Journal of Transportation Engineering, Part B: Pavements

The traditional mechanical equipment/chemical salt approach for pavement snow/ice removal is costly and may cause serious environmental pollution problems. To facilitate the pavement snow/ice melting in a more economical and sustainable way, a novel steel slag–based composite phase change aggregate (SS-CPCA) asphalt pavement was developed, and its technical performance was experimentally evaluated. The experimental results revealed that: (1) after 14 cycles of freeze–thaw treatment, the SS-CPCA asphalt pavement has an identical temperature regulation performance as its initial state, identifying that its long-term thermal durability is promising; (2) snow layer with a thickness of 5 mm that is covered on the SS-CPCA asphalt pavement at 0°C can be melted completely within 32 min, verifying that the SS-CPCA asphalt pavement has a satisfactory snow melting performance; and (3) a decrease of environmental temperature can result in an increase of ice melting rate (IMR) and a decrease of effective ice melting time (EIMT), indicating that the IMR and EIMT should be balanced to each other when selecting appropriate PCMs for pavement snow/ice melting. In addition, the economic–environmental performance of the SS-CPCA asphalt pavement was examined through a case study. It was found that, as compared with conventional asphalt pavements, it has a relatively higher initial construction cost. However, when taking the snow/ice removal cost into account, its total cost is significantly lower for the second-year application. Further, the SS-CPCA asphalt pavement can dramatically reduce ${\mathrm{CO}}_2$ emissions as compared with the traditional snow/ice melting approaches. Thus, it can be concluded that the newly developed SS-CPCA asphalt pavement can provide considerable economic–environmental benefits toward the pavement’s snow/ice melting.

Semirigid pavements are gaining importance in the pavement design field due to their improved performance in freezing zones. These semirigid pavements are constructed similarly to asphalt pavements, but with a cement-stabilized base layer. However, there is a limited study that quantifies the influence of design factors on the performance of semirigid pavements. Therefore, an attempt was made to investigate the role of subgrade, temperature, moisture, traffic, crack joint spacing, speed, asphalt thickness, cement-treated base (CTB) layer thickness, elastic modulus, and modulus of rupture of CTB layer on semirigid pavement design. Different combinations of factors were formulated using fractional factorial design in the design of the experiment (DoE). All factors influencing the design of semirigid pavements were considered on two levels (low and high). This analysis used data from the Federal Highway Administration’s (FHWA’s) Long-Term Pavement Performance Program (LTPP). These data were incorporated into the AASHTOWare Pavement ME Design 2.6.1 (MEPDG) software. Design-Expert was used to determine the significance of various factors on the performance indexes. In addition, an optimization technique was used to determine the optimal design thickness for cement-treated base under various subgrade and climatic conditions. The result suggests that the thickness of a CTB layer is greater on fine-grained soil than on coarse-grained soil.

Flooding can cause severe damage to roadway infrastructure due to inundated foundation. It is important to evaluate the postflooding pavement performance and make decisions for roadway opening and operation. Many studies have evaluated pavement performance after flooding, but the existing methods are either oversimplified or not applicable without information of realistic pavement saturation conditions. This study developed a new method to assess quantitatively the postflooding pavement performance, and proposes a decision support framework for roadway operation based on falling weight deflectometer (FWD) testing. Field measurements were collected to characterize the nonlinear modulus of pavement unbound materials under realistic stress states and moisture conditions. Finite-element models were developed and validated to relate FWD deflections to critical pavement responses under traffic loading. The results show that FWD deflections have good correlations with pavement surface deflections and tensile strains at the bottom of the asphalt layer under moving loads, which facilitates prediction of pavement performance. With the information of traffic loading on the roadway, pavement damage ratios at different saturation conditions after flooding can be evaluated. By comparing the estimated damage ratio and the agency-determined threshold, either truck weight limits or volume control can be adopted to mitigate the impact of flooding on pavement damage. With the method proposed in this study, transportation agencies can implement roadway operation considering performance deterioration and recovery of postflooding pavement.

A pavement maintenance treatment that has increased in popularity in recent years is ultrathin overlay (UTO). While the selection and construction processes for UTO has been well researched in previous studies, few studies assessed the field performance and cost-effectiveness of UTO especially in hot and wet climates. Therefore, the objective of this study was to evaluate the field performance and cost-effectiveness of UTO projects in Louisiana. To achieve this objective, asphalt pavements in Louisiana that received UTO were monitored for up to 14 years. The performance and cost-effectiveness of these sections were evaluated in terms of pavement condition Index (PCI), alligator cracking index (ALCR), rutting index (RUT), random cracking index (RNDM), and roughness index (RUFF). Results showed that UTO extended the pavement service life (PSL) by 8.7, 9.1, 7.0, 9.7, and 9.5 years, on average, for PCI, RUFF, RNDM, ALCR, and RUT, respectively. This extension varied based on the pretreatment pavement conditions and traffic level. As such, a predictive model was developed, with reasonable accuracy, to predict the extension in PSL of UTO based on project conditions. Results of the cost-benefit analysis indicated that UTO was cost-effective in most of the cases. The findings of this study were incorporated into a decision-making tool to assist transportation agencies in hot and humid climates determine the expected immediate and long-term field performance as well as the cost-effectiveness of UTO based on their project conditions. This will help these agencies make effective decisions for the maintenance and rehabilitation of their pavements.

Different test methods have been used to predict the performance of asphalt pavement by addressing the cracking mechanism. Based on the preference shown by highway agencies, the two most prevalent tests are the Indirect Tensile Asphalt Cracking Test (IDEAL-CT) and the Illinois Flexibility Index Test (I-FIT). Both tests conform to the fracture energy–based principle in defining the cracking potential of asphalt concrete at intermediate temperature, and therefore, for quality assurance, many agencies use these tests interchangeably following convenience without comprehending the relationship, if any, between them. Therefore, the study aims to find an equivalency between the tests by evaluating the fracture behavior and different measured parameters that are used to develop the cracking indexes and subsequent performance. In this regard, 11 different mixes have been evaluated to predict the cracking potential following their significant properties. Although both tests consistently identify possibly poor mixes, there is no appreciable proportionality between them. Moreover, the tests exhibit different fracture energy and strength and show individual slopes in failure mechanism trends. In contrast to fracture energy alone, the postpeak slope and the strength of the mixture seem to correlate better with the respective indexes. In general, the tests are not interchangeable; therefore, the selection of a mixture following the index value should be based on carefully observed field performance rather than just convenience. It is also recommended to incorporate the field performance of mixtures to find a better correlation when selecting the appropriate test performance criteria.

Dynamic modulus is a key material property to predict the performance of flexible pavements. Several prediction models have been developed worldwide to predict the dynamic modulus from aggregate, binder, and mixture properties with corresponding frequency and temperature. Artificial neural network (ANN)-based prediction models have shown better accuracy than regression-based models. In this study, two ANN-based prediction models were developed for the Colombian hot-mix asphalt (HMA) mixtures. One model (W-ANN) has similar input variables as the Witczak model, and the other model (H-ANN) has similar input variables as the Hirsch model. The ANN-based dynamic modulus prediction models were trained, validated, and tested using 972 data points. The coefficient of determination ($R^2$), RMS error (RMSE), absolute average error (AAE), and $S_e/S_y$ indicated that the two ANN-based models performed better than the previous models. The W-ANN had slightly better performance than the H-ANN model. The parameters for both ANN-based models are reported to reproduce dynamic modulus values for future use and testing with high accuracy. A standalone closed-form equation was extracted from each ANN model, which makes the developed models easier for and more accessible to practitioners. Sensitivity analysis showed that both models are sensitive to binder and mixture properties. These models can be utilized in Colombia for the existing and future development of pavement design packages, and will reduce the necessity of extensive testing in the future.

Concrete pavement performance models are evaluated, calibrated, and validated using field data from databases like the Long-Term Pavement Program. Conceptually, performance model predictions should match field data considering a reliability of 50%; that is, there is a 50% probability that the predictions of a certain distress indicator are higher or lower than the field data. However, modern pavements are designed for higher levels of reliability (usually 90% to 95%). Local performance model evaluation for higher levels of reliability requires a high amount of field data that traditional databases lack. Pavement management system (PMS) databases can be a useful resource for high reliability model analysis because of the large amount of data collected locally and regularly. However, when selecting and filtering field databases (of any source), the effect of censored performance data due to rehabilitation, removal from service, or modification of pavement sections is usually ignored. This paper proposes an approach for the use of PMS databases accounting for censored performance data to evaluate the accuracy of performance models’ high reliability predictions. The approach is exemplified using a PMS transverse joint faulting database. Results show that by addressing the “survival issue,” i.e., accounting for the censored performance data, the resulting PMS-based reliability model improves the faulting model accuracy in matching the field data for high reliability levels.

This study was motivated by the need for a road profile monitoring concept that can provide frequent measurements over large areas across all weather conditions. A profile inversion method was proposed in this context, based on measured in-vehicle accelerations alongside speed and location information. The method combined a quarter-car response model, a proportional-integral-derivative controller, and a nonlinear error minimization algorithm. In general terms, the underlying idea for profile inversion was centred around best-matching measured accelerations with accelerations calculated in a precalibrated quarter-car response model. The new method was first verified with synthetic/manufactured acceleration traces. Next, it was applied to real data obtained from 10 nominally identical electric cars that were driven over highways and urban roads. Inverted road profiles were compared to those measured by a standard laser profilometer. Very good match and reproducibility metrics were obtained, especially for highways, indicating that the new method is potentially useful as a large-scale road profile monitoring concept.

Abstract

Aging of asphalt increases its hardness due to oxidation, which challenges the incorporation of higher recycled asphalt (RA) content. Waste cooking oil (WCO) is gaining attention as a rejuvenator to incorporate higher RA content in new pavements. The study evaluated the potential of WCO as a rejuvenator before and after transesterification. Rheological tests, such as frequency–temperature sweep and multiple stress creep recovery (MSCR) were conducted to assess the performance characteristics of different rejuvenated binders. Chemical tests, including asphaltene extraction, free fatty acids, transesterification, Fourier-transform infrared spectroscopy (FTIR), and nuclear magnetic resonance (NMR) were performed to corroborate the rheological findings. Based on the investigation, a new method is proposed to determine the optimum dose of WCO for binders incorporating RA, considering viscosity and rutting. The results indicated that the optimum WCO content before treatment was on average 7.03%, which was reduced to 5.73% after transesterification. This is credited to the reduction of free fatty acids by 81.7% in treated WCO after transesterification, resulting in enhanced diffusion characteristics between treated WCO and recycled asphalt pavement (RAP). The rejuvenated binder had a 49.33% lower carbonyl index (CI) than RAP and an 18.35% higher CI than unaged viscosity-graded (VG) 30, respectively, validating the potential of WCO as a rejuvenator. ANOVA analysis of asphaltene content showed no significant difference between the rejuvenated binders with their corresponding optimum WCO and unaged VG 30 contents. Overall, transesterification of WCO could be a potential solution to improve the diffusion characteristics for enhanced rejuvenation.

Practical Applications

Reclaimed asphalt can be processed and used as a component in the production of new hot-mix asphalt. It commonly is mixed with virgin asphalt binder, aggregates, and other additives to create a sustainable asphalt mixture. The inclusion of RA reduces the demand for virgin materials such as asphalt binder and aggregates, thus decreasing the environmental impact of asphalt production. The current practice permits a lower quantity of RA in asphalt mixtures due to its higher stiffness. The utilization of WCO as a rejuvenator can restore the properties of RA binder to a considerable extent. It also will result in higher RA incorporation and a sustainable solutions including, reduction in inappropriate disposal and multiple-time utilization of WCO. Hence, the utilization of RA with WCO as a rejuvenator is a novel solution for sustainability.

Abstract

The prediction of strain responses under axle loadings is critical for flexible pavement design by the mechanistic-empirical approach. The mechanistic-empirical pavement design (pavement ME) method uses linear-elastic analysis to simulate the strain responses under axle loadings, and it relies on the concept of equivalent loading frequency to determine the elastic modulus of the asphalt concrete (AC) layer from the dynamic modulus master curve. The pavement ME method has a simplified procedure to calculate this frequency. The main goal of this study is to evaluate the accuracy of axle loading frequency calculated by the pavement ME method. This paper first introduces the concepts of predominant and equivalent frequencies, provides a brief explanation of the difference between them, and then proposes three predominant frequency methods for evaluation. The accuracy of the pavement ME method and the other methods of calculating the predominant frequency is evaluated in terms of frequency, modulus, and strain by comparing their results with those from dynamic viscoelastic analysis with moving loads. Results show that the time–frequency relationship for predominant frequency is closer to $f=1/(2t)$ than $f=1/t$, assuming that the pulse duration $t$ is accurate. Nevertheless, using $f=1/t$ with the approximate pulse duration as calculated by the pavement ME method gives reasonable predictions of the maximum tensile strain. On the other hand, while it gives reasonable predictions of vertical strains with increasing depth, the pavement ME method can underestimate them near the surface by up to 55%. Overall, even though the procedure for pavement ME frequency calculation is highly simplified, its general performance appears to be acceptable.

Practical Applications

The two most typical distresses of flexible pavement are rutting and fatigue cracking, and they are related to two critical strains: vertical strains throughout the layers and horizontal strains at the bottom of the asphalt concrete later of the pavement. The commonly used design approach, the pavement ME method, utilizes the concept of equivalent loading frequency to predict critical strains within the pavement by linear-elastic analysis rather than the full dynamic viscoelastic analysis. This reduces the computational cost significantly. This paper investigates the accuracy of the equivalent loading frequency calculated by the pavement ME method by comparing the frequency values with several other methods, and, finally, comparing the critical strains predicted by the pavement ME method and the results from dynamic viscoelastic analysis, which is considered to be the truth. The results showed that the pavement ME method underestimates vertical strains near the surface of the pavement, which may lead to underestimating rutting (before calibration). However, calibration may be able to remedy the problem. On the other hand, the horizontal strain predicted by the pavement ME method is reasonable, which means the fatigue cracking can be reasonably predicted.

This study proposes a three-dimensional (3D) mesomechanical simulation–based approach to determining the representative volume element (RVE) of asphalt concrete. In this approach, 3D mesostructures of asphalt concrete were developed by parametrically modeling the morphological characteristics of coarse aggregates and air voids. To define the RVEs, the effects were assessed of several geometrical characteristics, such as the volume fraction, gradation, and spatial distribution of coarse aggregates in the mesostructures. Further, the geometrically defined RVE was verified by performing finite-element simulations and inspecting whether the effective mechanical properties of asphalt concrete, such as the viscoelastic dynamic modulus, were accurately simulated. This approach was applied to a typical dense-graded asphalt concrete with a nominal maximum aggregate size of 13.2 mm. The results indicate that the proposed approach can effectively define the RVE of the asphalt concrete, of which the effective properties can be precisely simulated from the RVEs with a size of 50 mm. In addition, in terms of accurately characterizing the dynamic modulus only, an RVE size of 45 mm can satisfy the requirement. Findings of this paper are consistent with the results of existing RVE studies performed based on the laboratory tests. Therefore, the proposed approach provides a novel simulation-based paradigm for efficiently defining the 3D RVEs of asphalt concrete in mesoscale/multiscale simulations.

With the development of state-of-the-art algorithms, pavement distress can already be detected automatically. However, most pavement distress detection is currently implemented as a single task, either at the region level or at the pixel level. To comprehensively assess the pavement condition, a multitask fusion model, Pavement Distress Detection Network (PDDNet), was proposed for integrated pavement distress detection at both the region level and pixel level. PDDNet was trained and tested on distress images captured via unmanned aerial vehicle (UAV), and seven types of pavement distresses were investigated and analyzed. Compared with Mask Region-based Convolutional Neural Network (R-CNN), U-Net, and W-segnet, PDDNet shows higher performance in classification, localization, and segmentation of pavement distresses. Results demonstrate that PDDNet achieves region-level and pixel-level detection of seven types of distresses with the mean average precision of 0.810 and 0.795, respectively. As a portable and lightweight device, the UAV can collect full-width pavement distress images, which helps improve the efficiency of pavement distress detection.

To study the influence of periodically changing temperature on the crack repair structure of asphalt pavement, the temperature field model and temperature stress calculation model of repaired pavement structure with crack sealant were established using ABAQUS. The temperature field distributions in different climate divisions were obtained. The mechanical response of bond interface between crack sealant and repaired pavement was calculated. The results indicate that the bond interface is subjected to tensile and shear stress under periodically changing temperature. The most unfavorable positions of tensile and shear stress were determined. The tensile stress level is much higher than shear stress in five climate divisions. The stress level of bond interface is significantly influenced by the lowest temperature and temperature difference. The different pavement structure forms have a slight effect on the stress level of the bond interface, but this effect is far less than the influence of climate conditions. Finally, the bond failure of bond interface was simulated. Based on the simulation, the minimum bonding strength requirements ($T_n$) for crack sealant in different climate divisions were proposed. These requirements provide a reference and basis for the bonding performance evaluation and practical application of crack sealant.