Eyeing the surface

New Jersey DOT tests new methods to detect gradation segregation

Asphalt Article April 18, 2003
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Segregation may be defined as lack of homogeneity of
constituents in hot-mix asphalt (HMA) pavements such that accelerated pavement
distresses occur. The most common form of HMA segregation has been identified
as gradation segregation. Gradation segregation is the non-uniform distribution
of coarse and fine aggregate materials in the finished HMA pavements. Gradation
segregation can occur as the result of aggregate stockpiling and handling,
production, storage, truck loading practices, construction practices and
equipment adjustments.

Localized pavement areas rich in coarse aggregate are
typically associated with high air voids and low asphalt contents; these
conditions can lead to moisture damage as well as to durability-related
pavement distresses such as fatigue cracking, pothole formation and raveling.

Conversely, pavement areas rich in fine aggregate are associated
with low air voids and high asphalt contents, making them susceptible to
rutting and flushing.

The correlation between air voids and pavement durability
is well documented. In New Jersey, some projects have experienced high air
voids and segregation of the surface mixes due to poor construction practice or
equipment problems. Hence by establishing a relationship between surface
texture measurements, surface segregation and air voids, the New Jersey
Department of Transportation (NJDOT) wanted to establish a screening tool to
identify variations in surface texture that are typical of segregation and
potentially locate pavement sections with high air void content.

style='font-size:12.0pt;font-family:Times'>A research team consisting of the
New Jersey Institute of Technology, Abatech Inc. and the NJDOT conducted an
extensive research program. Available technologies were evaluated to develop a
screening tool for assessing surface texture as a means of locating segregated
areas of the surface pavement and potentially high air void locations. The work
described here was specifically focused on the use of laser technology to
develop procedures or screening tools to determine segregated areas.

Low tech, high tech

There are several traditional and emerging methods to detect
and quantify texture so that quality control/quality assurance program can be
built on to the design and construction of HMA pavements. The following is a
description of those methods.

The
traditionals
: There are three commonly used methods to detect segregation. They are
visual identification, sand patch testing, and nuclear density gauges.

Visual
identification:
Visual identification of non-uniform surface texture has
been used to locate segregation. This is a subjective approach which can lead
to disagreements between agency and representatives of the contractor. Usually
visual detection of non-uniform areas is used as the baseline against other
quantitative approaches.

Sand
patch testing
: The sand patch test has been used to quantify visual observations of
differences in the surface macro-texture. The ASTM E965 test method (ASTM 2001)
indicates that the precision of the test method is approximately 1% of the
measured depth in millimeters and the between operator variation is about 2%.

Nuclear
density gauges
: Nuclear density gauges can be used to identify segregated
areas by profiling the longitudinal density of the pavement mats. The
assumption is that segregation will be seen as low density. However, literature
indicates limited success. There are two reasons for the erratic success.
First, the common assumption for using these gauges is that density decreases
with increasingly coarse aggregate segregation. However, this assumption does
not consider the relationship of the gradation to the maximum density line. If
the job mix formula (JMF) begins above this line, separation of the coarse
aggregate in this type of mix may result in a higher density as the gradation
shift towards the maximum density line. Second, different types of aggregates
have different effects on gauge variability. Limestone, a commonly used
aggregate source, substantially increases testing variability. Gravel, on the
other hand, have much less of an effect on variability. If a mixture is
composed of coarse limestone and fine gravel stockpiles, the resulting change
in testing variability in coarse aggregate-rich and fine aggregate-rich areas
may make it difficult to adequately detect or measure segregation.

The
innovations
: Three new technologies have been identified as having potential to selectively
identify HMA segregation. They are thermal imaging, ground penetrating radar
and laser surface texture measurements.

Thermal imaging: All objects emit infrared radiation in
the form of heat, which can be detected by an infrared scanner. These natural
impulses are converted into electrical pulses and then processed to create a
visual image of the object's thermal energy. The colors used to represent the
thermal imaging can be user-selected to represent surface temperature changes,
such as blue for colder regions and red for warmer regions. The thermal imaging
technology will indicate high void regions, as thermal capacity of air is
minimal when compared to that of aggregates and asphalt cements. If one
assumes, high segregation causes high void ratios then the technology can be
easily adopted to detect segregation.

The primary component of any thermal
imaging system is an optical scanner, a unit that is used to detect infrared
radiation from an object. Other essential components of the system are a
display monitor, video camera and computer with appropriate software for data
acquisition, analysis and storage.

A full-lane width can be surveyed at one
time with an appropriately placed camera. Usually liquid-nitrogen-cooled
scanners provide improved resolution over other methods of cooling. Although
current technology is vehicle-mounted, operation at highway speeds (50 mph)
tends to blur the image. Resolution is improved substantially by operating the
equipment at slower speeds (40 mph).

Ground penetrating radar (GPR): style='font-size:12.0pt;font-family:Times;font-weight:normal'> The basic theory
used in GPR is a measurement of the dielectric constant, E, (or permittivity).
The electrical permittivity of air is different from that of aggregate and
asphalt cement. Hence in highway applications, the travel time of an
electromagnetic pulse through a structure can be used to compute the layer
thickness.

Continuous longitudinal surface texture
profiles can be obtained quickly because the technology can be operated at
normal highway speeds. However, slower speeds are needed for higher resolution.
The equipment is portable and reasonably affordable and can be mounted to any
vehicle.

Laser surface texture measurements style='font-size:12.0pt;font-family:Times;font-weight:normal'>: name="_Toc161149">Over the past 20 years the use of laser technology to define
surface texture has been gaining wide popularity. The technology uses a rapidly
pulsing semiconductor laser to produce an infrared light that is projected onto
the pavement surface. The light is scattered off of the surface and a receiving
lens focuses this scattered light onto a linear array of photodiodes. The diode
receiving the most light corresponds to the distance to the surface. Using
mathematical algorithms the distance to the surface at a discrete point is
obtained. The measurements are conducted very rapidly as the vehicle drives along
the pavement enabling measurements at points that can be typically separated by
1mm defining a surface profile.

Based on the subjectivity of measurements, if the visual
observation is eliminated, sand patch and laser methods are the most
appropriate methods to quantify the segregation based on surface texture. It
seems that out of the three emerging technologies discussed above, the laser
technology is quite capable of quantifying the surface texture and hence the
detection segregation of HMA pavements.

Table 2: Comparison of Surface Texture Measuring
technologies



Test

Method


Type of Mix


Depth of measurement


Fine

Gradations


Dense

Gradations


SMA


[if !supportEmptyParas] [endif] style='font-size:12.0pt;font-family:Times;font-weight:normal'>


Surface

Only


Depth of Life


Full AC

Mat Depth


Visual Observe


Yes


Yes


Yes


[if !supportEmptyParas] [endif] style='font-size:12.0pt;font-family:Times;font-weight:normal'>


Yes


No


No


Sand Patch


Yes


Yes


Yes


[if !supportEmptyParas] [endif] style='font-size:12.0pt;font-family:Times;font-weight:normal'>


Yes


Yes


No


Nuclear

Density


Gradation

Dependent


Gradation

Dependent


Yes


[if !supportEmptyParas] [endif] style='font-size:12.0pt;font-family:Times;font-weight:normal'>


No


Yes


No


Laser


Yes


Yes


Yes


[if !supportEmptyParas] [endif] style='font-size:12.0pt;font-family:Times;font-weight:normal'>


Yes


No

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