Journal of Road Engineering最新文献

The application of reclaimed asphalt pavement (RAP) and reclaimed asphalt shingles (RAS) on asphalt pavement can reduce the asphalt paving cost, conserve energy and protect the environment. However, the use of high contents of RAP and RAS in asphalt pavement may lead to durability issues, especially the fatigue cracking and thermal cracking. It is necessary to conduct a series of analyses on asphalt mixtures containing high RAP and RAS, and seek methods to enhance their long-term performance. This paper provides a comprehensive over-view of the long-term performance of recycled asphalt mixtures containing high contents of RAP and RAS. The findings in this research show that rutting resistance of high recycled asphalt mixtures is not a concern, whereas their resistance to fatigue and thermal cracking is not conclusive. Recycling agents can be used to improve the thermal cracking resistance of high recycled asphalt mixtures. An optimum decision on recycling agents will improve the durability properties of high recycled asphalt mixtures. It is recommended that to use a balanced mixture design approach with testing of the blended asphalt binders will provide better understanding of long-term performance of recycled asphalt mixtures containing high RAP and RAS.

This study aims to quantify the susceptibility of granular materials used in pavements to changes in moisture content and propose a correlation model to incorporate this susceptibility into seasonal analyses. The fines content and the percentage of fractured coarse aggregates were identified as direct indicators of the resilient modulus susceptibility to changes in water content. The results showed that the percentage of fractured coarse aggregates particles (FR) has a more significant impact on the resilient modulus (Er) of crushed granular materials used in pavement construction than the combined indicator of the fines content and sample volumetrics (n_f). Crushed granular materials with a higher percentage of fractured coarse aggregates are relatively insensitive to changes in the degree of saturation, but become more sensitive as the fine fraction porosity decreases. An adjusted model was proposed based on the existing formulation, but considers a complex parameter to describe and adjust the sensitivity of base granular materials to variations in moisture content with respect to fabrication characteristics, fines content and volumetric properties. The model shows that the variation of Er values is below ±10% for fully crushed granular materials. However, it reaches approximately ±12% for materials with 75% of crushed coarse aggregates and +40% and −25% for materials with FR ​= ​50%. This model could help select good aggregates characteristics and adjust grain-size distribution for environments where significant moisture content variations can occur in the pavement system, such as in the Province of Quebec (Canada). As it is based on parameters that can be easily determined or estimated, it also represents a valuable tool for detailed design and analysis that can consider material characteristics.

This paper reviews works on the dynamic analysis of flexible and rigid pavements under moving vehicles on the basis of continuum-based plane strain models and linear theories. The purpose of this review is to provide information about the existing works on the subject, critically discuss them and make suggestions for further research. The reviewed papers are presented on the basis of the various models for pavement-vehicle systems and the various methods for dynamically analyzing these systems. Flexible pavements are modeled by a homogeneous or layered half-plane with isotropic or anisotropic and linear elastic, viscoelastic or poroelastic material behavior. Rigid pavements are modeled by a beam or plate on a homogeneous or layered half-plane with material properties like the ones for flexible pavements. The vehicles are modeled as concentrated or distributed over a finite area loads moving with constant or time dependent speed. The above pavement-vehicle models are dynamically analyzed by analytical, analytical/numerical or purely numerical methods working in the time or frequency domain. Representative examples are presented to illustrate the models and methods of analysis, demonstrate their merits and assess the effects of the various parameters on pavement response. The paper closes with conclusions and suggestions for further research in the area. The significance of this research effort has to do with the presentation of the existing literature on the subject in a critical and easy to understand way with the aid of representative examples and the identification of new research areas.

E-ticketing, which has been promoted by the Federal Highway Administration (FHWA) “every day counts” (EDC) initiative, utilizes software applications to digitally track and store information regarding highway construction materials paid by state transportation agencies (STAs) by weight in unit bid contract structures. STAs often face implementation barriers such as institutional inertia, or the resistance by stakeholders to adopt changes from the status quo, including new technologies. The purpose of this paper is to determine the progression of STA e-ticketing policy adoption, specifically with a focus on asphalt paving operations, due to the COVID-19 pandemic. To accomplish this research effort, previous FHWA data, National Cooperative Highway Research Program (NCHRP) data, and other literatures are reviewed to determine an implementation baseline. Additional data is collected from the American Association of State Highway and Transportation Officials Committee on Construction to gain current feedback from STAs and their highway contractor partners after the COVID-19 pandemic. Additionally, a case study featuring the Kentucky Transportation Cabinet (KYTC), the Kentucky Association of Highway Contractors (KAHC), and the Plantmix Asphalt Industry of Kentucky (PAIKY) is performed to provide more in-depth analysis. The major finding includes a statistically significant result indicating increased implementation of e-ticketing for asphalt operations within the last two years, along with noting benefits including employee safety, task loading, and project documentation along with concerns regarding cellular connectivity and procurement responsibilities. These findings indicate the importance of STAs investing in partnership with contractors to improve stakeholder buy-in before proceeding towards e-ticketing adoption.

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs, this study presents an intelligent strategy for extracting road cracks. This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images. The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously. A convolutional neural network is utilized to extract cracks from the panoramic sequence image. The extracted sequence image is then aligned with the laser point cloud, enabling the assignment of RGB information to the vehicle-mounted three dimensional (3D) point cloud and location information to the two dimensional (2D) panoramic image. Additionally, a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud. The three-dimensional data pertaining to the cracks can be acquired. The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks. The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks. This approach exhibits superior accuracy when compared to conventional methods. Moreover, it facilitates rapid and accurate identification and localization of road cracks, thereby playing a crucial role in ensuring road maintenance and traffic safety. Consequently, this technique finds extensive application in the domains of intelligent transportation and urbanization development. The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

This study normalized the mixture's fatigue behavior at various temperatures, and the strength and fatigue tests of the mixture were conducted. The stress state of the asphalt mixture includes direct tensile, uniaxial compression, and indirect tensile. The Desai yield surface and fatigue path were proposed. And a normalized fatigue characteristics model of the mixture was established. The following conclusions were obtained. With the increases in the loading rate, the strength of the asphalt mixture increased. As the temperature increases, the strength of the mixture is reduced. At various temperatures and rates, the strength forms a closed curved surface. The Desai strength yield surface was established, which forms a closed curved surface. When the loading rate and temperature are below a certain critical line, the asphalt mixture will not undergo strength damage. At a fixed stress state, the fatigue damage path of the mixture was determined. The stress ratio was determined considering the influence of the loading rate. In this way, a normalized model can be described to express the asphalt mixture fatigue properties at various temperatures and stress levels. For the asphalt mixture in an indirect tensile state, the normalized fatigue equation parameter is 4.09. This model is more suitable for reflecting the viscous-elastic behavior of the mixtures than the fatigue equation determined by the notional stress ratio.