State highway agencies (SHAs) are required by Federal Highway Administration (FHWA) to develop Transportation Asset Management Plans (TAMP) in which the performance targets for roadway assets are determined. FHWA also developed national performance metrics to use in determining performance targets for pavements. However, for pavement assets, most SHAs employ their own performance metrics for pavement condition data reporting and performing maintenance and rehabilitation (M&R) analysis. Therefore, there is a need to incorporate national performance measures into SHAs' pavement management system to support the development of TAMP. In this study, new pavement performance metrics were proposed to assist SHAs in conducting M&R analysis. The relationships between the new metrics and existing pavement metrics used in the State of Tennessee were investigated. Comparison between the new metrics and the State's metrics was made with reference to network-level condition summary and performance prediction models. Results indicated that the new performance metrics appeared to be stable and less sensitive to sectioning method. Similar time-series patterns of network-level performance deterioration were found between the State's metrics and the new metrics. It is recommended that performance models be established based on the new metrics, as the deterioration rates from the two metrics were not well correlated.

Surface cracking is a major type of pavement distress that is of interest to pavement engineers. Cracks are generally categorized in relation to patterns, orientations, and locations. Each type of crack is associated with one or more failure modes of pavements. Accurately detecting and rating surface cracks is crucial in pavement condition surveying. Currently, many State Highway Agencies employ automated survey methods to collect pavement condition data at network level. As network-level pavement evaluation is based on a single run, the traditional way of characterizing data variation based on multiple runs is no longer valid. Therefore, it is necessary to introduce a new method to evaluate the variability of pavement condition data at the network level. In this study, the variability of network-level surface crack data was evaluated by means of network-level sample parallel tests. The parallel test was conducted from 2018 to 2020 using two vehicles equipped with identical automated survey systems which consisted of a 3-D imaging system and automated distress identification system. A matrix-based method was proposed to evaluate the variations of crack data obtained from two testing vehicles. Crack data investigated in this study included fatigue cracks, longitudinal wheel-path and non-wheel-path cracks, and transverse cracks. Results indicated that change of testing speed could potentially influence the variation of automated crack data. The variations between severity levels for fatigue cracking were higher than other types of cracks. The variation of crack data decreased with the increase of reporting intervals.

The use of pavement condition data to support maintenance and resurfacing strategies and justify budget needs becomes more crucial as more data-driven approaches are being used by the state highway agencies (SHAs). Therefore, it is important to understand and thus evaluate the influence of data variability on pavement management activities. However, owing to a huge amount of data collected annually, it is a challenge for SHAs to evaluate the influence of data collection variability on network-level pavement evaluation. In this paper, network-level parallel tests were employed to evaluate data collection variability. Based on the data sets from the parallel tests, classification models were constructed to identify the segments that were subject to inconsistent rating resulting from data collection variability. These models were then used to evaluate the influence of data variability on pavement evaluation. The results indicated that the variability of longitudinal cracks was influenced by longitudinal lane joints, lateral wandering, and lane measurement zones. The influence of data variability on condition evaluation for state routes was more significant than that for interstates. However, high variability of individual metrics may not necessarily lead to high variability of combined metrics.

Structural condition data is one of the critical data elements in pavement design and management for determining the needs of pavements rehabilitation. However, it is time-consuming and may raise safety concerns to use Falling Weight Deflectometer (FWD) for collecting pavement structure data at network-level. The traffic-speed deflection device seems to be a promising way to collect network-level structural capacity information in a safe and timely manner. To better understand the deflection collected from traffic-speed deflection devices, this paper focused on the influence of pavement data on deflection measurements. The pavement data in this study included pavement structure and surface condition data. The associations between deflection and pavement data was assessed by non-parametric rank correlation analysis. The pavement data elements that may influence deflection measurement were identified by random forest regression models. The relationship between deflection indices and surface condition indices were quantified by Tukey's HSD test. Results indicated that D-0 and SCI appeared to be more influenced by pavement type, surface roughness and distress than SCI of subgrade. IRI on the right wheel path tended to be more closely associated with SCI than other surface condition data. The change of surface condition indices appeared to be more sensitive to deflection indices on flexible pavements than on composite pavements. (C) 2020 Elsevier Ltd. All rights reserved.

Open-graded friction course (OGFC), also called permeable friction course (PFC), is a thin and permeable asphalt concrete whose skeleton is composed mainly of coarse aggregate, leading to an immediate drainage of water and an adequate frictional resistance, thus reducing traffic accidents and improving driving environments on rainy days. However, high porosity and open aggregate structures may readily contribute to stripping and raveling of OGFC. Application of fog seal on slightly cracked and/or raveled OGFC is one preventive measure to extend its service life. This study quantitively examined the influence of fog-seal application on the OGFC's behavior, such as water permeability, skid resistance, and raveling susceptibility. Laboratory tests, including the permeability test, texture depth test, and loaded wheel abrasion test, were conducted on samples obtained from the lane and shoulder in a section of OGFC pavement. Results demonstrate that as fog-seal application rate increased, permeability decreased. Fog seal temporarily reduced the texture depth. However, texture depth could be recovered after the loaded wheel test. Obviously, fog seal can play a beneficial role on abrasion resistance, thereby presenting a potential to ameliorate the durability of OGFC pavements.

State highway agencies are required to establish performance targets for pavement facilities based on national performance measures. Because of the inconsistency and uncertainty in performance measures between the national and state systems, states are facing challenges in utilizing national performance measures to set state performance targets. Furthermore, because of the lack of historical data, it is difficult to establish reliable models to predict future performance measures. In this study, the cross-correlations among the national performance metrics were investigated. The national performance measures were correlated with the state performance indices by a probabilistic method to consider the influence of uncertainty on setting the performance targets. Random forest method was employed to correlate the national performance measures to state performance indices. The results indicated that the international roughness index generally increased with the increase of standard deviation of rut depth. A single performance index was not correlated well with national measures of "poor" condition, whereas the pavement quality index (PQI) correlated well with "good" condition. The accuracy of the classification model with two indices (pavement smoothness index, pavement distress index) was higher than that with a single index (PQI). The probabilistic curves were developed to correlate state performance index and national measures, which can be used for performance target setting. This paper demonstrates that the national measures could be introduced into the state decision-making process by establishing probabilistic relationships between the national performance measures and the state pavement condition indices.

AbstractInternational roughness index (IRI) is widely employed for evaluating pavement performance. It is a critical indicator used by state transportation agencies to identify the maintenance dema...

The potential of using compaction meter value (CMV) for evaluating the compaction of asphalt pavements has been hindered by the fact that the value of CMV can be affected by many factors, which include not only roller operation parameters, but also the temperature of asphalt layer and the underlying support. However, the conventional data processing of CMV usually ignores these factors. The study proposed a new approach to thoroughly examine the relationships between CMV and other factors. Using a field project in Tennessee, USA, the intelligent compaction data were examined to establish the relationships between CMV and other operation parameters such as roller frequency and amplitude first, then the effects of asphalt temperature and underlying support were analysed further utilising the original Witczak model and Abaqus software. After eliminating the influence of other factors, the proposed method could improve the correlation between the asphalt mixture density and CMV.

This study compares the interlayer shear properties of pavement layers composed of different asphalt mixture types. Two dense asphalt mixtures (one surface mixture with Tennessee designation of D mix and another binder course mixture with Tennessee designation of BM mix) and one open-graded friction course (OGFC) mixture were selected for the comparison. The direct shear test was conducted with and without normal stress to assess the shear strength and shear stiffness at different tack coat application rates. Results show that at 0.2-MPa normal stress, the specimens composed of two dense mixtures gave higher shear properties than those with OGFC as the upper layer. This is due to the fact that the noncontact area between the OGFC and the underlying layer compromised the bonding between the two layers. Among the samples composed of two dense layers, the D-BM specimens showed a higher interlayer shear resistance resulting from a larger interlayer roughness caused by a better aggregate interlock between D and BM mixtures. This indicates an upper layer with a small nominal maximum aggregate size (NMAS) and an underlying layer with a large NMAS could provide a better bonding. For specimens composed of OGFC and a dense mixture (D or BM), at the optimal tack coat application rate, OGFC-BM showed a better shear performance than OGFC-D, due to the double effects of a larger interface contact area and a larger interface roughness than OGFC-D. (C) 2018 American Society of Civil Engineers.

Intelligent compaction (IC) is a relatively new technology for asphalt paving industry. The present study evaluated the effectiveness and potential issues of the IC technology for flexible pavement resurfacing construction using two field projects. In the first project, a geostatistical semivariogram model was established and the parameters derived from it were compared with univariate statistical parameters for the Compaction Meter Value (CMV) data. Further analyses illustrated the effect of temperature on the CMV value and compaction uniformity. In the second project, a multivariate analysis was performed between in situ tests and IC data. The possibility of combining various IC data to predict the asphalt layer density and improve the current quality control and assurance system was discussed.

Open graded friction course (OGFC) is a thin surface layer on pavements constructed with an open gradation asphalt mixture comprising of mostly coarse aggregate with very little fines to ensure a higher air voids content. This layer improves road users' safety in wet conditions. The University of Tennessee conducted a survey to states Departments of Transportation (DOT's) to gain knowledge on the usage, benefits, and challenges of OGFC. This paper presents the results of the survey that was sent to 52 states including District of Columbia and Puerto-Rico. Forty states (77%) responded to the survey. The responses indicate that 45% of the respondents still use OGFC, 42% used in the past they are no longer using it and 13% never used OGFC. The use is more concentrated in the Southern states than the Northern states of the US.

This laboratory study evaluated the influence of interface characteristics on the bonding properties between open-graded friction courses (OGFC) and the underlying layer. One gravel OGFC and two commonly used underlying layers [one base material (BM) and one thin-layer D mixture (TLD)] were used in this study. The BM is a regular asphalt binder course mixture with 19-mm nominal maximum aggregate size, whereas the TLD is a thin asphalt surface-wearing course mixture with 12.5-mm nominal maximum aggregate size. A direct shear test was performed to obtain the shear strength and shear stiffness at different tack-coat application rates. Adhesive and cohesive failure types on the interfaces were identified. Noncontact area between OGFC and underlying was obtained. Results showed that there were no significant differences in adhesive failure area between OGFC-TLD and OGFC-BM. The cohesive failure area of OGFC-TLD was larger than that of OGFC-BM. The noncontact area between OGFC and BM was larger in contrast with the area between OGFC and TLD at the same tack-coat application rate. With an increase in tack-coat application rate, the adhesive failure area and noncontact area decreased and cohesive failure area increased. The shear force to overcome the adhesive bonding between OGFC and BM was larger than that of OGFC and TLD at the same tack-coat application rate because of the larger interface roughness caused by BM's coarser aggregate gradation. At the optimal tack-coat application rates for OGFC-TLD and OGFC-BM, the difference in shear force to overcome the cohesive bonding between OGFC-BM and OGFC-TLD was very slight. The shear force to overcome the adhesive bonding is the factor that made the shear strength and shear stiffness of OGFC-BM larger than those of OGFC-TLD.

While having been successfully used for soil compaction for many years, intelligent compaction (IC) technology is still relatively new for asphalt pavement construction. The correlation between Compaction Meter Value (CMV) from the IC compactor and the compaction degree of the asphalt layers is hard to identify, mainly due to: (1) multi-layer structure of the road, (2) non-linear behaviour of asphalt materials, and the measuring depth of the IC roller. In this study, the possibility of utilising CMV to evaluate the density of different asphalt pavement layers was examined. The displacements of the newly placed surface layer and the underlying layers under a vibratory roller were analysed using the original Witczak model and the multi-layer pavement analysis software BISAR. A method was proposed to filter the effects of the underlying layers on CMV. Data from two asphalt pavement IC compaction projects in Tennessee were employed to verify the proposed filtering method. Further laboratory methods to simulate the IC roller compaction were also discussed.

The incorporation of recycled (aged) binder into virgin asphalt has become more popular in asphalt paving industry nowadays. However, the exact mechanism of the diffusion process between virgin and aged binders is still largely unclear. This paper presents a study in which molecular dynamics (MD) simulation was employed to investigate the diffusion between virgin and aged binders. Two asphaltic models with three components including asphaltenes, resin, and oil were built with different components ratio. The model of aged binder was constructed by increasing the asphaltenes ratio on the basis of virgin binder. The results of simulation was verified by GPC and both show that the diffusion of large molecules in asphalt was a critical factor for the diffusion of binders in that it was more susceptible to the changes of temperature. In an inter-diffusion model of virgin and aged binders, the diffusion coefficients of binders were not only determined by the diffusion ability itself, but also influenced by the properties of the diffusion acceptor. Based on this finding, the effect of different sequence of adding rejuvenator during recycling of asphalt mixtures was investigated. The result shows that adding rejuvenator into aged binder first could accelerate the inter-diffusion rate between virgin and aged binder in maximum level, thus increased the efficiency of recycling.

Due to variable aging of recycled asphalt pavement (RAP) and recycled asphalt shingle (RAS), the concerns arise over old-new binder blending during mixture production and subsequent diffusion process. In this study, a modified staged-extraction method was validated and employed to extract binder in approximately equal layers from retrieved virgin and RAP/RAS aggregates after mixing and subsequent diffusion treatment. Quantitative analysis was done on extracted binders in terms of large molecule size percentage LMS (%) from gel permeation chromatography (GPC). The results indicated that a well-blended binder film coated virgin aggregates from 50% RAP mix, while a non-homogeneous binder film was observed on RAP aggregates. The system of binder blend coating the virgin and RAP aggregates with un-mobilized RAP binder was validated. A possible composite binder system was found coating the virgin aggregates in 10% RAS mix. The diffusion study showed that within the mixture silo storage time, binder diffusion could be accomplished in both warm and hot mixes containing 50% RAP, indicating that binder homogeneity may not be an issue in high RAP mix. The binder diffusion in RAS mix was captured in a very slow rate. It was suggested that binder homogeneity can still be critical for high RAS mix.

The objective of the study was to evaluate the bonding fatigue performance between open-graded friction course (OGFC) and underlying layer through laboratory testing at different tack coat application rates. Direct shear fatigue test was performed to obtain the shear fatigue properties of the composite specimens composed of OGFC and its underlying layer. Two types of dense graded asphalt mixture (named BM and TLD in Tennessee) were selected as the underlying layer. In addition to the fatigue life determined according to the conventional 50% stiffness reduction method, energy approach was also employed to analyze the fatigue behavior of the composite specimens. Results showed that the OGFC-TLD structure gave a better shear fatigue performance than OGFC-BM. With the increase in tack coat application rate, the plateau value (PV) increased and the total cumulative dissipated energy decreased for both combined structures. The contact area between OGFC and the underlying layer was measured and correlated to the fatigue life. The contact area between OGFC and TLD was larger than that between OGFC and BM, leading to a better fatigue performance of OGFC-TLD.

This study investigates the factors that affect the bonding strength between open-graded friction course (OGFC) and underlying layer through laboratory testing. The direct shear strength test was performed to obtain the shear strength between OGFC and different underlying layers. Three factors were considered in the study: mixture type of underlying layer, tack coat application rate, and temperature. Two types of dense graded surface mixture and one type of stone matrix asphalt (SMA) were selected as underlying layer. The shear strength was evaluated at four tack coat application rates and three test temperatures. To investigate the friction between OGFC and underlying layer on the shear strength, the surface texture depth of underlying layer was also measured. Results from the study showed that underlying layer mixture type, tack coat application rate, and temperature all played a significant role in the shear strength, with temperature as the most significant factor followed by surface texture depth of underlying layer. At low temperatures, high stiffness of asphalt made both tack coat rate and surface texture depth of underlying less significant. At intermediate to high temperatures, surface texture depth of underlying layer had a significant effect on the shear strength, indicating that selection of appropriate underlying layer with adequate friction with OGFC is critical for a good bonding shear strength. Surface texture depth of underlying layer can be used as an indicator of the friction between OGFC and underlying layer.