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Funding shortages create pavement preservation challenges for state departments of transportation (DOTs). The Georgia DOT developed an innovative micromilling resurfacing method as a cost-effective way to preserve its pavements. The new method can save more than $5 million on an I-95 project of 84 lane miles. To ensure that the micromilled surface texture has a good bond and good runoff capability, the Georgia DOT established a stringent ridge-to-valley-depth (RVD) specification. Preliminary tests were conducted on an I-75 project with a circular track meter and an ultralight inertia profiler, but the RVD was first measured with a laser road profiler for the entire 84 lane miles of the I-95 project. The rough and smooth micromilled pavement surfaces have been studied and compared through an exploration of their statistical characteristics and patterns. Results from four 0.5-mi segments showed that both smooth and rough surface textures revealed normal distributions, although a smooth surface had a slight lognormal distribution. The smooth surface had a mean of about 2.5 mm and a standard deviation of 0.9 mm. The rough surface had a mean of about 4.6 mm and a standard deviation of about 1.1 mm. The cumulative percentage curves for both rough and smooth surface textures showed that the mean RVD value of 3.2 mm could effectively differentiate rough and smooth surfaces. The effects of different base lengths on the RVD were studied, and results showed that a 100-mm base length was adequate to differentiate between smooth and rough surfaces.

Damage mechanisms that lead to stripping significantly affect the dynamic modulus and tensile strength of hot-mix asphalt (HMA). When stripped HMA is unexpectedly encountered below the planned milling depth during routine mill and overlay rehabilitation projects, it must be removed and replaced; this causes significant cost overruns and delays. A procedure was developed to identify the extent and depth of stripping in in-place HMA pavement sections. Several nondestructive survey methods were analyzed to determine their capability to locate areas of stripping, either by themselves or in various combinations. Cores were extracted and used to calibrate the methods. Visual inspections of the cores and laboratory tests on selected cores were used to validate the results. The procedure involved observation of surface distresses, complete ground penetrating radar survey, seismic testing of selected areas, limited coring, and laboratory testing of selected cores. With these procedures, areas with stripping can be distinguished so that effective rehabilitation strategies can be developed.

Faulting is one of the three performance measures recognized by the Code of Federal Regulations (CFR) for jointed concrete pavements. U.S. Federal Highway Administration rules developed for the CFR require the state Departments of Transportation to use the AASHTO Standard R 36, Standard Method for Evaluating Faulting of Concrete Pavements, for measurement of faulting. R 36 allows both manual testing using a faultmeter and automatic testing using a high-speed inertial profiler (HSIP). There is a concern in the literature that the HSIP methods are not accurate enough for network level testing of faulting. Recent studies have also shown that three-dimensional (3-D) laser technology is showing promise for providing more accurate faulting measurements. Still, there currently is not a specific method in R 36 that utilizes 3-D data for gathering faulting measurements. This paper proposes a new method that takes full advantage of the full-coverage capabilities of 3-D to measure faulting more accurately and consistently. This method uses the comparison of smoothed areas on both sides of a joint instead of a single longitudinal profile to measure elevation differences. Field tests were performed to compare the 3-D method with manual readings taken with a Georgia faultmeter on two sections of interstate in Georgia. In addition, the impact of various footprints and measuring locations of faulting measurements using this 3-D technology were quantitatively evaluated using the proposed method. Based on this case study the new proposed 3-D method appears to be appropriate to be considered to be added as a 3-D automatic method in AASHTO R 36.

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