subgrade.

Data collected, processed, interpreted, and used for
Lindenwold, NJ 19.0/30.4 substructure remediation planning for third-rail electrified
transit line.

Data processing and interpretation of ground-coupled
antenna survey for concrete slabtrack. Report submitted

Pueblo, CO 2.0/3.2 to FRA. Air-coupled antenna data collected on TTCI’s
High Tonnage Loop.
Equipment testing and development. Repeat survey at
Denver, CO 2.13.4 varying water content and freeze-thaw temperature.
Sheridan, WY 4.3/6.9 Return visit to previously surveyed problem site to note
substructure changes.
Gillette, WY 37.0/59.2 Heavy-haul coal line with much coal fouled ballast. Data

processing and interpretation are on hold.

Heavy-haul coal line on highly plastic subgrade. Data

Neweastle, WY 29.8/47.7 processing and interpretation are on hold.

Heavy-haul coal line on highly plastic subgrade. Eight
Ardmore, SD 15.0/24 miles processed and interpreted and used for substructure
assessment.

Substructure survey for planning of line upgrade. Twelve

Jonesboro, AK 23.8/38.1 of 17 files processed through uniform trace spacing.

Survey of track sections with reoccurring subgrade
Hillsboro, ND 47.7/76.2 performance issues. Eight miles of automatic processing
complete. Four miles of enhanced complete.

Data processing and interpretation are on hold.
Grand Forks, ND 36.5/58.4

Total | 238.2/381.1

15



Figure 13 shows the variation in the ballast thickness at the two ends of the ties. The
ballast layer becomes thin at the center of the image. The bottom of the ballast layer is
above the bottom of the tie in the center of the lower image.

T
3300.00
scans 2091 a

Figure 13. Reduced Ballast Layer Thickness.

03 (file

21


Figure 7 shows an example of the subsurface conditions at highway grade crossings, as
detected by GPR. Trapped water immediately adjacent to the crossing is apparent by the
high amplitude reflections. The decrease in GPR reflection amplitude progressing away
from the crossing in the right side of Figure 7 correlates to decreasing water content of
the subballast and subgrade. The strong reflection from the surface of the reinforced-
concrete crossing planks momentarily reduced the signal amplitude from the subsurface
layer compared to the open track.

Figure 7. GPR Profile at Highway Grade Crossing.

The GPR profile in Figure 8 shows the access road along one side of the track. The
variable thickness of the gravel surface layer is clearly shown. Also shown are drainage
pipes from under the track installed in trenches dug into the road subgrade. The isolated
reflections beneath the gravel roadbed at 10 ns are from drainage pipes at approximate
depth of 2.1 ft (0.6 m). The breaks in the otherwise continuous reflection from the
bottom of the roadbed correlate with the pipes below.

17


Centerline
(middle of gage)

Eastside
of Track

Westside
of Track

z

q

é

3

é

3 |

i H |

8 i i
1200 1400 1600} 1800 1 2000 2200 2400
1 ! H 1
i | i 1

c v | i v
“Bar-Code” Index: | =

1200 1200 1800 1800 2000 7200 2200

MP + Feet

Figure 20. Subsurface Index Based on Depth of Ballast Pocket.

The banded image in the bottom of Figure 20 shows the depths of the subgrade surface
added together to accentuate the areas with the ballast pocket condition. Thresholds
applied to the Ballast Pocket Depth Index plot (middle of Figure 20) yields the color
coded bar scale plot in Figure 20. The bar-code depicts the worst areas (deep ballast
pockets) with dark banding and good areas with white.

30



provides information on the adequacy of the substructure’s strength to sustain traffic
loads. By mapping the thickness of ballast and subballast layers, GPR can expose areas
exhibiting subballast spreading, subgrade squeeze, subgrade attrition, and expansive clay
problems. GPR can also detect trapped water from poor drainage and distinguish fouled
ballast from clean ballast.

As with all subsurface investigation techniques, however, GPR does have some
limitations. For instance, substructure layer boundaries may not be detectable to GPR
under certain conditions, such as too little difference in electrical properties between the
two adjoining layers or boundaries producing high reflections that mask radar signals
from lower layers. The depth of radar penetration may be limited by such things as high
moisture content or wet conditions, highly conductive (salty or clayey) soils, or highly
metallic ballast components. GPR is also susceptible to interference from other radio
sources, especially in urban environments, which can mask subsurface returns.

3.3 Equipment for Railroad Applications

Antennas are used to transmit and receive the radar pulses. The transmitting and
receiving electronics are controlled by the GPR control unit, which also measures the
time and amplitude of the returned signals. GPR antennas are designed to operate at
various frequencies from tens of MHz to several GHz. The antenna’s operating frequency
must be considered for a given investigation. The antenna choice must take into account
the trade-off that exists between resolution and depth of penetration. The higher the
antenna frequency, the greater the resolution it exhibits; but higher frequency antennas
have less depth of penetration compared to lower frequency antennas. Lower frequency
antennas penetrate deeper than those at a higher frequency, but they have reduced
resolution.

A second consideration for antenna selection relates to how the antenna is deployed. The
two basic categories of antennas are air-coupled (air-launched) and ground-coupled
(Smith, 1995). Antennas that are air-coupled are designed to be used suspended above
the ground surface, with an air gap. Ground-coupled antennas are designed to be in
direct contact with the ground surface, with no air gap. Air-coupled antennas are
particularly suited to railroad substructure applications since they are suspended above
the ground and thereby allow high-speed measurement and clearance for turnouts, grade-
crossings, wayside detection devices and trash.

For the railway GPR development discussed in this report, three sets of GSSI 4208 1GHz
air-launched horn antenna pairs were used. These air-coupled antennas are designed to
work from 12 to 24 inches (30 to 60 cm) above the ground surface. A pair of antennas is
deployed outside each rail at the ends of the ties, and a third pair is positioned between
the rails along the centerline of the track. The system uses antenna polarization to
minimize interference clutter effects of the ties and running rails to produce a clearer
image of the substructure conditions. The antennas are supported on an adjustable frame
of high-strength fiberglass tubing that is mounted on a hi-rail vehicle, as shown in Figure
5.

12


medium mixing models were used to bound bulk density and water content manually
from the permittivity (Olhoeft et al., 2004). More than 200 miles (320 km) of data were
collected at sites representing a variety of subsurface conditions to demonstrate and
verify the radar techniques.

Follow-on phases have been planned to include installing the radar on hi-rail track
TGMV and use it to collect radar images routinely and to provide automating the
calculation of the depths, densities, and moisture contents of the substructure layers.


a typical track cross-section with deforming subgrade. The arrow dimensions indicate
the GPR antenna locations.

DATUM ____ L_ iL Cc R

Figure 17 Typical Track Cross-Section with Subgrade Deformation.

Figure 18 shows actual longitudinal scans for approximately 1000 ft (300 m) of track.
The distance from the datum to the top of the subgrade surface is indicated by the white

arrows. Locations A and B are where the subgrade soil has deformed upwards, creating a
situation similar to that shown in Figure 17.

Figure 18. Three Parallel GPR Profiles Showing Subgrade Deformation.

27


4.2 Engineering Solutions

GPR can be used for investigation of specific chronic problem locations and provide
information for diagnosing causes of problems at specific locations (e.g., ballast pockets,
soft clay) and for development of engineering solutions. GPR is very complimentary to
other investigation tools, such as cross-trenches and track stiffness measurements.

Figure 14 shows an example GPR survey result where GPR was used to investigate a
chronic problem spot near a pair of road grade-crossings. Figure 14 shows a typical
example of the subsurface conditions along three parallel longitudinal profiles at two road
grade-crossings, as detected by GPR. Trapped water immediately adjacent to the
crossings is apparent in the images. This water is trapped due to nonexistent lateral
drainage out of the track. The low point on the relatively impervious subgrade surface is
shown about 300 ft (100 m) to the left of the main road crossing. This information is
useful for the design of an effective drainage system that will improve the subsurface
condition and thereby solve a chronic maintenance problem. In this case, the GPR
indicates that the trapped water can be drained longitudinally away from the crossings to
a positive outlet point, as depicted on the bottom image in Figure 14.

Lateral

Drainage oad Read

Begins No Lateral Drainage 5 crossin
<< >< ‘away from track p< crossing > <ooesing,

Eastside
of Track

Trapped water
due (0 no Latoral &
Drainage

Centerline |
{olde of gagoy

Westside |
of Track

Low point in subgrade
& positive outlet point

Figure 14. Three Parallel, Longitudinal GPR Images near Two Road-Crossings.

24



Preface

This report presents the results of Phases 1 through 3 of a multiphase project to develop
Ground Penetrating Radar (GPR) for application in railway track substructure
assessment. These completed phases have significantly advanced the state of the art of
GPR data collection and interpretation in the railroad environment. The follow-on phases
will use the identified strategies to develop robust automated data interpretation and to
further investigate safety-compromising substructure track conditions.

This project was supported by staff from Ernest T. Selig, Inc. and Optram Inc., as well as
Don Heimmer of GeoRecovery Systems, Inc. The authors are grateful to Mr. Robert J.
Boileau of the Burlington Northern and Santa Fe Railway (BNSF) and Mr. Mahmood
Fateh of the Federal Railroad Administration (FRA), who served as the technical
monitors for their respective companies. Staff from BNSF were involved with field
activities and provided guidance on use. FRA and BNSF together provided about 80
percent of the project funding with much of the remaining funding coming from
equipment purchases by Gary Olhoeft and Don Heimmer. The authors are also grateful
to Dr. Ted Sussmann of the U.S. Department of Transportation Volpe National
Transportation System Center for his technical input and guidance, as well as useful
comments on the draft versions of this report.

iv


List of Figures

Figure 1. The Generation of a GPR Profile. .......ssssssssessesenssessesssseacsresserscaeseeneneaeneenenesees 4
Figure 2. Example of Full Waveform Modeling to Depth Determination... tees 7
Figure 3. GPR System Flow Diagram. .0.....c.ccssssesssssssesesssssessessesseseeseessssesnesenseaeceaneeness 9
Figure 4. GPR Image Example with Cross-Trenches for Calibration. ..........sccsessseseeeee 11
Figure 5. GPR Hi-Rail Setup with Three Pairs of 1-GHz Horn Antennas... 13
Figure 6. GPR Profiles Showing Sand Pocket and Shear Key. .......c:sccsssessessssseseesesseenee 16
Figure 7. GPR Profile at Highway Grade Crossing. .........scssscsssesseeseeseesseseesessessesseeseesessee 17
Figure 8. GPR Image of Access Road Along Track........sssssssssssssessesesessssesresesestsseenssesees 18
Figure 9. GPR Profile Showing Effects of Spreading Subballast...........ccsssessssseseeeeeees 18
Figure 10. GPR Profile Showing Ballast Pockets. ..........cscsssssssssessseseeseeseesessesesseesesseenee 19
Figure 11. Comparison of Images on the Two Sides and the Center of the Track
SUDStIUCTUTE. oo... eee ecssecsssessesesesessesesssssseessseessscssscsesssesecssseeneacenesssesusseeseeeenes 19
Figure 12. Deep V-Shaped Ballast Trench. Enhanced Closeup of Figure 11............00 20
Figure 13. Reduced Ballast Layer Thickness. ............:ssssssssssssssssssssesessesesessesessssesneaeansnees 21
Figure 14. Three Parallel, Longitudinal GPR Images near Two Road-Crossings............ 24
Figure 15. Example of Layer-Based Index of Longitudinal Layer Variation................+ 25
Figure 16. Subsurface Index Based on Ballast Pocket Condition. .........c:sssssssesseseeeeeeee 26

Figure 17. Typical Track Cross-Section with Subgrade Deformation.
Figure 18. Three Parallel GPR Profiles Showing Subgrade Deformation.
Figure 19. Subsurface Index Based on Thinning Subballast. .
Figure 20. Subsurface Index Based on Depth of Ballast Pocket.
Figure 21. Integrated View of Track Layout, GPR Image, Ballast Pocket Index and Track

Geometry Roughness. ..........ccsssessesessesssessssesseseseenssssssassessessesssssseeseseeeeseseeee 32

List of Tables
Table 1. List of GPR Surveys Performed During Project. ........ccccssseseseseeeseesseesetesseeeatenenenenees 15
Table 2. Substructure Problems and Corresponding GPR Measurement.........ccsesseeseseseeeeneee 23

iii


Figure 5. GPR Hi-Rail Setup with Three Pairs of 1-GHz Horn Antennas

The three antenna-pair arrangement permits three profiles to be collected at the same time
as the pairs of antennas are moved along the track. This provides three continuous
parallel longitudinal images along the track, providing information on the cross-track
variability.


1. Introduction

Track substructure (ballast, subballast, and subgrade) conditions have an important
influence in determining track performance, assessing the potential for service
interruptions, and needing to reduce train speed. A significant part of a railroad’s track
maintenance budget is driven by the rate of deterioration of track geometry. Rough track
is caused by movements in the substructure under repeated train loading. The
performance is significantly affected by moisture accumulation and thickness of the
roadbed layers (Selig and Waters, 1994). Thus the hidden and hard to monitor
substructure conditions are important to railway track performance.

GPR has the ability to map key railroad track substructure conditions quickly on a
continuous, top-of-rail, non-destructive basis (Olhoeft and Selig, 2002; Hyslip, et al.,
2003). This report describes work in which GPR was used to observe substructure
conditions, such as thickness of the ballast and subballast layers, variations in layer
thickness and condition along and across the track, pockets of water, and soft subgrade.
In addition, the GPR identifies locations and depths of subsurface drainage pipes,
trenches, and utilities.

For this development project the GPR antennas were located between the rails, as well as
at the ballast shoulders beyond the ends of the ties. The multiple-antenna configuration
provided measurement of the transverse, as well as longitudinal variation of the track
substructure. The radar equipment was mounted on a hi-rail vehicle, and surveys were
conducted continuously at speeds ranging from less than 2 mph to more than 25 mph (3
to 40 knv/hr). At 10 mph (16 km/hr) the radar resolution is a few inches horizontally (~7
cm) and a fraction of an inch vertically (< 1.0 cm), while depths of penetration of more
than 6 feet (2 m) were achieved. Future GPR systems of this type are anticipated to be
mounted on track geometry measurement vehicle (TGMV) for routine surveying during
track geometry data collection.

The GPR system for railroad use described herein has been developed in phases. The
first two phases used existing hardware to explore the capabilities of GPR for railway
track and established appropriate apparatus and procedures for collecting and processing
the radar data. The need for obtaining radar measurements at multiple positions across
the track to portray the three-dimensional nature of the substructure was determined. The
ability to model the radar data to determine estimates of water content of the substructure
materials was demonstrated. A variety of radar images were produced in Phase 2 (FRA
Contract No. DTFR53-01-P-00535) that illustrated the potential benefits of radar for
determining track subsurface conditions.

Phase 3 (FRA Contract No. DTFR53-02-P-00263) also used available radar equipment
mounted on a hi-rail vehicle. Multiple antenna configurations were established and
optimum configurations were determined. Measurement procedures were defined and
calibration procedures partly developed. Software was designed to process the radar data
automatically. Existing GPR modeling techniques for calculating complex dielectric
permittivity versus depth were demonstrated manually (Olhoeft, 1998, 2000). Effective


The profile in Figure 10 shows ballast pockets that have developed in the embankment
under the track. The ballast pockets are formed by failure of one side of the
embankment, which bulged outward allowing the ballast to settle.

Figure 10. GPR Profile Showing Ballast Pockets.

Figure 11 shows a V-shaped ditch that was dug perpendicular to the track in the bottom
image to drain trapped water from the track.

Wet spot

Figure 11. Comparison of Images on the Two Sides and the Center of the Track Substructure.

19


U.S. Department Ground Penetrating Radar for Railroad

of Transportation Track Substructure Evaluation
Federal Railroad
Administration

Office of Research and
Development
Washington, DC 20590

FRA/ORD-05/04 October 2005 This document is available to the
U.S. public through the National
Technical Information Service
Springfield, Virginia 22161


The dielectric permittivity and electrical conductivity are mostly independent. For
example, freshwater and saltwater have essentially the same dielectric permittivity (salt
water is slightly lower); however, saltwater exhibits a much higher electrical conductivity
than freshwater. GPR pulses travel at similar speeds through both types of water;
however, in saltwater the energy is attenuated very quickly and does not penetrate deeply.

As shown in Figure 1, reflections of the GPR pulse occur at boundaries in the subsurface
where changes occur in the material properties. Only a portion of the pulsed signal is
reflected and the remaining part of the pulse travels across the interface to again be
reflected back to the receiver from another interface boundary. The time the pulse takes
to travel through the layer and back is controlled by the thickness and electromagnetic
properties of the material. The travel time between upper and lower boundaries of a layer
can be used to calculate the layer thickness employing a known velocity.

2.3. Data Processing

To achieve the desired information in the railroad environment from the radar, the
collected data must be processed to:

1. Locate radar data position (e.g., tag the data with global positioning
system (GPS) coordinates, such as World Geodetic System 1984).

2. Verify accuracy of location using such things as digital video and U.S.
Geologic Survey (USGS) digital orthophoto quadrangle (DOQ) images.

3. Remove unwanted background and objects (e.g., the ties and rails).
4. Apply time-space and other filters to enhance desired image features.

Scale data plots for desired distance formats.

The steps of automatically processing GPR data from raw data with distortions to
geometrically correct images are known and straightforward. In this project, the data
acquisition process was standardized for uniform acquisition of GPR data (in terms of
procedures, time and relative amplitude calibration, antenna geometry, and polarization)
and location information. The location, or position, information was best accomplished
using wide area augmentation system, differential global positioning system (WAAS
DGPS). GPS, however, does not work everywhere, so backup positioning systems were
provided. The data processing then easily becomes automatic to correct for distortions
and common acquisition problems. With calibrated time and position, the GPR data can
use diffraction hyperbola and other velocity determination estimates to scale vertical axis
to produce geometrically correct image cross sections of the subsurface. This was
demonstrated in Phase 2 of this project. Also in Phase 2, the GPR antennas were
polarized and located to minimize the reflections from the rails.

Automation requires standardization, and the standardization of the data acquisition
process required gaining experience by collecting data in the field, thus reducing
problems that must be dealt with in later data processing. Examples would be how to


2. GPR

21 Applications

Since the early 1970s, GPR has been found to be useful in many areas of non-destructive
subsurface investigations (Olhoeft and Smith, 2000). Highway examinations using radar
have determined pavement layer thickness and deterioration, and extensive work has
been performed for bridge deck and scour evaluations. In environmental surveys, GPR is
useful in detecting underground storage tanks, buried drums, and debris, as well as
detecting other contamination not visible from the surface. Archeological and forensic
surveys have produced dramatic results. Radar has commonly been employed to detect
reinforcing steel, post-tension members, and conduits within concrete structures and
pavements, as well as identifying voids and loss of support beneath slabs. Geologic
investigations have profiled bedrock and the water table, while hydrologic studies have
examined lake, river, and subbottom features. GPR is also being used on railroad tracks
to provide continuous measurement of the condition of track substructure layers and
thereby provide information for maintenance and rehabilitation decision making. The
most successful applications are those exploiting the ability of GPR to produce high-
resolution images of the subsurface and to detect nonmetallic buried objects quickly,
continuously, and do not require direct material surface contact.

2.2 Principles

The GPR method transmits pulses of radio energy into the subsurface and receives the
returning pulses that have reflected off interfaces between materials with different
electromagnetic properties. It is a pulse-echo technique using radio energy as depicted in
the Figure 1. Antennas are moved across an area with a continuous series of radio pulses,
producing a distorted cross-section of the subsurface. The distortion is a function of the
geometry of the antenna position and orientation, as well as the velocity of the material
properties in the subsurface. Correcting for these parameters removes the distortion to
generate a true geometric cross-section image of the variations of electromagnetic
properties in the subsurface.


8. Bibliography

For more information, reference can be made to the following publications, most of
which were written during the project.

FRA Research Results, RRO2-03 (2002). “Ground Penetrating Radar for Railway Track
Substructure Investigation”. U.S. Department of Transportation, Federal Railroad
Administration, September 2002.

Selig, E.T., Hyslip, J.P., Olhoeft, G.R., and Smith, S. (2004). “Ground Penetrating Radar
for Track Substructure Evaluation, Phase 1-3,” Report to BNSF Railroad and Federal
Railroad Administration. March 1, 2004.

Selig, E.T., Hyslip, J.P., Olhoeft, G.R., and Smith, S. (2003). “Ground Penetrating Radar
for Track Substructure Condition Assessment”. Proceedings of Implementation of Heavy
Haul Technology for Network Efficiency, Dallas, TX, May, p. 6.27-6.33.

Smith, S. (2005). “As-Built Survey of Slab Track Using Ground Penetrating Radar at
Transportation Technology Center, Pueblo, CO”. Federal Railroad Administration,
Contract Number DTFR-53-02-P-00263.

Sussmann, T.R., Hyslip, J.P., and Selig, E.T. (2003). “Railway Tracks Condition
Indicators from Ground Penetrating Radar”. NDT&E International, 36, 157-167.

Sussmann, T.R., O’Hara, K.R., and Selig, E.T. (2002). “Development of Material
Properties for Railway Application of Ground Penetrating Radar,” Proceedings of
GPR2002, the 9th International Conference on Ground Penetrating Radar, Santa
Barbara, CA, pp.42-47.

Sussmann, T.R., O’Hara, K.R., Kutrubes, D., Heyns, F.J., and Selig, E.T. (2001).
“Development of Ground Penetrating Radar For Railway Infrastructure Condition
Detection,” Proceedings of the 2001 Symposium on the Application of Geophysics to
Engineering and Environmental Problems (SAGEEP), Denver, CO, March.

Sussmann, T.R., Heyns, F.J., and Selig, E.T. (1999). “Characterization of Track

Substructure Performance”. Recent Advances in the Characterization of Pavement
Geomaterials, Geotechnical Special Publication No. 89, ASCE.

38


GPR gray-scale image). These data were then converted to a continuous index
representing layer variation. The Layer Roughness Index in Figure 15 is simply
calculated as the moving standard deviation of the digitized bottom of the granular layer
over an average moving-window. This index is shown on the bottom plot in Figure 15.
The index is high on the left side of the plot where the subgrade surface elevation is
variable. The index is low on the right side of the plot where the subgrade surface is
relatively uniform.

A general index based on moisture content can be determined in the same manner.
Eventually, once the modeling development work is further along, the variation in ballast
layer fouling can be quantified in much the same way.

In Figure 16 an example of a more specific index, based on layer detection, is subgrade
layer depth variation for ballast pockets. Figure 20 presents an explanation of the
derivation of this index.

Ballast Pocket

~1 m Deep

x

3

3

£

€

Fa

a | _ ry

3 | Moderate

2 L —— ——— ——

38 i

2 YHigh

7

3

s

a ee)
1200 1400 1600 1800 2000 2200 2400

MP + Feet

Figure 16. Subsurface Index Based on Ballast Pocket Condition.

Other specific indices can be developed based on the lateral variation of layers. For
instance, the lateral variation of the subgrade surface across the track is indicative of poor
drainage due to bathtub condition and subgrade failure or deformation. Figure 17 shows

26


4.3 GPR Substructure Indices

The ability of GPR techniques to quickly collect quantitative information on track
substructure will make it an invaluable tool for substructure maintenance management.
GPR data is being used to develop indicators of substructure condition and performance
for wide-area planning and allocation of resources.

General indices of track substructure condition can be based simply on the longitudinal
and lateral variation of layers, water, and material properties. The longitudinal variation
of substructure layers often results in track stiffness variations, which translates into
rough track. Figure 15 presents an example of a general index based on longitudinal
variation of layers.

laid
5\3:8) 8/2) 2[s| Al4/y|s) ele|4|4| 214) slelaiz) |
Patco 2000 +2000 oo 0d 1000 2000 3090 40

Track
Layout

GPR
(Proc)

Layer
“Roughness”
Index

Figure 15. Example of Layer-Based Index of Longitudinal Layer Variation.

The GPR image in Figure 15 is an almost 2-mile (3.2-km) section of track. The distance
to the bottom of the granular layer was manually digitized (shown as white points on the

25


Summary

Ground Penetrating Radar (GPR) has been employed to assess railway track substructure
(ballast, subballast, and subgrade) conditions and to produce quantitative indices of
substructure condition for use in track maintenance management efforts. GPR involves
transmitting radar pulses into the substructure and measuring return signals that have
reflected off boundaries between substructure layers with different electromagnetic
properties. This report demonstrates uses of GPR to produce images and quantitative
indices of railroad track substructure condition quickly on a continuous non-destructive
basis.

The GPR equipment that has been developed in this project is mounted on a hi-rail
vehicle with clearance between the antennas and the track surface to permit continuous
measurements to be made along the track from above the top-of-rail at normal vehicle
speeds. Antennas are located at both ends of the ties, as well as in the center of the track,
so the variations of conditions are measured laterally across and longitudinally along the
track. The antenna configuration and surveying procedures have been optimized to
account for the radar-scattering influence of ties and rail.

The GPR data are processed to correct for location variations and to produce uniformly
spaced data. The data are also processed to remove unwanted background data,
principally from effects of ties and rails. After processing, modeling techniques have
been demonstrated to produce quantitative measures of substructure layer thickness and
water content. Observations from inspection trenches excavated under the track have
been used to gather soil properties and thickness information to compare with the radar
measurements to validate the effectiveness of the technique.

Indices of track substructure condition have been developed based on the GPR data. This
report presents some example indices that have been based on the longitudinal and lateral
variation of substructure layers, and the extent of ballast pocket development. GPR
provides a means to develop substructure indices based on layer contours, moisture
contents in the different substructure layers, amount of fouling in the ballast and the rate
of change of layer parameters.

More than 200 miles (320 km) of data were collected during this project at sites
representing a variety of subsurface conditions to demonstrate and verify the radar
techniques. The survey results show that the current GPR system is capable of observing
substructure conditions, such as thickness of the ballast and subballast layers, variations
in layer thickness and condition along and across the track, pockets of water, and soft
subgrade. In addition, locations and depths of subsurface drainage pipes, trenches, and
utilities can be identified. Further phases in the technology evolution include the
complete automation of data processing and interpretation, and continued surveying to
gain more experience in identifying safety-compromising substructure track conditions.


3.5. Example Results

Figures 6 through 13 are example results from GPR surveys conducted on railroad tracks
since 2001.

Figure 6 shows two GPR cross-section images that are from the same location, but
opposite sides of the track. The sand zone shown in the top scan acts as a water pocket,
and the trapped water in this pocket softens the surrounding clay subgrade causing track
geometry deterioration. The shear key in the bottom image was a previous attempt to
stabilize the soft subgrade by digging a drainage trench into the subgrade clay and filling
it with ballast. The extent of the shear key is well-defined by the increase in ballast
thickness and absence of the subballast layer.

Sand Zone t

in Clay “>,
\

Ballast
pi Ballast

Subballast

b.

Subgrade.

Figure 6. GPR Profiles Showing Sand Pocket and Shear Key.

16


These are a few examples of the track substructure indices currently being developed.
These simple indices will be refined to include weighting factors, combined with other
information, such as geometry and climate data. Indices can also be developed based on
changes in layer and water over time.

In general, indices can be based on processed data without modeling. Indices can also be
based on processed and modeled data. These indices would incorporate calculated water
content and other parameters, and could be used to develop more accurate composite
indices. Both of these types of indices possibilities are being considered.

Automated measurement and analysis techniques are being developed to produce
quantitative indices of track substructure condition that will enable improved cost
effectiveness of maintenance planning, increased safety, and reduced train service
interruptions. These indices will be based on such things as layer contours, moisture
content in the different substructure layers, amount of fouling material in the ballast, and
rate-of-change of layer parameters.

33


5. Conclusions

The following are conclusions regarding the present development status and the use of
GPR in the railroad environment. These conclusion have been determined as part of this
project.

1)

2)

3)

4)

5)

6)

7)

8)

GPR rapidly and non-destructively provides continuous, top-of-rail measurements
of substructure layer configuration and conditions.

Recording GPR data at three transverse locations across the track (both edges and
centerline) provides useful profiles of the track substructure that show variations
in conditions and depths along and across the track. Simultaneous recording at
multiple transverse locations reduces track occupancy needs and provides precise
correlation of the collected data streams.

GPR can provide quantified information on the thickness, as well as lateral and
longitudinal extent of substructure layers, as an indication of track performance.
GPR can obtain information on the adequacy of ballast and subballast thickness
and the presence and extent of deforming subgrade, as well as the variability of
substructure conditions longitudinally along the track.

GPR can determine the presence of trapped water in the substructure as high
amplitude reflections, as well as moisture content of substructure layers through
modeling.

GPR is capable of identifying locations and depths of subsurface drainage pipes,
trenches, and utilities.

GPR is useful for site-specific engineering investigations to determine the root
cause of specific problems and to develop engineering solutions at specific
locations.

GPR can be used to develop substructure condition indices. The condition indices
are needed to enable GPR to play a role in network-level planning and allocation
of a railroad’s maintenance and capital resources. For network-level planning, the
GPR information can be correlated with other measurements, such as track
geometry, features, track stiffness, and maintenance records to get complete
understanding of the track performance.

It is imperative to use air-coupled GPR antennas in railroad applications to
provide the necessary clearance to conduct railroad surveys at normal vehicle
speeds. The air-coupled GPR antennas that were used in this project are designed
to operate above the ground surface with a gap of at least 18 inches (0.5m).

34


4. Substructure Management Using GPR

41 Track Substructure Condition

Rough ballasted track is often caused by the poor condition of the track substructure
(ballast, subballast, and subgrade) under repeated train loading. The author’s experience
has indicated that the majority of track substructure problems in the United States are
associated with one or more of the following:

= Poor drainage of ballast, subballast, and subgrade, due primarily
to:
¢ Trapped water in ballast and subballast.
e Layer depression in impermeable subgrade.
= Fouled ballast (causing rapid loss of surface after maintenance).
=  Subgrade failure or deformation (from progressive shear or
excessive plastic deformation).
= Subgrade attrition (due to lack of subballast).
= Subgrade excessive swelling and shrinking (expansive clays).
Longitudinal variation of the condition and behavior of the track
substructure.
Transitions (causing loading and stiffness discontinuities).
Unstable embankments.
Inadequate amount of crib and shoulder ballast.
Sinkholes (karst and mining regions).

Indicators of these substructure problems are manifest in terms of one or more of the
following condition indicators of the ballast, subballast, and subgrade:

= Layer extent
= Water content
= Material Properties

The condition of the layers, in terms of thickness, lateral and longitudinal extent,
deformation with time, attest to such problems as a subgrade failure and deformation,
subgrade attrition, embankment instability, and sinkholes. The water content of the
substructure indicates poor drainage and can also attest to poor subgrade. Information on
material properties of the substructure can lead to conclusions on fouling condition,
ballast, and soil type.

GPR has the ability to map most of these key condition indicators quickly with a
continuous, top-of-rail survey. Table 2 presents the various substructure problems and
the corresponding GPR information that can be measured for use in defining the extent
and severity of the problems.

22


Abstract

This report presents the results of the first three phases of a multiphase project to adapt
Ground Penetrating Radar (GPR) to railroads for use in developing useful indices of
substructure condition and performance. The report includes brief discussions of some
basic GPR principles, as well as data processing and modeling techniques that are
applicable to railroad surveys. The railway GPR equipment is mounted on a hi-rail
vehicle and includes multiple sets of 1-GHz air-launched horn antennas suspended above
the track that permit fast survey travel speeds and high resolution measurements to a
depth of 3 to 6 ft (1 to 2m). The data from the multiple sets of antennas provide
transverse and longitudinal measurements of the track substructure. The report presents
example results from more than 200 miles (320 km) of surveys to demonstrate the
capabilities and applicability of GPR to assess railway track substructure (ballast,
subballast, and subgrade) conditions and to produce quantitative indices of railway track
substructure condition for use in track substructure maintenance management efforts.

KEYWORDS: Railroad, substructure, Ground Penetrating Radar, track maintenance,
ballast, subballast, subgrade, non-destructive testing.



Acronyms
DMI
DOQ
GPR
GPS
ORIM
SuMM
TGMV
USGS

WAAS DGPS

distance measuring instrument

digital orthophoto quadrangles

Ground Penetrating Radar

global positioning system

Optram, Inc.’s Right-of-way Infrastructure Management
Substructure Maintenance Management

track geometry measurement vehicle

United States Geological Survey

wide area augmentation system, differential global positioning system

39


uvavy ®

nd 42807
siao y yvAvy aedwo.>

JOMITA,
WwrRio

Aclsy]

“ueaseIg MOL Wayskg Yd *¢ 24N3Ly

INU VANAWWLESAGaa |

a VOY

soumeod Sd.
GOD [J] sr, dues

SOION Ply
oipny

sauna, oz\e9ur,

ody
uvava

doo

duegorpne

if $dd0

sdew yO
doa
sama,
saiey MUON UIeD
wOHISo4
- mised | be 1eoureo
a yeaysiaqqny,
: soSeumy fee} [eQ wontsog
Bulssooosg
uvave
sda ALL
aIMISIOW |e | jopow Boa sesn
indo

Saepow

ING
souvisiq,

Linx.

clock/trigger

Ez

Aw
Linx

=

(yy
AW a
3 Liwx c
I~

pO0T Ammnaqag saye
ainyoaryasy wiarség quaLin


‘ os wal) i.
AP Engine Sand, Moist Engine Sand & Ballast
wot wt IT sah Swit ale FAgaat) = own, Wet
ie aaahiaslil Sng ay

Figure 4. GPR Image Example with Cross-Trenches for Calibration.

3.2 Advantages and Limitations

Many advantages exist for the use of GPR on the railroads. Principally, GPR provides a
rapid, non-destructive, top-of-rail measurement technique of substructure layer conditions
with minimum interference to train operation. In this regard, GPR can be utilized as an
effective tool for exposing the root cause of reoccurring poor geometry and unstable
roadbed. GPR surveys can be collected on railroad tracks at vehicle travel speeds in
excess of 25 mph (40 km/hr), and the use of multiple antennas can provide variations in
substructure conditions across the track, which allows for this technique to be used on a
network-level basis to provide indices of track quality for utilization in inspections to
assess safety, maintenance, and operational constraints. The wide-area surveying ability
also provides the means to define sections of track that have similar conditions and
expected performance.

GPR provides the ability to measure layer thickness and, using the multiple antenna
configuration, can determine the amount of deformation and non-uniformity of
substructure layers. The lateral configuration of the substructure layers can attest to the
root cause of substructure problems. The ability of GPR to measure layer thickness also

11


Fe Al dd
REPORT DOCUMENTATION PAGE OMB No_ 0704-0188

Public reporting burden for this collection of information is estimated fo average 1 hour per response, including the lime for reviewing instructions, searching data sources,
‘gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection
Of information, including suggestions for reducing this burden to Washington Headquarters Service, Directorate for Information Operations and Reports,

1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget,
Paperwork Reduction Project (0704-0188) Washington, DC 20503,
PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS.

4. REPORT DATE (DD-MM-YYYY) 2. REPORT TYPE 3. DATES COVERED (From - To)
18-10-2005 Final Report April 2001—August 2004
4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER:

DTFRS53-05-P-00394

Ground Penetrating Radar for Railroad Track Substructure Evaluation Sb. GRANT NUMBER

5c. PROGRAM ELEMENT NUMBER

6. AUTHOR(S) 5d. PROJECT NUMBER

in). (2) ith iol)
J.P. Hyslip’, GR. Olhoeft”, S.S. Smith, E.T. Selig’ SoTASIKNUNEER

5f. WORK UNIT NUMBER

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION
© Emest T. Selig, Inc. © Consultant/Scientist © GeoRecovery Systems, Inc REPORT NUMBER
105 Middle St. 1950 Mt. Zion Drive 425 Violet St.
Hadley, MA 01035 Golden, CO 80401 Golden, CO 80401
9, SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S)

U.S. Department of Transportation
Federal Railroad Administration

Office of Research and Development 11. SPONSORING/MONITORING
1120 Vermont Avenue NW AGENCY REPORT NUMBER
Washington, DC 20590

12. DISTRIBUTION AVAILABILITY STATEMENT
This document is available to the public through the National Technical Information Service, Springfield, VA 22161.

13. SUPPLEMENTARY NOTES.

44. ABSTRACT

This report presents the results of the first three phases of a multiphase project to adapt Ground Penetrating Radar (GPR) to railroads
for use in developing useful indices of substructure condition and performance. Included are brief discussions of some basic GPR
principles, as well as data processing and modeling techniques that are applicable to railroad surveys. The railway GPR equipment
is mounted on a hi-rail vehicle and includes multiple sets of 1-GHz air-launched hom antennas suspended above the track that permit
fast survey travel speeds and high resolution measurements to a depth of 1 to 2m. The multiple sets of antennas provide transverse
and longitudinal measurements of the track substructure. This report presents example results from more than 200 miles (320 km) of
surveys to demonstrate the capabilities and applicability of GPR to assess railway track substructure (ballast, subballast, and
subgrade) conditions and to produce quantitative indices of railway track substructure condition for use in track substructure
maintenance management efforts.

45. SUBJECT TERMS

Railroad, substructure, ground penetrating radar, track maintenance, ballast, subballast, subgrade, non-destructive testing

416. SECURITY CLASSIFICATION OF: 17. LIMITATION OF | 18. NUMBER 19a. NAME OF RESPONSIBLE PERSON
ABSTRACT OF PAGES James P. Hyslip
48
‘a. REPORT b. ABSTRACT | c. THIS PAGE UU 19b. TELEPONE NUMBER (Include area code)
Unclassified | Unclassified } Unclassified 413-268-8700

Standard Form 298 (Rev. 8-98)
Prescribed by ANSI-Std 239-18


ce

“ssouysnoy Asjawioay yous | pue xapuy 304904 Iseleg ‘adewy] YD WModvy yous Jo mata payessaquy [7 aans1y

is Tape ssn 1A QUMO} Ww abe) ay sez1ORU EHF xe dine wee
4 Re Q]
$0
ro
ow
add
0
xepul
dg Buidojaasg
for ul asn 405 saahe7
pazii6ig yy -
sebew| Yd5
0
nog
£0 do
zO

XOPU| }9490d
yseyeg

\ y S|

sa) uutinoes

uns-es
109

ssauybnoy
Auyawioag yore,

HL

= ae
TTM~ noke7 ainyeay

lee 7 r T T rT r r : F 2 a 9 0e1]

‘OS oor Ouse 00E Ose one cost oor os
004 + dN
= [= falelel= t1s [el+lo 14 leis|e1¢ [ele fale elels

op ax

Ci ence)
x [ST



The top and bottom profiles in Figure 11 show data from outside the edge of ties (north
and south side of track, respectively), while the middle profile shows data along the
center of the track. The center image shows a greatly reduced ditch depth, and the top
image shows a wet spot on the opposite side of the track from a deep V-drain. Using an
estimated ballast dielectric permittivity from the radar travel time to the bottom of the V-
shaped ditch, the ditch depth was estimated at 4.7 ft (1.4 m). The image of the bottom of
the ditch is brighter than the ballast/subballast boundary, which indicated that the bottom
of the ditch is wetter. The north side (top image in Figure 11) of the wet spot has the
texture and periodicity corresponding to the tie spacing. Excavation of a similar image in
another location showed this pattern to be caused by extrusion and fingering of the
subgrade clays under the repeated loading of the passing trains. Figure 12 shows a larger,
enhanced version of the bottom image in Figure 11.

Ballast

NNOBR A Nt Ly PDR

Fouled Bavast
(Qld: Roadbed)

Subballast

Clay Fill

Figure 12. Deep V-Shaped Ballast Trench. Enhanced Closeup of Figure 11.

20


NOTICE

This document is disseminated under the sponsorship of
the Department of Transportation in the interest of
information exchange. The United States Government
assumes no liability for its contents or use thereof



One approach to developing meaningful substructure indices based on GPR requires
matching the information from the GPR measurements to known characteristics of
different types of substructure problems and then quantifying the GPR data to depict
these characteristics. Figure 19 shows an example of this approach.

GPR Scan:

=

Ballast

Condition Index:

GPR Derived Layer Index

ooo 2000 +«3000~«4000 «sooo «6000 ——Tooa~—«000«=«9000-—«10000
“Bar-Code” Index:

incon

yo00 2000-3000 «4000 coo 7000-8000 10000
Distance from MPxx

— High Index
Moderate Index

Figure 19. Subsurface Index Based on Thinning Subballast.

Figure 19 shows a GPR scan with varying thickness of ballast and subballast which, in
this example, are an indication of a problem associated with lateral subballast spreading

28


7. References

Hyslip, J.P., Smith, S.S., Olhoeft, G.R., and Selig, E.T. (2003). “Assessment of Railway
Track Substructure Conditions Using Ground Penetrating Radar.” Proceedings of the
2003 Annual Conference of the American Railway Engineering and Maintenance-of-
Way Association (AREMA), Chicago, October.

Hyslip, J.P. and McCarthy, B.M. (2000). “Substructure Investigation and Remediation
for High Tonnage Freight Line.” Proceedings of the 2003 Annual Conference of the
American Railway Engineering and Maintenance-of-Way Association (AREMA), Dallas,
TX, September.

Olhoeft, G.R., (2000). “Maximizing the Information Return from Ground Penetrating
Radar.” Journal of Applied Geophysics, v. 43/2-4, p. 175-187.

Olhoeft, G.R. (1998). “GRORADARTM: Acquisition, Processing, Modeling, and Display
of Ground Penetrating Radar Data: Ver. 4.0.” Software distributed on CD-ROM at
GPR98, 7th International Conference On Ground Penetrating Radar, University of
Kansas, Lawrence, KS, May.

Olhoeft, G.R. and Selig, E.T. (2002). “Ground Penetrating Radar Evaluation of Railroad
Track Substructure Conditions.” Proceedings of GPR2002, the 9th International
Conference on Ground Penetrating Radar, Santa Barbara, CA, S.K. Koppenjan and H.
Lee, eds., Proceedings of SPIE vol. 4758, pp. 48-53, April.

Olhoeft, G.R., Smith Il, S., Hyslip, J.P. and Selig, E.T. (2004). “GPR in Railroad
Investigations.” Proceedings of GPR2004, the 10th International Conference On Ground
Penetrating Radar, 21-24, Delft, The Netherlands, p.635-638, June.

Olhoeft, G.R. and Smith II, S.S. (2000). “Automated Processing and Modeling of GPR
Data for Pavement Thickness and Properties.” Proceedings of GPR2000, the 8th
International Conference on Ground Penetrating Radar, Gold Coast, Australia, D.A.
Noon, G.F. Stickley, and D. Longstaff, eds., SPIE vol. 4084, p.188-193, May.

Selig, E.T. (1997). “Substructure Maintenance Management”. Proceedings 6th
International Heavy Haul Railway Conference, International Heavy Haul Association,
Cape Town, South Africa, April.

Selig, E.T. and Waters, J.M. (1994). Track Geotechnology and Substructure
Management. Thomas Telford Ltd., London.

Smith II, S.S. (1995). “Detecting Pavement Deterioration with Subsurface Interface
Radar.” Sensors, vol.12, no. 9, p.29-40.

37


Table 2. Substructure Problems and Corresponding GPR Measurement.

Substructure Problem

GPR Information Based On

Poor drainage-trapped
water

Intensity of GPR reflection and moisture contents of
ballast/subballast layers.

Poor drainage — layer

Difference in depth to impermeable subgrade surface
laterally across the track (i.e., lateral layer thickness

depression (bathtub) variation).
Fouled ballast GPR scattering pattern textures and permittivity of ballast
layer.
Ratio of layer thickness and/or subgrade surface depth
Subgrade failure or from middle to edge of tie. Also, moisture content and
deformation consistency of subgrade soil along with thickness of
granular layer.
Subgrade attrition Lack of subballast layer in combination with fine-grained

fouling.

Subgrade excessive
swelling and shrinking

Variation of clay subgrade surface. Also, moisture
content and consistency of subgrade soil.

Longitudinal variation of
the condition

Variation (roughness) of layer thickness, moisture content
and composition.

Subballast moving
laterally on thin clay
surface

Change in layer thickness laterally across the track and
presence of high moisture content layer.

Transitions

Rate of variation of the substructure layers along or
across track of layer properties.

Unstable embankments

Typically, the present GPR system is not applicable due
to shallow penetration (<2m). Some indication of
shallow manifestation of layer deformation may be
possible.

Inadequate crib and
shoulder ballast

This can be performed without GPR by inspection of
ballast surface (or by using the digital video acquired with
the GPR).

23



recognize and handle radio frequency interference problems caused by railroad
communications and other sources appearing in the GPR data, how to acquire accurate
location information where the GPS does not work (e.g., high radio frequency noise
areas, tunnels), how to recognize and flag places where GPR does not work (i.e., no
penetration through clay layers, metal, highly conductive salt zones, or from too much
clutter), and other unanticipated issues.

Once GPR data are processed to geometrically correct image cross-sections of the track
substructure, then image processing and texture, morphological or pattern recognition
algorithms can be applied to automatically enhance, detect, and extract geometric
features of interest. Examples of these features include detection and mapping of ballast
and other layer thickness, location of abrupt thickness changes (such as a shear key),
location of material changes (such as type of ballast), location of utilities (such as cable
and pipe crossings), or location of drainage features.

2.4 Data Modeling

Modeling produces quantitative values for dielectric permittivity and depth. Once
obtained, dielectric permittivity can subsequently be modeled into water content and
density. Modeling requires radar system calibration for recorded signal time and absolute
amplitude. Providing automatic modeling is desirable to derive dielectric properties and
then extract density and water content information (Olhoeft and Smith, 2000). Once the
absolute amplitude calibration procedure is available, the automatic modeling becomes
straightforward and is currently performed automatically for concrete and asphalt
highway surveys (Olhoeft, 2000). However, the railway situation is more complicated
than highways. Highways have a flat, smooth, horizontal surface that is easily calibrated
for absolute amplitude while railway ballast is coarse gravel with a slope and surface
roughness comparable to the scale of the 1 GHz wavelength. Thus the smooth surface
calibration assumptions and procedures do not work. An absolute amplitude calibration
procedure using multiple antenna geometries, polarizations, and/or frequencies will be
required to be developed to provide automatic modeling of railroad GPR data.

GPR data in this study were modeled by matching simulated radar pulses to the measured
radar pulses. Figure 2 presents an example of full waveform modeling through to depth
determination and validation by trenching (from Olhoeft et al., 2004). The bottom right-
hand image in Figure 2 is raw, unprocessed GPR data. A single scan is selected from this
data for modeling after digital video certifies the antenna field of view is clear.
GRORADAR (Olhoeft, 1998) uses full waveform modeling to produce electromagnetic
material properties, which turn time into depth. The modeling results were validated
using the results from cross-trenches dug along the track, which are shown in the top
portion of Figure 2.


3. GPR for Railroad Applications

3.1 Railroad Substructure Investigation

Appropriate tools for field investigation of railway substructure problems include cross-
trenches, cone penetrometer tests, test borings, characterization of track geometry data
and deterioration trends, track stiffness measurements, and GPR (Selig, 1997; Hyslip and
McCarthy, 2000). GPR surveying provides a continuous survey and characterization of
the track substructure, quickly locating areas of potential trouble for further investigation
or maintenance. GPR has the ability to provide a rapid, non-destructive measurement
technique for evaluating these key substructure condition indicators (Olhoeft and Selig,
2002) and can be used to provide numerical data for development of substructure
condition indices (Hyslip, et al., 2003).

Material and moisture variation within the track substructure causes distinct material
differences that are easily recognized by GPR. Water possesses a high dielectric
permittivity compared to the other materials typically found in the substructure and
produces a strong effect on the GPR profiles. In an area where water has been trapped in
the substructure, the dielectric permittivity is increased, resulting in increased two-way
travel time and a stronger reflection than if it were drier. The texture of the radar record
allows the relatively coarse-grained ballast layer to be recognizable from the
comparatively finer-grained subballast layers, and the texture allows fouled ballast to be
distinguished from clean. In the case of fouled ballast, the normal layering is disrupted
by fine-grained materials in the otherwise coarse-grained matrix. By quantifying the
GPR scattering pattern textures, determinations can be made regarding the amount of
fouling in the ballast layer.

To verify and calibrate the railway GPR data, it is currently necessary to excavate cross-
trenches (inspection trenches) in locations with key substructure conditions to correlate
the actual conditions with the radar data. Figure 4 shows a typical GPR image example
along a 500 ft (150 m) section of track. Figure 4 also shows photos of the cross-trenches
that were excavated and logged for calibration of the GPR data. Depths to key
substructure layers are measured in the cross-trenches and used with travel times from the
radar data to determine average velocities. The velocities are use to calculate the material
properties values, such as dielectric permittivity.

Once enough GPR data has been calibrated with inspection trench information, the need
for inspection trenches will diminish from what is presently required. Eventually quick
assessments of subsurface conditions over large distances will be made with minimal
invasive cross-trenching.

10