Hot in-place recycling (HIR) is a shallow in-situ rehabilitation technology designed to restore aged asphalt surface layers while minimizing material consumption and transportation demand. Although HIR demonstrates significant potential for low-carbon pavement maintenance, its environmental and economic advantages are highly sensitive to construction quality and process control. This review systematically synthesizes recent advances in HIR across process configurations, material systems, construction equipment, quality control mechanisms, performance evolution, service life prediction, and life-cycle sustainability assessment. The relationships between construction variables and pavement performance are organized through a staged linkage that connects heating uniformity, milling depth control, rejuvenator distribution, mixture homogeneity, compaction quality, and environmental conditions with mechanical properties, functional indicators, deterioration rate, and service life. Standardized quality control frameworks integrating input, process, output, and acceptance indicators are summarized. Furthermore, an integrated life-cycle sustainability assessment framework is discussed, emphasizing functional unit consistency, service-life normalization, user impacts, uncertainty propagation, and multi-criteria decision analysis. Research gaps remain in quantifying the link between heating quality and long-term performance, developing intelligent process monitoring, compiling long-term field-performance data, and supporting decision-making under uncertainty. This review provides a structured basis for quality-controlled, performance-based, and low-carbon application of HIR in asphalt pavement maintenance.

Incorporating reclaimed asphalt pavement (RAP) materials directly into a rotary drum dryer to mix with virgin aggregates in a high-heat environment will produce binder residue. The characterization and potential effects of this combustion residue on the properties of asphalt binders remain unclear. Therefore, this study obtained the combustion residue and clarified its effect on asphalt binder performance. Initially, the physicochemical, morphological, and elemental characteristics of combustion residue were determined. Subsequently, the effect of the combustion residue on asphalt binder properties was analyzed using the rotational viscosity (RV) test, dynamic shear rheometer (DSR), bending beam rheometer (BBR) equivalent test, and atomic force microscopy (AFM) test. The findings revealed that the addition of combustion residue significantly affected the viscosity and high-temperature performance of virgin binder, and had a slight effect on the low-temperature crack resistance. Asphalt binder containing combustion residue exhibited more elastic behavior than virgin binder at lower frequencies or higher temperatures, and had similar viscoelastic performance at higher frequencies or lower temperatures. Additionally, asphalt binder containing combustion residue had enhanced elastic recovery compared to virgin binder. The addition of combustion residue improved the fatigue life of asphalt binder by more than 30% and enhanced its resistance to crack propagation. Furthermore, it increased the surface microroughness and AFM modulus of the virgin binder.

Reliable traffic load characterization remains a critical challenge in many African countries due to the lack of continuous field measurements. This study developed an integrated dynamic traffic monitoring and weigh-in-motion system on representative highways in Kenya to obtain long-term, multi-source traffic data. Traffic operations were quantified across hourly, weekly, and monthly scales, including flow variability, vehicle class composition, axle loads, overload behavior, and speed distributions. Results indicate that the spatiotemporal characteristics of traffic volume show pronounced short-term fluctuations but strong long-term stability. Despite their lower proportion, multi-axle heavy trucks dominate structural loading, with overload ratios exceeding 80% and gross weights approaching 100 t. Over 60% of vehicles operate at medium-to-low speeds (20–60 km/h), extending load duration and increasing pavement damage potential. These combined effects indicate that average indicators alone underestimate true loading demand. The proposed framework provides field-based traffic load spectra and a transferable methodology for traffic monitoring and pavement design optimization across developing regions in Africa.

During the construction process of hot in-place recycled asphalt mixture, there are usually problems such as poor mixing uniformity, temperature and gradation segregation during paving, insufficient compaction at the starting position, and poor road performance of the mixture. To address the issues of construction quality and road performance in the process of hot in-place recycling of asphalt mixture, this study conducts research on improving the construction quality and road performance based on construction control through theoretical research, actual engineering projects, and laboratory tests. Changing the mixing method and increasing the mixing time can improve the mixing uniformity of the recycled asphalt mixture. Adding stirring devices on both sides of the paver and maintaining uniform rotation of the stirring devices can improve the temperature and gradation uniformity of the asphalt mixture. Increasing the proportion of new materials and raising the temperature at the starting position can improve the construction quality of the hot in-place recycled pavement at the starting position. Dynamically adjusting the amount of new materials and new asphalt based on the pavement condition and ensuring the paving temperature can improve the construction quality and road performance of the hot in-place recycled asphalt mixture. The construction control methods proposed in this study can provide theoretical basis and technical support for the construction of hot in-place recycled asphalt mixture.

In the production of hot recycled asphalt mixture, the mixing method and material characteristic are the decisive factors determining the quality and cost of the products. This study investigated the influence of flat-and elongated-shaped aggregate of different sizes on the temperature evolution and thermal equilibrium process of hot recycled asphalt mixture containing 30 % recycled asphalt pavement (RAP) under various mixing conditions. Digital models of real shaped aggregates were utilized to represent the new and RAP particles, and a horizontal mixing apparatus was designed to replicate the actual mixing environment in DEM. Meanwhile, conventional mixture samples were fabricated and digital image processing technology was employed to visualize the temperature evolution of recycled asphalt, thereby validating the simulation results. The simulation results have revealed that the temperature evolution of recycled asphalt mixture was divided into three distinct stages. The inclusion of flat-and elongated-shaped fine aggregates smaller than 4.75 mm was found to accelerate thermal transition within the mixtures. Moreover, the preheating temperature of RAP played a crucial role in governing the rate of thermal transfer between new and RAP particles. Experimental observations demonstrated a consistent trend with the simulation outcomes, confirming the validity and reliability of the numerical model. The findings of this research provide valuable insights into enhancing the effective utilization of RAP and reducing production costs in hot recycled asphalt mixture manufacturing.

Solvent-based cold-mix asphalt features low energy consumption and reduced emissions but suffers from insufficient early-age stiffness due to slow solvent volatilization. This study proposes a biological enhancement strategy in which a hydrocarbon-degrading strain (Acinetobacter halotolerans) is applied to the binder surface to accelerate the removal of light hydrocarbons. Gas Chromatography–Mass Spectrometry (GC–MS) analysis shows that the microorganisms selectively digest C6–C9 hydrocarbons, significantly reducing the total solvent content, with enhanced efficiency when glucose is supplied as a co-substrate. Rheological measurements confirm that microbial digestion markedly accelerates stiffness development and improves high-temperature deformation resistance during curing. Fourier Transform Infrared Spectroscopy (FTIR) further indicates an increase in oxygenated functional groups, consistent with a compositional shift toward heavier fractions after microbial action. Minor softening effects from microbial metabolites were observed, but their influence on the overall mechanical response is limited. These findings demonstrate a sustainable and effective bio-assisted pathway to enhance the early-age performance of solvent-based cold-mix asphalt.

Green ecology and energy conservation face growing challenges as lagging indicators in urban development and renewal. Cement concrete, the primary material carrier of urban civilization, imposes severe environmental pressures due to high carbon emissions from production. Concurrently, mounting solid waste generated from resource extraction and urban regeneration has overwhelmed conventional landfilling approaches, falling short of public demands for green, safe, and sustainable alternatives. Against this backdrop, alkali-activated materials (AAMs) have emerged as a promising substitute for cement-based composites, offering substantial potential for solid waste valorization, reduced carbon footprint, and competitive engineering properties. Transport infrastructure, a major consumer of construction materials, exhibits broad compatibility with varied material specifications, positioning it as an ideal platform for large-scale application of AAMs. However, current research on AAM remains predominantly focused on fundamental characteristics (e.g., mechanical performance, durability, and microstructure), leaving their systematic deployment in transport infrastructures critically underexplored, with no comprehensive review yet available to systematize this emerging domain. Therefore, this paper presents an overview on the composition, reaction mechanisms, and properties of AAMs, with a focus on their multifaceted applications in transport infrastructure (including pavements, road base, soil subgrade, precast components, and heavy metal immobilization), as well as the economic and environmental benefits. Meanwhile, the current technical challenges and future perspectives toward revolutionizing transport infrastructure with low-carbon AAMs are also discussed, providing strategic insights and practical guidance for sustainable transport infrastructure engineering.

As the highway networks continue to expand, the workload for pavement inspection tasks is rapidly increasing. However, existing pavement inspection methods struggle to reconcile the contradiction between obtaining rich pavement information and the associated high costs and low efficiency. This paper presents a low-cost and easy-to-deploy vision-based workflow for pavement 3D reconstruction under normal driving conditions. Pavement point clouds were obtained through feature extraction and matching, motion estimation, and 3D reconstruction. A point cloud processing workflow combining plane fitting and perspective correction to improve geometric consistency was proposed. Given the monotonous, repetitive, and low-texture characteristics of pavement scenes, this paper systematically evaluated the performance of multiple feature extraction and feature matching algorithms, including classic and deep learning-based methods. By comparing with manual measurement results and considering both reconstruction accuracy and quality, the optimal strategy was determined. The variation in model accuracy under different speeds was investigated through experiments. The results indicate that proposed workflow can maintain stable reconstruction quality without interrupting normal traffic, and the depth estimation accuracy is within engineering-level tolerance under our measurement protocol. This study enables the low-cost acquisition of 3D pavement information, which is crucial for evaluating pavement technical conditions. It provides a new pavement inspection and monitoring solution, particularly offering significant application value for the extensive network of low-grade pavements.

Long-life pavement has been introduced to address the urgent need for durable and reliable transportation infrastructure. This review overviews the development of aggregates for long-life pavements and summarizes future research directions. The review indicates that natural aggregates, being non-renewable resources, are steadily declining in availability and may need to meet future demands. Construction solid waste aggregates are rapidly developing, with fine separation of reclaimed asphalt pavement (RAP) and reinforcement of cement-based recycled aggregates serving as key strategies to enhance their application. Industry solid waste aggregates possess properties suitable for long-life pavements and offer additional functionalities such as cooling, conductivity, and reflectivity, demonstrating significant development potential. While artificial aggregates exhibit superior performance, their large-scale application requires consideration of economic and environmental impacts. Current aggregate evaluation methods need to address the needs of long-life pavements. Aggregate performance requirements should be graded based on mechanical stress and temperature distribution, with corresponding evaluation methods and indices developed. Evaluating the mechanical properties of aggregates should align more closely with actual stress states. Tests such as triaxial, repeated load, and wheel abrasion polishing are better suited for assessing the strength and durability of long-life pavement aggregates. Similarly, evaluating aggregates' physicochemical properties should be based on studies correlating these properties with road performance, with proposed evaluation criteria. Morphological characteristics of aggregates significantly influence asphalt mixture performance, and efficient evaluation of their profile, angularity, and texture will be a key focus of future research.

Using fine reclaimed asphalt pavement (RAP) to prepare recycled gussasphalt (RGA) can significantly enhance its recovery rate. However, the high RAP content and the additional aging that occurs during the mixing process can lead to unsatisfactory low-temperature performance of RGA. The incorporation of a rejuvenator is a widely accepted method for improving the low-temperature performance of recycled asphalt mixtures. However, there is a lack of systematic research on the application of rejuvenators in RGA. This paper examines the mechanisms through which rejuvenators influence the properties of RGA by analyzing their effects on both the asphalt and the mixture. The results indicate that the rejuvenator can significantly enhance the low-temperature performance and workability of RGA, as well as improve its fatigue resistance under conditions of large deformation. The addition of the rejuvenator does not compromise the high-temperature performance of RGA. This is because the rejuvenator enhances the compatibility between the modifier and asphalt, thereby alleviating the significant phase separation that occurs between the modifier and asphalt at elevated mixing temperatures. Furthermore, the high mixing temperature of RGA (which exceeds 220 ℃) can lead to significant thermal volatilization of the rejuvenator, which is primarily composed of light components with low boiling points. This volatilization can adversely affect the performance of the rejuvenator. When using rejuvenators in RGA, it is essential to appropriately increase the dosage to compensate for these volatilization losses.

In this research, a numerical simulation of recycled asphalt mixture was conducted, considering the morphology of irregular virgin and reclaimed asphalt pavement (RAP) aggregates using the 3D discrete element method (DEM). The shape of coarse aggregates was accurately captured through X-ray computed tomography and image processing technology. Clumps representing realistic coarse aggregates were generated in the DEM model based on aggregate gradation. The linear model, Burgers model, and linear parallel bond model were employed in the DEM model of the asphalt mixture. Laboratory indirect tensile (IDT) test results were compared and analyzed against those of the virtual specimen, confirming the accuracy of the established DEM model. The study preliminarily evaluated the influence of bonding parameters and RAP aggregate morphology on the DEM simulation. The findings revealed that both bonding parameters and RAP aggregate morphology significantly affect the outcomes of the virtual IDT test. The peak force of the IDT specimens increased as bonding parameters increased, while a rounder shape or poorer angularity of coarse aggregates tended to decrease the IDT strength of the asphalt mixture.

Epoxy asphalt (EA) is a high-performance pavement material typically produced by combining asphalt and epoxy resin. As early epoxy asphalt pavements near the end of their service life, the recovery of EA and its mixtures has become a significant challenge. Current recycling methods that repurpose epoxy asphalt mixtures as inert aggregates result in the waste of valuable resin resources. This paper reviews research on the recovery of epoxy resin (EP) and its composites to identify viable solutions for the pressing issue of epoxy asphalt recovery. Closed-loop recovery of EP, which can be categorized into source-based closed-loop recovery (SCR) and end-based closed-loop recovery (ECR), provides valuable insights for addressing this challenge. SCR focuses on designing new reversible EP and has been applied in research related to reversible EA. However, it proves ineffective for existing thermosetting EA. In contrast, ECR, which pertains to existing thermosetting EPs, has the potential to introduce amino, hydroxyl, carboxyl, and other reactive groups into the recovered thermosetting EA, thereby transforming it into active materials. Inspired by the recovery principles of ECR, this paper proposes a surface-activated recycling strategy for epoxy asphalt and its mixtures, and outlines the potential methods and future challenges.

Freeze-thaw cycles are the main cause of subgrade damage in cold regions. To investigate how straw fibers affect the road performance of reinforced black soil in these areas, this study conducted unconfined compressive strength (UCS), California bearing ratio (CBR), and resilient modulus (RM) tests, supplemented by CT scanning. The novelty lies in comparing coarse and fine straw fibers and establishing a freeze-thaw damage prediction model. It analyzed the effects of straw fiber types (coarse and fine) and contents (0, 0.5%, 1.0%, 1.5%, 2.0%, 2.5%) on the soil's mechanical properties and reinforcement mechanisms. Results showed that straw fibers enhance soil mechanics by distributing stress, limiting soil particle movement, inhibiting crack growth, and reducing porosity. Fiber content impacts the mechanical properties of reinforced soil more significantly than fiber type. The optimal fiber content for both coarse and fine straw fibers is 1%. At this content, the UCS of coarse fiber-reinforced soil (CFS) reached 1.11 MPa, a 32.14% increase compared to the reference group (B-0), and the RM reached 207.39 MPa, a 63.70% increase compared to B-0. Meanwhile, the UCS of fine fiber-reinforced soil (FFS) reached 1.01 MPa, a 20.24% increase, and the RM reached 150.33 MPa, an 18.66% increase. Freeze-thaw cycles degrade mechanical properties by weakening the bond between soil and straw fibers. As the number of freeze-thaw cycles increases, both the UCS loss rate and RM loss rate rise. FFS exhibits superior freeze-thaw resistance compared to CFS, due to its lower porosity and fewer cracks. The developed freeze-thaw damage evolution equation shows a strong fit (R-2 > 0.85) and applies to straw fiber-reinforced black soil under the conditions of this study. This research provides a theoretical basis for designing eco-friendly straw fiber-reinforced subgrades in cold regions.

Asphalt pavement structural design typically relies on empirical mechanical methods, with the layered elastic system widely used as the theoretical foundation for mechanical calculations. In the practical design process, the mechanical response of the pavement is influenced by various factors, including the pavement structure type, the loads form and size, and the interlayer bonding conditions. However, existing research has not yet systematically analyzed the specific impacts of these factors. The study explores the influence of various factors on asphalt pavement design using layered elastic system computations. By comparing the impacts of different factors on the mechanical characteristics of the pavement structure, the study identifies common patterns and clarifies the key areas and indicators in pavement design that are influenced by these factors. The results indicate that tensile stress is related to differences in modulus, and the mechanical characteristics differ across different structural types; the reduction in overall thickness and the load type coefficient affect the distribution of tensile and shear stresses. The findings provide theoretical support and reference for the optimization of mechanical calculations in asphalt pavement design.

Partial replacement of ordinary Portland cement (OPC) with fly ash (FA) and ground granulated blast furnace slag (GGBS) is a critical approach for low-carbon cementitious materials. However, the quantitative multi-scale synergistic mechanism of 1:1 FA–GGBS systems under wide replacement rates remains unclear. This work characterized the macroscopic performance (fluidity, 7 d and 28 d compressive strength) and microstructural characteristics (hydration products, pore structure, products morphology) of FA–GGBS composite cement mortars using TG-DSC, MIP, SEM-EDS and particle size analysis. A distinct positive synergistic effect between FA and GGBS was verified. This positive synergistic effect is reflected by the optimal balance between workability and mechanical performance at 20% replacement. With increasing OPC replacement, fluidity increased initially then stabilized, while 28 d compressive strength increased first and then decreased, peaked at 20% replacement, reaching 51.16 MPa (19.17% higher than the control). This optimal dosage yielded the closest particle packing to the Fuller curve and the highest packing density. The CH content was reduced by 20.65%, harmful pores (>50 nm) were notably diminished, and a denser, more uniform C-(A)-S-H gel interlocking matrix was formed. The synergy originates from the morphological, filling, hydration-coupling and interlocking effects. These findings systematically evaluate the performance of a fixed 1:1 FA-GGBS blend under the tested conditions and identify its optimal replacement dosage, providing a theoretical basis for industrial solid waste valorization and low-carbon cementitious material design.

To overcome the drawbacks of traditional trial-and-error (time-consuming and labor-intensive) and AI-based (complex parameters and low material specificity) methods in determining the preferred mix proportions of GGBS and FA cement-based composite cementitious materials, this study proposes a ΔS value comparison method as a supplementary screening tool, grounded in Fuller’s maximum density curve theory. Using P.O 42.5 Portland cement, S95 GGBS, and Class Ⅱ FA, this study quantified the deviation (ΔS) between the measured particle size distribution of composite powders (10%-35% GGBS and FA dosages) and the ideal Fuller curve. Macroscopic tests (fluidity, compressive strength) and microscopic analyses (MIP, TG-DSC, SEM) validated the method. Results showed that, under the conditions of this study, ΔS first decreased then increased within the GGBS or FA replacement series, reaching minima at 20% GGBS (ΔS = 1467) and 15% FA (ΔS = 1300), which indicates the preferred dosage, selected within the tested range and for the adopted raw materials. These preferred dosages correspond to a particle state closest to the ideal Fuller curve and potentially improved particle packing performance, yielding a 28 d compressive strength of 50.22 MPa (GGBS) and a 56 d compressive strength of 53.37 MPa (FA)-16.98% and 14.36% higher than the reference group-with improved fluidity. Microscopically, GGBS underwent hydration and FA exhibited pozzolanic reactions at these dosages. Both reactions consumed CH to generate additional C-S-H gel and densify the microstructure. A moderate-to-strong negative correlation (R² > 0.75) was observed between ΔS and compressive strength. The 95% confidence bands are added to the fitting curves to verify the robustness of this correlation. The results suggest that the reduction in ΔS reflects improved particle gradation, which is linked to optimized pore structure and further contributes to improved compressive strength. This work advances Fuller curve application to quantitative analysis within the tested cement-GGBS (or FA) system, providing a preliminary reference for mix proportion design and industrial solid waste utilization under the given material and test conditions.

Engineering systems increasingly rely on data-driven optimization and closed-loop decision-making. Accordingly, computational models in engineering are no longer only tools for forward analysis, but also need to support parameter updating, design optimization, and feedback decision-making. In contrast, existing pavement mechanics computation still mainly serves response prediction under given parameter conditions and lacks a dedicated differentiable physics solver that directly provides stable gradient information. To address this gap, this study develops ∂Pave, a differentiable physics solver for pavement mechanical response computation. ∂Pave builds on a spectral element forward solution framework for layered pavement systems under moving loads. The solver connects load, material, geometric, and evaluation parameters to explicit stages of an end-to-end differentiable spectral element method solution path. Within this unified physical framework, ∂Pave returns selected mechanical responses at specified points in the layered pavement coordinate system together with their gradients with respect to specified input parameters. This study verifies the computed gradients through examples involving multiple response quantities. The results show that the automatic differentiation gradients from ∂Pave are generally consistent with finite difference results. In multi-parameter joint differentiation tasks, the efficiency advantage of ∂Pave over parameter-by-parameter finite differences increases with the number of differentiated parameters. This study further illustrates the use of the same response-gradient interface in two gradient-driven pavement engineering workflows, namely pavement structural design optimization and measurement-point layout optimization for pavement inspection. The two examples use task-specific variables, objectives, constraints, and decision procedures outside the physics solver. They demonstrate that ∂Pave can serve as a reusable physics-based response-gradient provider for different pavement mechanics task formulations.

UV-triggered radical-induced cationic frontal polymerization enables epoxy/oxetane thermosets to continue curing after brief UV exposure. However, formulations that support faster front propagation do not necessarily maximize tensile strength. We combined single-factor screening, central composite design, desirability optimization, and orthogonal UV experiments to examine the relations among formulation, process, and properties. In situ infrared thermography recorded front propagation. A thermochemical finite-element model described the thermal field. Across the formulation space, FTIR-derived BADGE conversion poorly predicted tensile strength. The single-variable model gave R2 ≈ 0.08, while tensile strength ranged from 19.1 to 44.7 MPa as BADGE conversion ranged from 78% to 81%. The selected formulation yielded a front velocity of 51.6 mm·min−1, a tensile strength of 37.7 MPa, and a BADGE conversion of 82.3%. All three results were within the prediction intervals. UV wavelength, irradiance, and exposure time affected tensile strength and BADGE conversion. The steady front velocity changed by less than 10%. The model reproduced continued propagation after UV removal and the axial cooling gradient. The thermochemical analysis supported self-sustained propagation. These results establish a composition-resolved multi-response strategy. Composition determines the attainable properties, while UV settings tune ignition.

Highlights What are the main findings? A workflow encompassing low-cost and readily deployable acquisition, multi-class pavement distress automated segmentation, and geometric information extraction, based on point clouds. An end-to-end network for segmenting distress from pavement point clouds, incorporating a long-tail class imbalance mitigation strategy and a dual-stream feature fusion module. What are the implications of the main findings? Enables scalable, low-cost 3D pavement inspection and monitoring using consumer-grade imaging, reducing reliance on expensive scanning systems and improving deploy ability for routine inspections. Provides engineering-ready 3D distress outputs to support condition assessment, maintenance prioritization, and integration into intelligent pavement management workflows.Highlights What are the main findings? A workflow encompassing low-cost and readily deployable acquisition, multi-class pavement distress automated segmentation, and geometric information extraction, based on point clouds. An end-to-end network for segmenting distress from pavement point clouds, incorporating a long-tail class imbalance mitigation strategy and a dual-stream feature fusion module. What are the implications of the main findings? Enables scalable, low-cost 3D pavement inspection and monitoring using consumer-grade imaging, reducing reliance on expensive scanning systems and improving deploy ability for routine inspections. Provides engineering-ready 3D distress outputs to support condition assessment, maintenance prioritization, and integration into intelligent pavement management workflows.Abstract The application of 3D data in pavement inspection represents an emerging trend. Acquiring and measuring the 3D information of pavement distress enables a more comprehensive assessment of severity, thereby allowing for accurate monitoring and evaluation of the pavement's technical condition. Existing methods face challenges in high-cost pavement scanning and insufficient research on automated 3D distress segmentation. This study employed a consumer-grade action camera for data acquisition and constructed an engineering-aligned 3D point cloud dataset of pavements. Then a long-tail class imbalance mitigation strategy was introduced, integrating adaptive re-sampling with a weighted fusion loss function, effectively balancing minority class representation. The proposed network, named PointPaveSeg, was a dedicated point cloud processing architecture. A dual-stream feature fusion module was designed for the encoder layer, which decoupled geometric and semantic features to improve distress extraction capability. The network incorporated a hierarchical feature propagation structure enhanced by edge reinforcement, global interaction, and residual connections. Experimental results demonstrated that PointPaveSeg achieved an mIoU of 78.45% and an accuracy of 95.43%. In the field evaluation, post-processing and geometric information extraction were performed on the segmented point clouds. The results showed high consistency with manual measurements. Testing confirmed the method's practical applicability in real-world projects, offering a new lightweight alternative for intelligent pavement monitoring and maintenance systems.