Search

The performance of an asphalt mixture does not only rely on its engineering properties. Yet, the service characteristics of an asphalt mixture do play an important role on the durability of pavements. This study was conducted to evaluate the effect of different aggregate types (granite and limestone) and the incorporation of recycled paper mill sludge (RPMS) on mixtures behaviour in terms of workability and compaction energy index (CEI). The effect of RPMS incorporation on the leaching potential was also assessed. A test was evaluated through the toxicity characteristics leaching procedure (TCLP) to identify the leaching behaviour of heavy metals with a possibility to contaminate the nearby water sources. Next, a surface morphological analysis was also conducted through the Scanning Electron Microscopy (SEM) to assess the relationship of fillers addition to the optimum binder content and water absorption. In this study, RPMS was used at rates of 0.5% and 1%. Based on the TCLP's results, the leaching potential of RPMS incorporated mixture was addressed and proven to be less than the standardised requirements. The addition of different percentages of RPMS into limestone and granite asphalt mixtures had resulted in the increment of optimum binder content; however, still lower than control samples. Whereas their small increment in the combined water absorption percentage are relatively same to the control samples. The workability indices of asphalt mixtures peaked upon the usage of 0.5% RPMS but slightly reduced at 1% RPMS but nevertheless remained higher than the control specimen. This is due to the ability of RPMS reduce the surface tension, hence enabling less energy for compaction. The 0.5% RPMS addition was found to be the optimal content required to obtain a better service performance of asphalt mixture during mixing and compaction processes. [ABSTRACT FROM AUTHOR]

In view of the low identification accuracy of the crack-detection technology of asphalt pavement under the current conditions of complex pavement (subject to strong light, water on the road, debris, and so on), an asphalt pavement crack-detection algorithm based on improved YOLOv5s was proposed by building the data set for asphalt pavement cracks. The first step was to make the following improvements to the original YOLOv5s model according to the characteristics of the asphalt pavement crack data set: The k -means++ algorithm was used to recluster the anchor points of the crack data set, and the initial anchor frame matching the crack characteristics of the asphalt pavement was obtained to replace the default initial anchor frame in the YOLOv5 original model. In the prediction part of the original model, the Convolutional Block Attention Module (CBAM) was added in the order of first channel and then space to improve the detection ability of the model to small cracks. The CIoU_Loss function was used as the regression loss function of the model to replace the GIoU_Loss function in the original model to improve the positioning accuracy of the anchor frame. The second step was to perform an ablation experiment on the improved YOLOv5s model. This would prove that each improvement scheme could increase detection ability without conflict. The final step was to compare the improved YOLOv5s model with various classic target detection models in the data set of this paper: the Crack Forest Data set (CFD), the Crack500 data set, and the Crack200 data set. The results showed that the detection of the improved YOLOv5s model on each data set was better than other target detection models. The mAP@0.5 and mAP@[0.5:0.95] of this model on the data set of this paper were 90.58% and 56.08%, respectively, which were much higher than other target detection models. These findings indicate that the improved YOLOv5s model had better detection under complex pavement conditions and could provide a theoretical basis for the automatic detection of asphalt pavement cracks. [ABSTRACT FROM AUTHOR]

Pavement adhesion plays a crucial role in driving safety, while traditional test methods exhibit some limitations. To improve the efficiency and accuracy of asphalt pavement texture characterization and adhesion assessments, this paper uses three-dimensional (3D) laser technology to detect the continuous point cloud data of road surface and reconstruct the 3D topography of pavement texture. On this basis, a volume parameter Volume of peak materials (Vmp) is innovatively proposed to comprehensively characterize the 3D spatial characteristics of road surface texture. The correlation analysis between the proposed Vmp and the traditional adhesion evaluation index Transversal Adhesion Coefficient (CAT) is conducted, and then refined graded adhesion prediction models based on the proposed Vmp are proposed. Results show that the proposed volume parameter Vmp can reliably and accurately characterize the asphalt pavement texture by considering more structural properties of the road surface texture. According to the research findings of this paper, it is feasible to achieve rapid and correct assessment of asphalt pavement adhesion using 3D laser detection technology by comprehensively considering the 3D characteristics of the road surface texture. [ABSTRACT FROM AUTHOR]

Road crack detection is one of the important parts of road safety detection. Aiming at the problems such as weak segmentation effect of basic U-Net on pavement crack, insufficient precision of crack contour segmentation, difficult to identify narrow crack and low segmentation accuracy, this paper proposes an improved U-net network pavement crack segmentation method. VGG16 and Up_Conv (Upsampling Convolution) modules are introduced as backbone network and feature enhancement network respectively, and the more abstract features in the image are extracted by using the Block depth separable convolution blocks, and the multi-scale features are captured and enhanced by higher level semantic information to improve the recognition accuracy of narrow cracks in the road surface. The improved network embedded the Ca(Channel Attention) attention mechanism in U-net's jump connection to enhance the crack portion to suppress background noise. At the same time, DG_Conv(Depthwise GSConv Convolution) module and UnetUp(Unet Upsampling) module are added in the decoding part to extract richer features through more convolutional layers in the network, so that the model pays more attention to the detailed part of the crack, so the segmentation accuracy can be improved. In order to verify the model's ability to detect cracks in complex backgrounds, experiments were carried out on CFD and Deepcrack datasets. The experimental results show that compared with the traditional U-net network F1-score and mIoU have increased by 13.6% and 9.9% respectively. Superior to advanced models such as U-net, Segnet and Linknet in accuracy and generalization ability, the improved model provides a new method for asphalt pavement crack detection. The model is more conducive to practical application and ground deployment, and can be applied in road maintenance projects. [ABSTRACT FROM AUTHOR]

Cracks provide the earliest and most immediate visual response to structural deterioration of asphalt pavements. Most of the current methods for crack detection are based on visible light sensors and convolutional neural networks. However, such an approach obviously limits the detection to daytime and good lighting conditions. Therefore, this paper proposes a crack detection technique cross-modal feature alignment of YOLOV5 based on visible and infrared images. The infrared spectrum characteristics of silicate concrete can be an important supplement. The adaptive illumination-aware weight generation module is introduced to compute illumination probability to guide the training of the fusion network. In order to alleviate the problem of weak alignment of the multi-scale feature map, the FA-BIFPN feature pyramid module is proposed. The parallel structure of a dual backbone network takes 40% less time to train than a single backbone network. As determined through validation on FLIR, LLVIP, and VEDAI bimodal datasets, the fused images have more stable performance compared to the visible images. In addition, the detector proposed in this paper surpasses the current advanced YOLOV5 unimodal detector and CFT cross-modal fusion module. In the publicly available bimodal road crack dataset, our method is able to detect cracks of 5 pixels with 98.3% accuracy under weak illumination. [ABSTRACT FROM AUTHOR]

Crack disease is one of the most serious and common diseases in road detection. Traditional manual methods for measuring crack detection can no longer meet the needs of road crack detection. In previous work, the authors proposed a crack detection method for asphalt pavements based on an improved YOLOv5s model, which is a better model for detecting various types of cracks in asphalt pavements. However, most of the current research on automatic pavement crack detection is still focused on crack identification and location stages, which contributes little to practical engineering applications. Based on the shortcomings of the above work, and in order to improve its contribution to practical engineering applications, this paper proposes a method for segmenting and analyzing asphalt pavement cracks and identifying parameters based on image processing. The first step is to extract the crack profile through image grayscale, histogram equalization, segmented linear transformation, median filtering, Sauvola binarization, and the connected domain threshold method. Then, the magnification between the pixel area and the actual area of the calibration object is calculated. The second step is to extract the skeleton from the crack profile images of asphalt pavement using the Zhang–Suen thinning algorithm, followed by removing the burrs of the crack skeleton image using the connected domain threshold method. The final step is to calculate physical parameters, such as the actual area, width, segments, and length of the crack with images obtained from the crack profile and skeleton. The results show that (1) the method of local thresholding and connected domain thresholding can completely filter noise regions under the premise of retaining detailed crack region information. (2) The Zhang–Suen iterative refinement algorithm is faster in extracting the crack skeleton of asphalt pavement, retaining the foreground features of the image better, while the connected-domain thresholding method is able to eliminate the missed isolated noise. (3) In comparison to the manual calibration method, the crack parameter calculation method proposed in this paper can better complete the calculation of crack length, width, and area within an allowable margin of error. On the basis of this research, a windowing system for asphalt pavement crack detection, WSPCD1.0, was developed. It integrates the research results from this paper, facilitating automated detection and parameter output for asphalt pavement cracks. [ABSTRACT FROM AUTHOR]

Asphalt pavement's density measurement is an important step in the quality control of asphalt road construction. It is usually achieved by applying the coring method (CM), nuclear density gauge (NDG), and electromagnetic density gauge (EDG). CM is the most accurate method, but it is a destructive method because the pavement is damaged when the cores are taken. NDG and EDG are nondestructive methods with high efficiency, but their measurement accuracy is poorer than that of CM. An EDG commonly used in density measurement is named pavement quality indicator (PQI). A novel method named density profiling system (DPS) is also based on the potential EDG. However, it was not applied to this research because more tests are required to verify its accuracy. This paper presents an approach to improve the accuracy of the nondestructive methods with NDG and PQI. It is based on the artificial neural network (ANN), which processes the raw data got from NDG and PQI and produces the predicted asphalt density as the output. The density measured in CM was used as the target density and the error between ANN-predicted density and target density was computed. To minimize this error, various ANN architectures and learning algorithms were tried in the ANN training process. Each established ANN model makes a substantial improvement in the performance of NDG or PQI in asphalt density measurement. Practical Applications: This research was initiated by Fulton Hogan (FH) Limited, a large road construction and maintenance company in New Zealand. FH lab teams are responsible for asphalt road density measurement in FH's road projects. One of the main method they use is to measure the densities of the cores taken from asphalt pavements (coring method). It is quite accurate but destructive and very time-consuming. They also use NDG or PQI, which are highly efficient nondestructive measurement devices. However, their measurement accuracy is poorer than that of the coring method. FH lab teams wanted to have a new density measurement method that is both accurate and efficient. An ANN-based approach is presented in this paper to address the issues faced by the FH lab teams. Densities collected with coring methods, NDG, and PQI were used to train and validate the ANN models. The results from the ANNs show substantial improvements of the measurement accuracy and efficiency. The proposed approach has been presented to the FH lab teams, who are impressed with its performance and plan to implement it in their projects. [ABSTRACT FROM AUTHOR]

The arch expansion damage of asphalt pavement is a typical disease in desert Gobi and saline-alkali areas, and the reasons for arch expansion are very complex. Exploring the impact of salt solution on the mechanical and drying shrinkage performances of cement-stabilized macadam helps to clarify the causes of the arch expansion damage. To this purpose, this paper designed a salt solution infiltration experiment, using salt solution infiltration to simulate the transmission and accumulation of salts in cement-stabilized macadam, and carried out the compressive and flexural tests of cement-stabilized mortar and cement-stabilized macadam, and measured the drying shrinkage performance of cement-stabilized mortar and macadam. The results show that the type of salt solution has a significant influence on the weight of the cement-stabilized mortar samples, sulfates will cause the samples to lose weight, while chlorides and mixed solutions cause the increase in weight. Chlorides and sulfates lead to the decrease in the strengths of cement-stabilized mortar and macadam. The salt crystallization will lead to the decline of the drying shrinkage strains of cement-stabilized mortar and macadam, which has a positive action for reducing the drying shrinkage deformation. However, under the combined action of chlorides and sulfates, cement-stabilized macadam expands with the moisture loss. This may be one of the important causes of the arch expansion of asphalt pavement in the Gobi area and saline-alkali area. [ABSTRACT FROM AUTHOR]

Concurrently detecting multiple objects of interest will yield massive time savings in processing and enable a more streamlined and unified detection system. The ShuttleNet is designed to repeat the encoding–decoding round freely or even endlessly, achieving prodigious successes in terms of simultaneous detection of multiple pavement distresses and surface design features on asphalt pavements. This paper proposes an efficient and improved architecture of ShuttleNet called ShuttleNetV2 for enhanced global modeling and retrieving fine details capabilities. The proposed ShuttleNetV2 represents two major modifications on the original ShuttleNet. On the one hand, the self-attention mechanism is purposefully introduced to capture long-range dependency. On the other hand, ShuttleNetV2 adopts various sampling scales to combine the characteristics of different receptive fields. The experimental results indicate that the recommended architectural variation of the proposed ShuttleNetV2 model yields a mean F -measure of 94.21% and a mean intersection-over-union of 0.8914 on 1500 pairs of testing images. The proposed ShuttleNetV2 outperforms ShuttleNet in detecting nearly all types of pavement patterns. In particular, ShuttleNetV2 efficaciously tackles the tangible limitations of ShuttleNet in detecting giant distresses. Moreover, the ShuttleNetV2 can process an image in roughly 78 ms using modern graphic processing unit devices, which has a promising potential in supporting the real-time detection of multiple pavement distresses and surface design features on asphalt pavements. [ABSTRACT FROM AUTHOR]

During a heavy traffic flow featuring a substantial number of vehicles, the data reflecting the strain response of asphalt pavement under the vehicle load exhibit notable fluctuations with abnormal values, which can be attributed to the complex operating environment. Thus, there is a need to create a real-time anomalous-data diagnosis system which could effectively extract dynamic strain features, such as peak values and peak separation from the large amount of data. This paper presents a dynamic response signal data analysis method that utilizes the DBSCAN clustering algorithm and the findpeaks function. This method is designed to analyze data collected by sensors installed within the pavement. The first step involves denoising the data using low-pass filters and other techniques. Subsequently, the DBSCAN algorithm, which has been improved using the K-Dist method, is used to diagnose abnormal data after denoising. The refined findpeaks function is further implemented to carry out the adaptive feature extraction of the denoised data which is free from anomalies. The enhanced DBSCAN algorithm is tested via simulation and illustrates its effectiveness while detecting abnormal data in the road dynamic response signal. The findpeaks function enables the relatively accurate identification of peak values, thus leading to the identification of strain signal peaks of complex multi-axle lorries. This study is valuable for efficient data processing and effective information utilization in pavement monitoring. [ABSTRACT FROM AUTHOR]

This paper overviews the use of several waste materials for the construction and reconstruction of surface courses of asphalt pavements in the framework of sustainable perspectives that are adopted in pavement engineering. Based on a relevant literature search, the most commonly investigated alternative materials include waste plastic, crumb rubber, waste glass, steel slag, and Reclaimed Asphalt Pavement (RAP). Although recycling in pavement engineering is not a novelty, the strict performance requirements of the surface layers required to support a distress-resistant behavior possess continuous research challenges about the mechanical behavioral parameters, such as fatigue, rutting, moisture damage, and serviceability requirements, such as skid resistance. While studies in a laboratory environment mainly dominate, the importance of performance observations of real structures in the field is also pinpointed in an effort to provide a comprehensive overview of the so far knowledge status. Thereafter, this paper discusses peculiar issues and criteria for waste material selection that should balance performance requirements, local availabilities, and potential legislation concerns, thereby maximizing the economic or environmental advantages. [ABSTRACT FROM AUTHOR]

Featured Application: This review concludes the advantages of heat pipe technology and its application in permafrost regions are summarized, which can also provide recommendations for permafrost protection measures. Permafrost spans approximately 23–25% of the land in the northern hemisphere, primarily found in Russia, Canada, USA, and China. Numerous engineering projects, particularly those related to transportation, are situated within these permafrost regions. Due to the impact of highway construction and global warming, the permafrost beneath the infrastructure is deteriorating, leading to significant damage. Two phases closed thermosyphon (TPCT) is a widely accepted green countermeasure against the problem in permafrost regions. Although it has been applied to prevent permafrost degradation, their application presents significant challenges on account of the stronger endothermic action of asphalt pavement. This paper focused on a review of the thermosyphon technology and application in the permafrost. Moreover, the article highlighted the excellent working performance of the TPCT that improves the stability of the infrastructures and prevents it degrading due its excellent efficiency in terms of heat transfer. The industrial applications of the TPCT were also summarized, along with their limitations. Ultimately, the findings presented in this paper can offer crucial insights for future TPCT design and development in permafrost areas. [ABSTRACT FROM AUTHOR]

The availability of high-quality aggregate for infrastructure development in Canada has significantly decreased. This reduction has posed significant challenges, particularly in large urban areas across Canada. Moreover, exploring the potential of incorporating innovative by-products into pavement structures has displayed potential advantages in technical, economic, and environmental aspects. The methodology presented in this paper is based on several research projects from over the past twenty years. This case study is based on the several research projects that have been conducted at the Centre for Pavement and Transportation Technology (CPATT) in Canada. The focus of this paper is developing a framework that can be used to evaluate the use of recycled materials in asphalt pavement. These include recycled concrete aggregate (RCA); recycled asphalt roof shingles (RAS); recycled crumb rubber (RCR); and recycled asphalt roof shingles (RAS) in asphalt pavement. In addition, the use of RCA in concrete pavement will also be evaluated. In addition, the use of RCA in concrete pavement will also be evaluated. A methodology and strategy for implementing these materials and designs into specifications, while also managing risk, are outlined. Finally, the work presents a life cycle assessment analysis, including the analysis of cost and sustainability. Overall, the paper illustrates the process of evaluating products, technologies, and designs from technical, economic, and environmental viewpoints, and then implementing them in a robustly engineered way. Generally, the collected data results from the lab, field performance of the test sites, and sustainability and Life Cycle Cost Assessment (LCCA) analyses are very promising. For example, the Hot Mix Asphalt (HMA) pavement design with a 40% RAP was the most environmentally friendly. Meanwhile, it was determined that the HMA mix comprising 20% RAP and 20% Crumb Rubber Modifier (CRM) was found to be the most creative and environmentally friendly option. According to another study, higher storage durations were shown to improve RAP and virgin binders' blending, thereby raising the general quality of HMA and RAP mixtures. Furthermore, the study discovered that mixtures containing various types of untreated CRCA in different amounts had higher Indirect Tensile Strength (ITS), rutting resistance, and stiffness modulus than the control mix, which contained 0% coarse recycled concrete aggregate (CRCA). This suggests that the effective utilization of recycled materials is a viable approach with the capacity to significantly enhance the adoption of recycled components in asphalt pavements. [ABSTRACT FROM AUTHOR]

Accurate recognition and location of pavement manholes are of great significance for pavement maintenance. This paper proposes an improved You only look once X (YOLOX) for automated detection of manholes on asphalt pavements. The proposed model improves the performance of the YOLOX model in two respects. First, the channel attention mechanism is introduced to enhance the model's adaptive feature refinement; second, a microscale detection layer is deployed in the YOLOX model to extract more essential and distinct features. The experimental results are impressive, with the improved YOLOX achieving an F1 score and overall intersection-over-union of 98.14% and 91.61%, respectively, on 250 testing images, surpassing other state-of-the-art models such as YOLOv4, Faster R-CNN, EfficientDet, and the original YOLOX. To demonstrate robustness of the proposed model, the improved YOLOX is further applied to process manhole images taken randomly by a smartphone, which differ significantly from those acquired by a laser imaging system. It is found that the improved YOLOX can also yield similar detection efficiency in different scenes, which indicates the proposed model has a strong generalization ability. Particularly, the average frame per second (FPS) of the improved YOLOX is approximately 50.74 FPS using a modern graphic processing unit (GPU) device, implying the promising potential of the proposed model in supporting real-time automated detection of pavement manholes. [ABSTRACT FROM AUTHOR]

Pixel-level detection of expansion joints on complex pavements is significant for traffic safety and the structural integrity of highway bridges. This paper proposed an improved HRNet-OCR, named as expansion joints segmentation network (EJSNet), for automated pixel-level detection of the expansion joints on asphalt pavement. Different from the high-resolution network (HRNet), the proposed EJSNet modifies the residual structure of the first stage by conducting a Conv. + BN + ReLU (convolution + batch normalization + rectified linear unit) operation for each shortcut connection, which can avoid the network degradation. The feature selection module (FSM) and receptive field block (RFB) module are incorporated into the proposed EJSNet model to learn and extract the contexts at different resolution levels for enhanced latent representations. The convolutional block attention module (CBAM) is introduced to enhance the adaptive feature refinement of the network. Moreover, the shared multilayer perceptron (MLP) architecture of the channel attention module (CAM) is also modified in this paper. Experimental results demonstrate that the F-measure and intersection-over-union (IOU) attained by the proposed EJSNet model on 500 testing image sets are 95.14% and 0.9036, respectively. Compared with four state-of-the-art models for semantic segmentation (i.e., SegNet, DeepLabv3+, dual attention network (DANet), and HRNet-OCR), the proposed EJSNet model can yield higher detection accuracy on both private and public datasets. [ABSTRACT FROM AUTHOR]

The low-altitude technology of unmanned airborne infrared detection system is used to effectively monitor the temperature segregation in the paving stage and realize the temperature uniformity control of asphalt pavement construction. The image mosaic method can splice two images with overlapping areas together to form a panoramic image. In order to solve the problems of long time-consuming and low accuracy of aerial image mosaic algorithm, the low-temperature area of the whole pavement can be obtained quickly and accurately. In this paper, threshold segmentation technology is introduced to convert the image captured by the unmanned aerial vehicle (UAV) into a binary greyscale image so as to compensate for the mosaic error caused by temperature difference. In order to improve the efficiency and accuracy of splicing, a reference plate is used, which can provide enough feature points for splicing. Finally, the image mosaic method proposed in this paper can quickly obtain the image of the whole low-temperature area of the newly paved asphalt pavement, which has practical value and positive significance for the quality control of asphalt pavement. [ABSTRACT FROM AUTHOR]

Oxidative aging of asphalt binders seriously affects the durability of asphalt pavements and causes early damage. Hence, appropriate indices that could track the extent of asphalt binder aging are of great importance to the material selection, design, and maintenance of asphalt pavement. This paper aims to select the applicable rheological and chemical indices to characterize oxidative aging degrees of polymer-modified asphalt binders. Styrene-butadiene-styrene (SBS)-modified asphalt and two kinds of SBS/crumb rubber compound-modified asphalt were subjected to a rolling thin-film oven (RTFO) test and 20 h, 40 h, and 60 h pressure aging vessel (PAV) tests. Various rheological experiments at different temperature ranges were applied to obtain rheological indices, including complex shear modulus (|G*|), G-R parameter, and J' (derivative of creep compliance). A range of chemical indices were determined by Fourier transform infrared spectroscopy (FTIR). The results indicate that the carbonyl index is strongly correlated with PAV aging time. |G*| at 52°C and J' values at -18°C are the two most promising rheological indices to track the oxidative aging of asphalt binders and relate well to the chemical changes induced by PAV aging. In addition, the G-R parameter is problematic in some instances when used as the rheological index because its accuracy depends on the precise fitting of master curves. [ABSTRACT FROM AUTHOR]

High-temperature hazards of asphalt pavement and pollution from car exhaust are two major problems that need to be solved in road construction. In this paper, a multifunctional composite coating has been prepared from the perspective of reducing road temperature and car exhaust degradation. The principle of heat-reflecting coating is used to reduce the road surface temperature. At the same time, the TiO2 aqueous solution with photocatalytic degradation effect is added to the heat-reflective coating material to achieve the purpose of degrading automobile exhaust degradation, creating a new type of multifunctional coating that has both cooling and exhaust degradation effects. In addition, by changing the amount of carbon black, a multi-functional coating with the best coloring is selected, so that it has better functionality and has the most suitable shade for the road surface. Finally, the cooling effect and the exhaust gas reduction effect are examined through indoor and outdoor tests and the slip resistance of the coating is tested using the pendulum method. The results show that the functional coating group has a certain ability of cooling and exhaust gas degradation compared to the normal control group without coating. For the functional coating group with different carbon black content, the functional coating (G2) with 0.9% carbon black content has the strongest overall functionality. The cooling and exhaust gas reduction effects proved to be the best. The surface cooling rate is 5.4°C, while the internal cooling rate is 4.3°C. The cumulative degradation efficiency of CO and NO is found to be 27.77%, and 73.75%, respectively. [ABSTRACT FROM AUTHOR]

The curing process of cold recycling mixture with emulsified asphalt is a process of emulsion breaking, water evaporation, and cement hydration, resulting in adhesion development and strength formation. There are many factors that affect this process, including curing temperature, curing time, reclaimed asphalt pavement (RAP) contents, and cement contents. However, the evaluation of the promoting effect of each factor is still not quite clear. Hence, in this paper, the curing temperature, curing time, and RAP contents were discussed to find out the dominating factor in this process. The development of moisture loss and indirect tensile strength (ITS) was measured and analyzed through establishing prediction models between them and curing time. Besides, the functional relationship between moisture loss and ITS was also analyzed to evaluate the promoting effect of each factor. The results showed that the curing temperature has a certain impact on the development of moisture loss and ITS and an increase in curing temperature would accelerate the reaction rate, while RAP contents can hardly affect this process. Through functional relationship between moisture loss and ITS, it was found that the development of early strength and adhesion was dominated by ITS despite the increase of curing temperature and RAP contents. Expanding the hydration effect of cement could promote the curing process. However, this dominating role weakened at higher temperature and moisture loss should be treated more carefully. [ABSTRACT FROM AUTHOR]

This paper was to develop a prediction framework for obtaining the rheological properties of extracted and recovered asphalt binders utilizing mixture performance and other factors such as in-place air voids, pavement structure, traffic level, and aging duration. A total of 21 field projects consisting of 66 pavement sections were included in the analysis, which were located in different climatic zones with various RAP contents, traffic levels, pavement structures, pavement age, and material properties. Results indicate that the neural network can be successfully adopted to predict cracking-related binder properties consisting of effective asphalt binder, G*sin(δ) and binder fracture energy, and rutting-related binder properties including high temperature performance grade (PG), MSCR Jnr3.2, and R3.2. Both prediction and validation models worked well for pavement sections with varied contents of RAP when new data was introduced. [ABSTRACT FROM AUTHOR]

The low-temperature performance of asphalt mixtures was a critical factor that investigated the thermal cracking of asphalt pavement in cold regions of the world. Many scholars have affirmed that the failure temperature of the thermal stress restrained specimen test (TSRST) could be an index to evaluate the low-temperature performance of asphalt mixtures. However, the influence of transient heat transfer on asphalt mixtures was ignored in the TSRST, potentially leading to inaccurate evaluation indexes for low-temperature performance. In this paper, the thermal contraction strain and the effective temperature of asphalt mixtures were analyzed considering transient heat transfer in the TSRST. First, the effective temperature and the thermal contraction strain were captured during the cooling process. Then, the calculation model of thermal stress was improved. The pseudo strain energy density was calculated based on the energy theory. Finally, the calculation model of thermal stress was evaluated with the failure temperature as the standard. The difference between the failure temperature calculated by the calculation model of thermal stress without considering the transient heat transfer and the failure temperature calculated considering the transient heat transfer was at least 2°C. [ABSTRACT FROM AUTHOR]

Asphalt binder is the most common material used in road construction. However, the need for more durable and safer pavements requires a better understanding of asphalt's aging mechanisms and how its characteristics can be improved. The current challenge for the road industry is to use renewable materials (i.e., biomaterials not subjected to depletion) as a partial replacement for petroleum-based asphalt, which leads to reducing the carbon footprint. The most promising is to utilize biomaterials following the principles of sustainability in the modification of the asphalt binder. However, to understand whether the application of renewable materials represents a reliable and viable solution or just a research idea, this review covers various techniques for extracting bio-oil and preparing bio-modified asphalt binders, technical aspects including physical properties of different bio-oils, the impact of bio-oil addition on asphalt binder performance, and the compatibility of bio-oils with conventional binders. Key findings indicate that bio-oil can enhance modified asphalt binders' low-temperature performance and aging resistance. However, the effect on high-temperature performance varies based on the bio-oil source and preparation method. The paper concludes that while bio-oils show promise as renewable modifiers for asphalt binders, further research is needed to optimize their use and fully understand their long-term performance implications. [ABSTRACT FROM AUTHOR]

The dynamic modulus of asphalt mixture is an important factor in the design of asphalt pavement, and many scholars have proposed different models for estimating the dynamic modulus of asphalt mixture, but there are almost no studies on the prediction of the dynamic modulus of semi-flexible materials. In order to analyze and estimate the dynamic modulus of semi-flexible materials, we set up a high-performance cementitious paste (HPCP) semi-flexible material and a reference group Stone Mastic Asphalt (SMA-16) under multiple conditions, first measured its dynamic modulus in the laboratory, and analyzed the dynamic modulus characteristics of the material, and then used the equation the estimation equation proposed by Witczak et al. (Witczak1-37A) as a benchmark to introduce a new parameter, grouting mass ratio (Pb) to develop a Witczak- G prediction model to compare and validate the predicted dynamic modulus with the measured values. The results show that compared with SMA-16, HPCP semi-flexible material exhibits higher dynamic modulus and lower phase angle, and its temperature sensitivity and deformation resistance are significantly better than those of SMA-16. Under the influence of porosity and Pb factor, the dynamic modulus is positively correlated with both factors, and the phase angle increases first and then decreases, showing strong elastic properties. In this paper, we propose a dynamic modulus prediction model based on viscosity and Pb, Witczak-G, which predicts the highest coefficient of determination (R2) of the predicted dynamic modulus as high as 0.99 after initial fitting and validation, which indicates that the Witczak-G model is suitable for predicting the dynamic modulus of semi-flexible materials injected with HPCP. [ABSTRACT FROM AUTHOR]

If HT ht , additional tests should be conducted. These factors include the asphalt amount, physical properties of asphalt, the gradation and characteristics of aggregates, and asphalt-aggregate interface characteristics ([3]; [4]). It can be seen that similar to 70# base asphalt, the rutting resistance at high temperatures also can be improved using the elaborated mixing process proposed in the original paper for SBS-modified asphalt and hard-grade asphalt. [Extracted from the article]

In the process of asphalt pavement maintenance management, the technical condition of the pavement is accurately predicted, its performance trend is predicted, and the right time is chosen to take targeted maintenance measures that will play a multiplier role, so predicting the technical condition of the pavement is important significance. This paper mainly studies the cluster dimensionality reduction evaluation method of the technical condition of expressway asphalt pavement. This paper summarizes the experience of regular highway inspection data inspection and analysis, and mainly studies the standardized analysis method of highway pavement inspection data, aiming to meet the data requirements at all levels through effective data analysis indicators. The experimental data in this paper show that the driving quality of the two-way pavement is good, the total average SRI is 91.2, and the evaluation is "excellent," and the left width is slightly better than the right width; the transverse crack penetration of most reconstructed road sections is greater than 0.4, indicating that the transverse crack penetrates the road surface more serious. The experimental results of this paper show that the technical status of asphalt pavement based on cluster analysis has practical significance, and the analysis results show that the treatment effect is ideal. [ABSTRACT FROM AUTHOR]

The development of the transportation industry has led to an increasing number of overloaded vehicles, which reduces the service life of asphalt pavements. Currently, the traditional vehicle weighing method not only involves heavy equipment but also has a low weighing efficiency. To deal with the defects in the existing vehicle weighing system, this paper developed a road-embedded piezoresistive sensor based on self-sensing nanocomposites. The sensor developed in this paper adopts an integrated casting and encapsulation technology, in which an epoxy resin/MWCNT nanocomposite is used for the functional phase, and an epoxy resin/anhydride curing system is used for the high-temperature resistant encapsulation phase. The compressive stress-resistance response characteristics of the sensor were investigated by calibration experiments with an indoor universal testing machine. In addition, the sensors were embedded in the compacted asphalt concrete to validate the applicability to the harsh environment and back-calculate the dynamic vehicle loads on the rutting slab. The results show that the response relationship between the sensor resistance signal and the load is in accordance with the GaussAmp formula. The developed sensor not only survives effectively in asphalt concrete but also enables dynamic weighing of the vehicle loads. Consequently, this study provides a new pathway to develop high-performance weigh-in-motion pavement sensors. [ABSTRACT FROM AUTHOR]

The safety of the airport runway, as an infrastructure, is of considerable concern. The existing research has problems of hysteresis and unreasonable load application. In this paper, ANSYS is used to construct a coupled tire–pavement model to study the dynamic characteristics of airport asphalt pavements under impact loading. Taking the Boeing 737–800 as an example, the impact of an aircraft landing on an airport pavement is simulated by applying a dynamic load to the landing gear. The effects of tire pressure, landing pitch angle, and sinking speed on the dynamic response of the airport runway are investigated. The effects of each factor of the airport pavement are analyzed by comparing the maximum effective stress, effective strain, and displacement in the vertical direction at the same position of different structures. The results show that when the tire pressure is 2.0 MPa, the maximum values of effective stress, effective strain, and vertical displacement increase by 29.8%, 19.1%, and 22.2%, respectively, compared with 1.0 MPa. The maximum values of effective stress, effective strain, and vertical displacement at the 3.0 m/s sinking speed increase by 25.2%, 93.1%, and 77.1%, respectively, compared with that at the sinking speed of 1 m/s, which indicates that the effect of sinking speed on the dynamic response of the pavement is more significant. However, the change in the landing pitch angle has little impact on the response parameters of the pavement. Meanwhile, the flexural tensile stress at the bottom of the surface and the equivalent effect at the top of the soil foundation must be considered in the design of the airport pavement structure. [ABSTRACT FROM AUTHOR]

Asphalt mixture is a temperature sensitive material. With the change of external environment temperature, asphalt pavement is prone to temperature-related diseases. Adding phase change material (PCM) to asphalt pavement to adjust pavement temperature is one of the effective methods at present. At present, there are many types of research on PCMs, but the research on PCMs added to the pavement structure is very scarce. In this paper, through the temperature test of rutting plate specimens with different layer combinations, the cooling effect of pavement structure combinations with PCMs added to different layers (upper layer, middle layer, and bottom layer) in pavement structure under different illumination times are discussed. Through the self-designed environmental simulation box, the real-time monitoring of the temperature of different layers in the pavement structure is realized. The cooling effect between different layers in different phase change pavement structure combinations is analyzed, and compared with each layer of ordinary pavement structure, and the best addition method is obtained for phase change materials, which provides a certain reference for the construction and specific application of PCM asphalt pavement, and made important contributions to the development of asphalt cooling pavement. The results show that the PCM can effectively reduce the temperature of each layer of the pavement structure. Under different illumination durations, the cooling effect of the samples with PCM in the upper layer was the worst. The samples with phase change material in the middle layer had the best cooling effect in the upper and middle layers of the pavement. The addition of phase change material to both the upper and middle layers had the most obvious cooling effect on the lower layer of the pavement. Therefore, combined with the comprehensive consideration of economy and cooling effect, the comprehensive cooling effect of adding PCMs to the middle surface layer is the best. It is recommended to add phase change materials to the middle surface layer during asphalt cooling pavement construction. [ABSTRACT FROM AUTHOR]

Low temperature cracking (LTC) distress on pavement seriously affects road life. This paper finished a literature review of the research on the mechanism of LTC of asphalt composites (asphalt composites refers to asphalt binder and asphalt mixture in this article), test methods, factors contributing to LTC, measures to prevent and control the distress, and prediction of LTC in asphalt pavements. The following conclusions were obtained: the cracking mechanism of asphalt mixtures needs to be further revealed by means of simulation at the micro level, the BBR and 4 mm plate test (by DSR) methods are currently optimal, and a correlation between asphalt and asphalt mixture evaluation indexes needs to be established. Sensitivity analyses are needed for the factors affecting LTC of asphalt mixtures. It is necessary to calculate the contribution of each factor to the LTC of asphalt mixtures. The aim is to propose targeted improvement measures for the most unfavourable factors, as well as to carry out research and development of key materials for anti-cracking. Measures for the prevention and control of LTC of asphalt pavement are analyzed and discussed. Existing researches on the prediction of LTC of asphalt pavements is discussed. It is necessary to analyse the mechanical response of asphalt pavement, the damage process and the sensitivity of anti-cracking parameters on the basis of considering the complex geometrical characteristics and material properties of asphalt pavement materials. Finally, the mechanism of LTC, evaluation methods, factors influencing LTC, and remedial measures for asphalt composites were summarized, and future research prospects were suggested. This paper provides theoretical support for the further solution of LTC distress of asphalt pavement, which is effective on the improvement of pavement life. [ABSTRACT FROM AUTHOR]

In order to explore the aging performance attenuation mechanism of 90# and SBS (styrene-- butadiene--styrene block copolymer) modified asphalt under the large temperature difference and strong ultraviolet radiation in the Tibetan area, this paper adopts the outdoor natural exposure aging (NEA) condition in the Tibetan area. Scanning calorimetry and thermogravimetric analysis techniques were used to test and analyse the permanent deformation resistance and thermal stability of two asphalts with different aging times (0 month (0M), April (4M) and 8 months (8M)) to study the on-site aging mechanism of asphalt in Tibetan areas. The results show that with the prolongation of NEA time, the non-recoverable creep compliance, polymer area and glass transition temperature of the two asphalts decrease, while the average recovery rate and deformation temperature increase, and the aging degree gradually deepens. Under the special outdoor conditions in Tibetan areas, the permanent deformation resistance and thermal stability of SBS modified asphalt are better than 90# asphalt. The research results explored the aging and decay mechanism of the two asphalts from the macro and micro perspectives, which provided theoretical support for the research and development of anti-aging technology in Tibetan areas and guaranteeing the road performance of asphalt pavement in the whole life cycle. [ABSTRACT FROM AUTHOR]

Featured Application: This paper proposes a novel method for transverse cracking detection based on vehicle vibration response. Transverse cracking is thought of as the typical distress of asphalt pavements. A faster detection technique can provide pavement performance information for maintenance administrations. This paper proposes a novel vehicle-vibration-based method for transverse cracking detection. A theoretical model of a vehicle-cracked pavement vibration system was constructed using the d'Alembert principle. A testing system installed with a vibration sensor was put in and applied to a testing road. Then, parameter optimization of the Short-time Fourier transform (STFT) was conducted. Transverse cracking and normal sections were processed by the optimized STFT algorithm, generating two ideal indicators. The maximum power spectral density and the relative power spectral density, which were extracted from 3D time–frequency maps, performed well. It was found that the power spectral density caused by transverse cracks was above 100 dB/Hz. The power spectral density at normal sections was below 80 dB/Hz. The distribution of the power spectral density for the cracked sections is more discrete than for normal sections. The classification model based on the above two indicators had an accuracy, true positive rate, and false positive rate of 94.96%, 92.86%, and 4.80%, respectively. The proposed vehicle-vibration-based method is capable of accurately detecting pavement transverse cracking. [ABSTRACT FROM AUTHOR]

The subgrade soil of asphalt pavement is significantly susceptible to changes in moisture content, and therefore many projects introduce polymer-based reinforcement to ensure soil performance. This paper aims to incorporate a variable representing the dry–wet cycle into the prediction model of resilient modulus of polymer reinforced soil. The polymer adopted is a self-developed subgrade soil solidification material consisting of sodium dodecyl sulfate and polyvinyl oxide. The current resilient modulus prediction model is improved, notably involving the effects of the dry–wet cycle. Combined with finite element method (FEM) analysis, the actual stress state of pavement and the coupling effect of dry–wet cycle and vehicle load on the resilient modulus are studied. The deterioration in resilient modulus with the variation in seasonal climate and load response is also investigated. Results show that the deviator stress is negatively correlated with the resilient modulus while the bulk stress has a linearly positive relation. The decreasing rate at low deviator stress is larger than that at the high level. Moreover, the dry–wet cycle can reduce the resilient modulus and the reducing amplitude is the largest at the first dry–wet cycle. FEM analysis shows that the middle position of the subgrade slope has the largest initial resilient modulus with decreasing amplitude in the first year of dry–wet cycles, while the upper position shows a smaller change. The variation in resilient modulus is closely related to the changes in cumulative volumetric water content. Considering that different positions of subgrade bear the external vehicle load, the equivalent resilient modulus is more realistic for guiding the subgrade design. [ABSTRACT FROM AUTHOR]

Rutting is one of the major asphalt pavement distresses that could cause hydroplaning and lead to roadway safety concerns on a rainy day. However, there is still no theoretical methodology with simulation to evaluate and predict the driving safety caused by rut-induced hydroplaning using vehicle dynamics. This paper proposes a methodology, based on a new developed "vehicle-water-filled rutting" open-loop vehicle dynamics model analyzed by CarSim (a professional vehicle dynamic software), to simulate and compute the impact of unbalanced water-filled rutting on driving stability/safety with a special focus on the vehicle's lateral dynamic stability, including lateral offset and lateral acceleration. Analysis results show the following: (1) The unbalanced water depths in left rutting and right rutting lead to the different friction between left rutting and right rutting and make the vehicle wander left and right uncontrollably along the roadway. (2) When the vehicle speed is greater than 80 km/h and the rutting width exceeds 0.7 m, the unbalanced water-filled rutting begins to affect the vehicle's lateral stability apparently and very likely threaten the driver's life. (3) By computing the vehicle's lateral offset and acceleration in different water widths and lengths in the hydroplaning situation, this paper proposes the rutting width and length thresholds for vehicle oversteer and instability, based on which the vehicle risk level is proposed, RISK I is the situation where vehicle's lateral offset exceeds 1.025 mm which likely causes vehicle running into the adjacent lane (the danger can be avoided if there is no vehicle in the adjacent lane), RISK II is the situation where the vehicle's tires begin to work into the nonlinear zone (the vehicle's lateral acceleration exceeds 0.4 g) with the increase of rutting width and length, which makes the vehicle lose controls irreversibly for drivers, and this situation should arouse more concerns for transportation agencies. The proposed methodology would enable transportation agencies to predict the security risk of rutting and play a vital role for transportation agencies to scientifically establish the relevant specifications (e.g., rutting maintenance) that proactively trigger the maintenance and rehabilitation to prevent potential safety concerns from happening. Recommendations on future researches, including taking braking stability and real rutting conditions of the proposed model into consideration, are also continued in the future study. [ABSTRACT FROM AUTHOR]

The objective of this paper is to present a novel approach for the continuous monitoring of pavement condition through the use of combined piezoelectric sensing and novel condition-based interpretation methods. The performance of the developed approach is validated for the detection of bottom-up fatigue cracking through full-scale accelerated pavement testing (APT). The innovative piezoelectric sensors are installed at the bottom of a thin 102 mm (4 in.) asphalt layer. The structure is then loaded until failure (up to 1 million loading cycles in this study). The condition-based approach, used in this work, does not rely on stain measurements and allows users to bypass the need for any structural or finite-element models. Instead, the data compression approach relies on variations in strain energy harvested by smart sensors to track changes in material and structural conditions. Falling weight deflectometer (FWD) measurements and visual inspections were used to validate the observations from the sensing system. The results in this paper present a first large-scale validation in pavement structures for a piezopowered sensing system combined with a new response-only based approach for data reduction and interpretation. The proposed data analysis method has demonstrated a very early detection capability compared to classical inspection methods, which unveils a huge potential for improved pavement monitoring. [ABSTRACT FROM AUTHOR]

This paper aims to reveal the interaction relationship between microcracks and macrocracks and the influence of the interaction on the crack propagation behavior. A theoretical model of asphalt concrete was established for the interaction between microcracks with different crack densities and a macrocrack. And a meso-structure model of AC-13 dense-graded asphalt concrete was established by combining the Talyor medium method and the DEM (discrete element method). Macro and micro parameters, such as the stress–strain characteristics, crack evolution parameters, and crack tip stress field, were obtained through a semi-circular bend virtual test and used to study the characteristics of crack propagation under the interaction between microcracks and the macrocrack. The results indicate that the interaction has an effect throughout the process of asphalt concrete damage, and shows shielding and acceleration effects as the microcrack density changes. When the microcrack density is low (f3 ≤ 0.8), the crack propagation process, which is affected by the interaction effect, exhibits significant differences, and the interaction effect shows the shielding effect. When the microcrack density is high (f3 > 0.8), the fracture stage is mainly affected by the interaction effect, which shows the acceleration effect. The results provide a predictive theoretical and numerical model for low-temperature cracking of asphalt pavement, and theoretical support for the design, maintenance, and upkeep of long-life pavement. [ABSTRACT FROM AUTHOR]

This paper presents a specific 3D computational fluid dynamics model to quantify the effects of the combustion of asphalt road pavement on user safety in the event of a fire in a bi-directional road tunnel. Since the consequences on tunnel users and/or rescue teams might be affected not only by the tunnel geometry but also by the type of ventilation and traffic flow, the environmental conditions caused by the fire in the tunnel under natural or longitudinal mechanical ventilation, as well as congested traffic conditions, were more especially investigated. The simulation results showed that the combustion of the asphalt pavement in the event of a 100 MW fire, compared to the case of a non-combustible road pavement, caused (i) an increase in smoke concentrations; (ii) a greater number of users exposed to the risk of incapacity to escape from the tunnel; (iii) a more difficult situation for the firefighters entering the tunnel upstream of the fire source in the case of natural ventilation; (iv) a higher probability of the domino effect for vehicles queued downstream of the fire when the tunnel is mechanically ventilated. [ABSTRACT FROM AUTHOR]

Overloaded traffic is one of the major effects that cause more early damage to asphalt pavement than regular traffic. Moving overloaded traffic not only needs to consider dynamic coefficient and axle load coefficient when carrying out pavement mechanics calculations, but also accelerates pavement failure and boosts the cost of construction and maintenance. Although asphalt pavement of a stabilized base with inorganic binder has a strong bearing capacity, the shortcoming of reflective cracking also seriously restricts its performance. This paper describes the mechanical response and crack propagation of asphalt pavement of stabilized base with inorganic binder which has a crack, under the coupling effect of moving overloaded traffic and temperature. Extended finite-element method (XFEM) was conducted to simulate reflective cracks propagating freely from a stabilized base with inorganic binder to asphalt overlay. Dynamic analysis was also carried out by varying the axle weight and tire pressure, which could help highway builders understand the stress distribution of pavement under design traffic and the crack propagation law of pavement structures. Results indicated that the mechanical response of asphalt pavement was comprehensively related to tire pressure, axial weight, and its active position and that overloaded traffic accelerates crack propagation more than regular traffic. This research achievement contributes to providing roadway engineers with a more profound perception to potentially advance pavement design practitioners for specific traffic characteristics. [ABSTRACT FROM AUTHOR]

Stone matrix asphalt and asphalt concrete mixture with 13.2 mm nominal maximum aggregate size (named SMA13 and AC13, respectively) are widely used in the surface course of asphalt pavement in China. Generally, the pavement performance of SMA13 is superior to that of AC13, while the cost of the former is significantly higher than that of the latter. The objective of this paper was to develop a new hot mix asphalt (named SMAC13) whose performance and cost are between SMA13 and AC13. A boundary sieve size (BSS) of 2.36 mm was selected between fine and coarse aggregates. Based on the union set of aggregate gradation ranges of SMA13 and AC13, the family of gradation curves in the forms of S shapes were designed in terms of the BSS passing rate. According to the evaluation of the skeleton interlock of coarse aggregate of the gradation curve family, the aggregate gradation range of SMAC13 was determined. Also, the performance of three kinds of asphalt mixtures were compared through laboratory tests. The results indicated that SMA13 shows the best rutting resistance, followed by SMAC13 then AC13, while in terms of low-temperature performance in resistance to cracking, the sequence is SMAC13, AC13, and SMA13. The sequence of water stability is AC13, SMAC13, and SMA13. Furthermore, the cost of SMAC13 is 25% less than that of SMA13. Therefore, SMAC13 can be used as an alternative for the surface course of asphalt pavement in terms of performance and cost. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive review of the use of life cycle cost assessment (LCCA) and life cycle assessment (LCA) methods for evaluating the sustainability and costs of using recycled materials in asphalt pavement rehabilitation projects. The review begins with an introduction to pavement rehabilitation strategies and the importance of choosing techniques based on thorough engineering and economic analyses. It then explores the different types of recycled materials that can be utilized, including reclaimed asphalt pavement, recycled concrete aggregate, and recycled asphalt shingles, discussing the key characteristics and properties of these materials based on previous laboratory studies. The review also examines the various rehabilitation methods that employ recycled content, such as cold in-place recycling, hot in-place recycling, and full-depth reclamation, providing a detailed breakdown of the construction, maintenance, and rehabilitation costs considered in LCCA and analyzing the environmental benefits of recycled material usage through a review of LCA techniques and criteria like carbon footprint reduction, impacts on air and water quality, and considerations of technological factors. Software tools for conducting LCA are compared and challenges to advancing the adoption of recycled materials are reviewed along with directions for future research efforts. The unique contribution of this work is its holistic assessment of LCCA and LCA methodologies to inform the sustainable and cost-effective deployment of recycled materials in asphalt pavement rehabilitation, a topic of growing importance for transportation infrastructure management. In summary, this current work provides a valuable review of how LCCA and LCA methodologies can assess the sustainability and costs of employing recycled content in asphalt pavement rehabilitation projects. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of freeze-thaw cycles on the performance of asphalt mixtures containing 60% rejuvenated asphalt pavement (RAP). Two rejuvenation processes, traditional and bio-graded recycling, are compared regarding high-temperature performance, low-temperature performance, dynamic stability, flexural tensile strength, split tensile strength, water stability, and fatigue performance after various freeze-thaw cycles. The results indicate that bio-graded rejuvenation, compared to traditional rejuvenation, effectively enhances the high-temperature performance, low-temperature performance, water stability, and fatigue performance after freeze-thaw cycles. Both rejuvenations initially meet the dynamic stability requirements but show a decreasing trend with increasing freeze-thaw cycles, with traditional rejuvenation exhibiting more severe degradation. The flexural tensile strength initially exceeds that of conventional asphalt mixtures but decreases significantly with freeze-thaw cycles, especially in traditional rejuvenation. Additionally, freeze-thaw action increases the internal void ratio, affecting water stability and anti-freezing ability, particularly in traditional rejuvenated mixtures. These findings underscore the impact of freeze-thaw cycles on rejuvenated asphalt mixtures and emphasize the importance of innovative rejuvenation techniques for sustainable pavement. [ABSTRACT FROM AUTHOR]

Self-melting ice asphalt pavement materials inhibit pavement freezing and improve driving safety. This paper aims to study the long-term salt release characteristics of self-melting ice asphalt mixtures and the impact on pavement after complete salt release. Firstly, a method to accelerate the rapid release of salt based on the Los Angeles abrasion tester. Then, long-term salt release patterns were elucidated under the influence of deicing agent dosage, type of asphalt, and type of gradation. Finally, a quantitative analysis of the pavement performance after complete salt release is conducted. The results indicate that the release efficiency of the Los Angeles abrasion tester method has increased by 91 times compared to the magnetic stirrer immersion flushing method and by 114 times compared to the natural soaking method. The SBS-modified self-melting ice asphalt mixture possesses a longer duration of salt release, but the uniformity of salt release is inferior. Salt release duration is directly proportional to the dosage of deicing agents. SMA-13 self-melting ice asphalt mixture exhibits poorer uniformity in salt release. After complete salt release, high-temperature stability of self-melting ice asphalt mixtures decreased by 31.6%, low-temperature performance decreased by 15.4%, water stability decreased by 26.7%, and fatigue life decreased by 35.9%. [ABSTRACT FROM AUTHOR]

In recent years, asphalt pavement has been subjected to varied environmental conditions during its service life, conditions that predispose it to deformation and cracking. To enhance the performance of asphalt pavement, rock asphalt has been selected as a modifier due to its good compatibility with virgin asphalt binder and its ability to improve the fatigue cracking resistance of asphalt mixtures. Although scholars have conducted some studies on rock asphalt mixtures, research on the fatigue and self-healing performance of these mixtures under conditions such as ultraviolet (UV) aging and freeze–thaw remains limited. This paper presents findings from a study that employs a combined fatigue-healing test to assess the impact of such complex environmental factors on the fatigue and self-healing properties of fine aggregate matrix (FAM) mixtures containing three types of rock asphalts, i.e., Buton, Qingchuan (QC), and Uintaite Modifier (UM). The analysis of fatigue-healing test results, grounded in viscoelastic continuum damage (VECD) theory, indicates that rock asphalt can extend the fatigue life of FAM mixtures, albeit with a concomitant decrease in their self-healing capabilities. The study further reveals that UV aging, freeze–thaw, and UV aging–freeze–thaw conditions all led to a diminution in the fatigue and self-healing properties of FAM mixtures. However, FAM mixtures containing rock asphalt demonstrated greater resilience against these reductions. Atomic force microscope (AFM) results indicate that UV aging reduced the number of bee-structures and enlarged their area, whereas the incorporation of rock asphalt enhanced the uniformity of these structures' distribution, thereby improving the fatigue cracking resistance of FAM mixtures. Fourier transform infrared spectroscopy (FTIR) analysis reveals that while UV aging increased the carbonyl and sulfoxide indices within the asphalt binder, rock asphalt is effective in mitigating this effect to a certain degree, thereby enhancing the aging resistance of FAM mixtures. [ABSTRACT FROM AUTHOR]

In recent times, circular economy initiatives in addition to the need for sustainable biomaterials have brought about several attempts at the eco-friendly, eco-sustainable and cost-effective production of asphalt pavements. It is an increasingly common practice in the asphalt industry to improve road pavement performance using additives to enhance the physico-chemical properties of bitumen, which performs the role of the binder in the asphalt mix. This paper evaluated the potential of a bio-based additive derived from olive leaf residue as a modifier and antioxidant agent for bitumen. Samples of neat, aged and doped aged bitumen were analyzed. In this study, the two bio-based additives were characterized in terms of phenol, chlorophyll, lignin and cellulose content, which was correlated with the mechanical properties of the tested samples. The mechanical properties of the neat, modified, aged and unaged samples were evaluated via Dynamic Shear Rheology. The bio-based additives proved to be promising and can improve the properties of bitumen binder and the performance of asphalt pavements in general. [ABSTRACT FROM AUTHOR]

Intelligent compaction (IC) has emerged as a breakthrough technology that utilizes advanced sensing, data transmission, and control systems to optimize asphalt pavement compaction quality and efficiency. However, accurate assessment of compaction status remains challenging under real construction conditions. This paper reviewed recent progress and applications of smart sensors and machine learning (ML) to address existing limitations in IC. The principles and components of various advanced sensors deployed in IC systems were introduced, including SmartRock, fiber Bragg grating, and integrated circuit piezoelectric acceleration sensors. Case studies on utilizing these sensors for particle behavior monitoring, strain measurement, and impact data collection were reviewed. Meanwhile, common ML algorithms including regression, classification, clustering, and artificial neural networks were discussed. Practical examples of applying ML to estimate mechanical properties, evaluate overall compaction quality, and predict soil firmness through supervised and unsupervised models were examined. Results indicated smart sensors have enhanced compaction monitoring capabilities but require robustness improvements. ML provides a data-driven approach to complement traditional empirical methods but necessitates extensive field validation. Potential integration with digital construction technologies such as building information modeling and augmented reality was also explored. In conclusion, leveraging emerging sensing and artificial intelligence presents opportunities to optimize the IC process and address key challenges. However, cooperation across disciplines will be vital to test and refine technologies under real-world conditions. This study serves to advance understanding and highlight priority areas for future research toward the realization of IC's full potential. [ABSTRACT FROM AUTHOR]

The large temperature differences between day and night in winter at plateau areas can lead to the reduction of skid resistance of roads. However, most of the traditional salt storage and deicing fillers are chlorides, and their long-term usage will cause damage to the ecological environment. In order to achieve green deicing of asphalt pavement, this paper developed efficient and environmentally friendly salt storage fibers for the anti-icing of asphalt pavement, and the optimal components of salt storage fibers were determined. On this basis, the morphology and rust resistance of salt storage fibers were characterized, and the ice suppression and deicing performances were also determined. The experimental results show that the optimal component ratio of anti-icing reagent for sodium acetate, potassium acetate and sodium formate follows 7∶2∶1 and the optimal component ratio of organic salt and fiber is 3∶1 , which can achieve a better ice-melting effect and sustainable economy. According to the scanning electron microscope (SEM) images, the salts in the salt storage fiber are fully absorbed, which has a certain slow-release performance due to the resin package. In addition, the effective anti-icing components of the salt storage fiber are less corrosive to the metal materials, and the asphalt mixtures doped with salt storage fibers can melt ice at the rate of (1,022 g/ h·m2) under relatively low temperatures. This can effectively weaken the freeze-bond strengths and ice–road interface adhesion. [ABSTRACT FROM AUTHOR]

During the compaction process of HMA pavement, it is common to spray cold water on the wheel of a road roller to prevent the mixture from sticking to the wheel, which might deteriorate the bonding strength between the asphalt binder and aggregate, and consequently lead to surface polishing of the pavement. This paper aims to demonstrate whether the water used during the compaction process affects the surface performance of HMA pavement. In this study, the black pixel ratio and mass loss ratio were used to evaluate the water effect on the surface performance of asphalt pavement, considering the water consumption, molding temperature and long-term ageing process. The test results indicated that the water used during the compaction process would increase the risk of surface polishing of HMA pavement. This adverse effect became more significant if the HMA samples were prepared using greater water consumption, a greater molding temperature and a long-term ageing process. Moreover, there exists a certain correlation between the black pixel ratio and mass loss ratio, and their relationships were demonstrated by the experimental results in this study. It is recommended that further research concentrates on the influencing mechanism and the treatment strategy for the adverse effect caused by the water used during the compaction process. The use of more types of asphalt binders, aggregate and methodologies is also recommended in further studies. [ABSTRACT FROM AUTHOR]

In order to develop high performance thermal reflective coating for asphalt pavement, this paper studied the effect of the ratio of functional fillers on thermal insulation performance, the effect of the ratio of binder materials on bond strength and the effect of the content of functional fillers on thermal insulation performance and bond strength, and then prepared the thermal reflective coating and evaluated its durability. The results show that, under different mass ratios of TiO2 and SiO2, the thermal insulation performance of the thermal reflective coating increases with the increase of TiO2 mass ratio. Under the same dosage of curing agent, the maximum bond strength is obtained when the dosage of toughening agent is 20%-30%. With the same amount of toughening agent, the maximum bond strength is obtained when the amount of curing agent is 30%-40%. With the increase of the content of functional fillers, the thermal insulation performance of the thermal reflective coating increases, and the bond strength decreases slowly at first and then rapidly. The thermal reflective coating was prepared according to the optimum ratio of each component. The wear rate of the coating increases with the increase of wear times, and the increase rate is fast in the early stage. The thermal insulation performance decreases linearly with the increase of wear rate. With the increase of wear times, the skid resistance first increases rapidly and then decreases slowly. [ABSTRACT FROM AUTHOR]

During its service life, asphalt pavement is affected by environmental factors such as heat, light, oxygen and moisture. The asphalt binder ages, resulting in a decrease in the performance of the asphalt pavement. Therefore, the development and application of an asphalt anti-aging agent is of great significance. In this paper, the road performance of the developed asphalt binder liquid anti-aging agent was verified in the two scales of asphalt binder and asphalt mixture, respectively. Firstly, a simple aging test method was proposed using needle penetration as the evaluation index. The aging time of the simple aging method was determined to be 20 h. Secondly, the addition of anti-aging agents improved the low-temperature performance of the asphalt binder and had a less adverse effect on the high-temperature performance. The test values of needle penetration and the ductility of the asphalt binder increased and the values of the softening point decreased. And the road performance of the anti-aging asphalt mixture basically met the specification requirements. The addition of the anti-aging agent improved the low-temperature performance of the aged asphalt mixture by 16%, which is of great significance for improving the service life of asphalt pavement. [ABSTRACT FROM AUTHOR]

Porous asphalt pavements are widely used in rainy and wet areas for their skid resistance, noise reduction, runoff minimization and environmental sustainability. Long-term moisture vapor erosion and the destabilization of large pore structures can easily result in pavement problems such as fragmentation, spalling, cracking, and excessive permanent deformation. To this end, four different preventive maintenance materials, including the rejuvenation (RJ), cohesion reinforcement (CEM), polymerization reaction, and emulsified asphalt (EA) types, were selected in this paper to improve the high-viscosity porous asphalt pavement. The effects of the different preventive maintenance materials on the temperature sensitivity, rheological properties and fatigue performance of high-viscosity modified asphalt were evaluated through temperature sweep, frequency sweep, multi-stress creep recovery (MSCR), linear amplitude sweep (LAS), and bending beam rheometer (BBR) tests. The results showed that the four preventive maintenance materials exhibit different enhancement mechanisms and effects. RJ improves the fatigue properties, deformation resistance and low-temperature cracking resistance of aged asphalt by adding elastomeric components; CEM materials are more conducive to increasing the low-temperature crack resistance of aged asphalt; while GL1 and EA improve the viscoelastic behavior of aged asphalt, but the effect of the dosing ratio needs to be considered. [ABSTRACT FROM AUTHOR]

Timely monitoring of pavement sub-surface layer thickness and condition evaluation is essential to ensure stable pavement performance and safety under heavy traffic loading. In addition, accurate estimation of pavement layer thicknesses is required for condition evaluation, overlay design/quality control assurance, and structural capacity evaluation of existing pavements to predict its remaining service life. Traditionally this vital information is ascertained through coring/drilling and visual inspections. In contrast to these current techniques, ground-penetrating radar (GPR) is a nondestructive technique gaining popularity in pavement asphalt layer thickness estimation and structural condition monitoring. Its high-quality data contains vital pavement condition information, and survey costs are reasonably economic. In this work, GPR data were acquired along a toll road in Queensland, Australia, using the GSSI 4-channel SIR30 GPR unit. Asphalt layer thickness information is considered an important input parameter for condition assessment, pavement performance, and lifetime modelling. This work presents an automated segmentation framework to evaluate pavement conditions for a large pavement network. The developed algorithm uses GPR asphalt thickness data as input and generates segments with decision boundaries utilising a cascaded k-means and DBSCAN approach that works in two steps: 1) centroid initialisation using k-means algorithm, 2) clustering using DBSCAN algorithm. Presented in this paper is the workflow of the cascaded method that is applicable to automated analysis of GPR asphalt thickness data. The performance of the cascaded kmeans and DBSCAN algorithm was evaluated in terms of entropy compared with traditional k-means and traditional DBSCAN algorithms. The results show that the proposed method outperforms its constituents. Based on the results of this study, the method presented in this paper is cost-effective, economical and robust for segmenting large pavement network with GPR data. [ABSTRACT FROM AUTHOR]