Search Results (279)

Asphalt pavement on rigid base (cement concrete) differs significantly from traditional granular base pavement. To investigate its mechanical behavior, a viscoelastic–viscoplastic damage constitutive model for asphalt mixtures is proposed and verified. A user-material subroutine (UMAT) is developed to implement the model, and a three-dimensional finite element model is established to analyze pavement responses under various working conditions. Key numerical results include the following: the asphalt layer primarily experiences compressive–shear failure, with peak shear stress (τ₁₂) reaching 141.6 kPa under rigid base conditions; emergency braking increases τ₁₂ to approximately 270.3 kPa, a 91% increase; increasing vehicle speed from 15 m/s to 35 m/s raises τ₁₂ by 36.7%; based on stress analysis alone, the recommended asphalt layer thickness is between 0.10 m and 0.14 m, as thickness beyond 0.10 m yields diminishing stress reduction. The findings provide references for performance prediction, structural design, and material development of asphalt pavement on a rigid base. Full article

Road pavement rehabilitation increasingly incorporates innovative surface technologies aimed at improving pavement performance while reducing environmental impacts. In addition to conventional recycled asphalt pavement (RAP) maintenance strategies, advanced pavement surface systems such as reflective coatings, rejuvenator-based self-healing mixtures, and thin low-noise asphalt layers have been developed to enhance durability and functional performance. This study presents a comparative Life Cycle Assessment (LCA) of four pavement surface technologies using primary inventory data obtained from full-scale road sections. The systems evaluated include a conventional maintenance mixture and three alternative surface solutions: reflective pavement coatings, RAP mixtures incorporating rejuvenator-based self-healing systems, and thin low-noise asphalt layers. The assessment follows ISO 14040 and ISO 14044 standards and applies the ILCD 2011 midpoint+ (EF 2.0) method. To enable comparability between technologies with different durability, the functional unit was defined as 1 m² of rehabilitated pavement per year of service life. The results indicate that thin low-noise asphalt layers provide the highest environmental benefits across most impact categories due to significant material savings associated with reduced layer thickness. Reflective pavement coatings decrease several impacts, particularly fossil resource depletion and atmospheric emissions, although higher burdens are observed in some categories due to synthetic binder production. RAP mixtures incorporating rejuvenator-based self-healing systems improve resource efficiency and extend pavement durability but may increase impacts associated with binder manufacturing. Overall, the findings highlight relevant environmental trade-offs between different pavement surface technologies and demonstrate that parameters such as layer thickness, binder composition, recycled material content, and service life strongly influence environmental performance. The study illustrates how comparative Life Cycle Assessment supports the development and selection of more sustainable pavement surface systems. Full article

Pavement engineers frequently need a rapid and accurate evaluation of layer thicknesses and conditions. Such an assessment is critical for evaluating current conditions and identifying optimal maintenance and rehabilitation needs. The objective of this study was to use remote sensing for assessing pavement thickness uniformity. For this purpose, the potential use of Ground-Penetrating Radar (GPR) data was considered. Traditional GPR data interpretation methods are generally not intended to quantify the spatial variability information required for pavement management-related analyses. Thus, the method presented herein is based on several layers of statistical assessment of pavement thickness changes for identifying homogeneous sections. The suggested approach provides consistent thickness assessment over consecutive pavement segment lengths. Such evaluation is particularly useful for integration into Pavement Management System (PMS) analyses at both the project and network levels. The approach was used in concrete pavements, and data from an in-service roadway are provided as an example to demonstrate how this analysis is applied. This analysis approach provides several benefits to highway agencies: a quick and accurate condition assessment regarding existing pavement thickness; better decision-making in identifying alternative maintenance and rehabilitation techniques for uniform sections with respect to thickness, which clearly need to be combined with condition assessment of pavement layer materials; and efficient use of remote sensing data for pavement sections where construction inventory data may not be available. Full article

Most computational studies of vehicle hydroplaning have emphasized structural realism through fluid–structure interaction, tire deformation, tread geometry, and pavement surface characterization. By contrast, the hydrodynamics governing the flow in the tire vicinity, particularly the role of turbulence, have received comparatively limited attention. In a significant number of studies, the flow has been treated as laminar despite turbulent flow conditions, while in a few other studies turbulence modeling has been adopted without an explicit assessment of its impact on hydroplaning predictions. In this study, we present a simplified three-dimensional computational fluid dynamics (CFD) model designed to isolate the flow regimes governing hydroplaning and to quantify the mean effect of the turbulence modeling on the predicted hydroplaning speed. Using a finite-volume formulation with a volume-of-fluid representation of the air–water interface, the flow around and beneath a smooth 0.7 m-diameter tire sliding in locked-wheel mode over a flooded, nominally smooth pavement is simulated. The tire is represented as a rigid body with an idealized rectangular bottom patch whose area is determined from the tire load and inflation pressure, avoiding the need to prescribe a measured or assumed deformed footprint. Steady-state hydroplaning is modeled for a uniform upstream water film thickness of 7.62 mm with a 0.5 mm gap between the tire and the pavement, over tire inflation pressures ranging from approximately 100 to 300 kPa, and predictions are verified against the empirical NASA hydroplaning equation. For these conditions, simulations without turbulence closure exhibit a consistent, systematic underprediction of the hydroplaning speed of approximately 13.5% relative to the NASA relation. Incorporating turbulence effects through Reynolds-averaged closures substantially reduces this bias, with average deviations of about 6% for the realizable k–ε model and 2.4% for the shear stress transport (SST) k–ω model. An analysis of the results indicates that hydrodynamic lift is dominated by pressure buildup associated with stagnation at the lower leading edge of the tire, with a significant contribution from shear-dominated flow in the thin under-tire gap, and that turbulence acts to moderate the integrated lift from these pressure fields. These results demonstrate that explicitly accounting for turbulence in the tire vicinity is essential for reproducing empirical hydroplaning trends and for avoiding systematic bias in CFD-based hydroplaning predictions. Full article

This study investigates the thermo-mechanical response of geocell-reinforced concrete pavements through scaled model tests and three-dimensional finite element analyses. Static, thermal, traffic, and coupled temperature–loading tests were conducted to clarify the deformation evolution, strain distribution, and damage-related response of the reinforced structure. The results show that, under static loading, pavement settlement evolves through three stages, namely initial compaction, plastic development, and stable strengthening, indicating progressive mobilization of geocell confinement. Under thermal loading, slab strain exhibits pronounced spatial and temporal non-uniformity, and the slab center is identified as the thermally sensitive zone. Under coupled temperature–loading conditions, both strain and settlement show a non-monotonic response near 1.1–1.3 kN, suggesting a potential damage-initiation range. Post-test crack observations further provide direct qualitative evidence that local cracking damage occurred in the slab under representative loading conditions. Under traffic loading, permanent deformation accumulates with load repetitions and is highly sensitive to load amplitude, indicating a load-sensitive transition in cumulative deformation behavior rather than a definitive fatigue threshold. Numerical results further show that geocell reinforcement reduces central settlement by 17.4% relative to plain concrete pavement and by 7.6% relative to doweled pavement, while producing a smoother deflection basin and a more uniform stress distribution. Parametric analyses indicate that the optimum geocell height is approximately one-third of the slab thickness; beyond this range, the marginal reinforcement benefit decreases. Overall, the results demonstrate that geocell reinforcement can effectively improve load transfer, deformation compatibility, and thermo-mechanical stability of concrete pavements under the investigated conditions. Full article

Crumb rubber-modified asphalt concrete (CMAC) has gained increasing attention as a sustainable pavement material capable of improving mechanical performance while utilizing waste tire resources. This study investigates the rutting resistance and fatigue behavior of CMAC using a combined experimental and mechanistic–empirical modeling approach. Asphalt mixtures containing 0–25% crumb rubber by binder weight were prepared and evaluated through Marshall stability and indirect tensile fatigue tests, whereas Fourier-transform infrared spectroscopy (FTIR) was used to examine binder–rubber interactions. The results indicate that crumb rubber significantly influences both the volumetric and mechanical properties of asphalt mixtures. Mixtures containing 10–15% crumb rubber exhibited optimal performances, achieving up to 36% higher Marshall stability and improved fatigue life compared with conventional asphalt mixtures. FTIR analysis revealed that rubber particle swelling and limited chemical interactions enhanced binder elasticity and improved binder–aggregate compatibility. However, excessive rubber content (≥20%) resulted in reduced stability owing to increased binder absorption and decreased effective binder film thickness. A mechanistic–empirical model incorporating viscoelastic, viscoplastic, and fatigue damage parameters successfully reproduced the experimental trends and identified the same optimal rubber content range. The findings demonstrate that CMAC with a moderate rubber content can enhance pavement durability and structural performance while promoting environmentally sustainable road construction through the reuse of waste tires. Full article

A static load test, single-wheel load test, and cyclic-wheel load test were carried out on large-thickness flexible base-layer and semi-rigid base-layer asphalt pavement structures by a multifunctional wheel-load testing machine. A comparative analysis was conducted on the influence and mechanism factors, such as load strength, test temperature, and load rate, on the stress and strain at the top and bottom of two asphalt pavement structures. The results show that in the interval of 1.3 MPa ≥ load intensity ≥ 0.5 MPa, with the increase of static load, the transverse strain and vertical strain at the top and bottom of the base layer of large-thickness flexible base-layer asphalt pavements increase slowly with a slight increase; the transverse strain and vertical strain at the top of the base layer of large-thickness semi-rigid base-layer asphalt pavements are more sensitive to heavy traffic load; and the transverse strain and vertical strain generated at the bottom of the base layer increase uniformly with the enhancement of static load. Under the action of a single-wheel load, the transverse and vertical strain generated at the top and bottom of the base layer of large-thickness flexible base-layer and semi-rigid base-layer asphalt pavements are alternately tensile and compressive, mainly compressive strains, while large-thickness semi-rigid base-layer asphalt pavement exhibits more complex strain changes. Full article

Increasingly frequent extreme rainfall commonly leads to water accumulation on the road surface, elevating vehicle tire hydroplaning to a major threat to driving safety. Existing research mainly focused on tire model optimization or predicting critical hydroplaning speed features based on empirical formulas and numerical simulations. However, there is a lack of systematic validation of the tire–water–pavement coupling interaction under realistic pavement conditions, with particular insufficient attention paid to pavement dynamic responses. In this study, numerical simulation and field full-scale accelerated loading methods were applied to investigate dynamic response characteristics of the tire–water–pavement coupling interaction system. Parametric analyses were first performed to investigate the influences of vehicle speed, vehicle load, water-film thickness, and tire lateral position on the mechanical behaviors of the fluid–structure interaction for a moving vehicle tire. Subsequently, field-measured dynamic responses’ features were used to validate the numerical model, which was then further applied to predict critical conditions of vehicle tire hydroplaning. Finally, the mechanisms of hydroplaning and corresponding mitigation measures were discussed. The study revealed that increasing vehicle speed and water-film thickness, as well as decreasing vehicle load, would reduce the pavement supporting force. The tire–pavement contact stress and strain decreased from the vehicle tire’s center position towards its shoulders. The predicted critical hydroplaning condition suggested that increasing vehicle load mitigated hydroplaning by reducing the proportion of water-induced hydrodynamic lifting force relative to the total vehicle load. When the water depth is relatively shallow, the hydroplaning risk increases rapidly with water depth, while the water’s adverse impact on tire–pavement contact force gradually diminishes as water depth continues to increase. It implies that a vehicle with a relatively low axle load driving on the pavement with a thin thickness of retained water in light rain will still face the hydroplaning risk, as the pavement’s supporting force may be substantially reduced in this weather. The findings provide theoretical foundations and experimentally supported insights on driving safety assessment and anti-skid design of water-covered pavement. Full article

With increasing traffic loads and increasingly complex climate conditions, accurate prediction of the International Roughness Index (IRI) of asphalt pavements is crucial for developing effective maintenance plans. However, traditional regression models have limitations in capturing the coupled effects of traffic, structure, and environmental factors. To overcome this limitation, this study constructed a dataset containing 10,836 samples based on the Long-Term Pavement Performance (LTPP) database, integrating traffic load, pavement structure parameters, and climate variables. The variance inflation factor (VIF) and correlation analysis were used to validate the effectiveness of feature selection. We trained nine machine learning models and optimized the hyperparameters using a Bayesian optimization method with five-fold cross-validation to ensure good generalization ability. Results show that the TabPFN model, based on prior information, achieved the best overall performance with a coefficient of determination $R^2$ = 0.9474 and a low prediction error (RMSE = 0.138) on the test set. Paired t-tests based on cross-validation further confirmed that TabPFN’s predictive performance is statistically superior to the baseline model. SHAP and generalized additive model (GAM) analyses indicate that traffic load is the main driver of IRI growth, while structural layer thickness, within a certain range, can mitigate pavement roughness. Climatic factors have indirect long-term effects through cumulative environmental exposure. Although the main drivers differ slightly among different pavement structures, traffic load consistently plays a dominant role. To enhance the model’s practical applicability, we also developed a user-friendly graphical interface (GUI) for fast and accurate IRI prediction. Full article

Today, distributed optical fiber sensors are widely used in structural health monitoring due to their high sensitivity and long-distance applicability. However, when embedded in pavement structures, distributed optical fiber sensors are always installed in a slotted buried fashion, which not only affects current pavement durability but also reduces pavement construction efficiency. In order to design clear requirements of in situ-embedded distributed optical fiber sensors for pavement construction, this study analyzes the micro-mechanical behavior of optical cables under the ultimate pavement compaction state based on a coupled DEM-FDM approach. According to the study results, it is found that when the pavement subbase was compacted, the maximum contact force of 13.2 mm aggregates in the Z-direction exceeds 150 N, which is the main resistance of the external load during pavement construction. The tight-buffered optical cable without reinforcement element and armored layer cannot withstand the vibration load. The inclusion of GFRP strengthening components and an armored layer decreased maximum stress by 38.2% (X), 30.6% (Y), and 30.9% (Z), as well as displacement by 64.6% (X), 45.5% (Y), and 66.7% (Z). Additionally, the thickness of the outer sheath enhanced the ability to withstand tension but not compression. The increase in the thickness of the armored layer can improve the ability to withstand tension and compression. Full article

Due to the complex mesostructure of calcareous sand, accurately predicting the mechanical response of Asphalt-Bonded Calcareous Sand (ABCS) is extremely challenging. This study pioneers the development of a mesoscale model for ABCS that explicitly incorporates the Interfacial Transition Zone (ITZ) via a random particle algorithm. To overcome the efficiency bottlenecks of traditional time-domain integration, this study establishes a mesoscale framework coupling a random polygonal aggregate algorithm with direct Steady-State Dynamics (SSD) analysis. A major advantage of this framework is its capacity for large-scale parametric sensitivity analysis; herein, 920 independent mesoscale models were generated and rapidly solved across the broadband frequency domain. The framework was rigorously validated, demonstrating high predictive accuracy for both the baseline calibration and an independent 12% asphalt content mixture (baseline R² = 0.99, MAPE = 6.94%; independent validation R² = 0.96, MAPE = 9.73%). Notably, the SSD approach completes calculations (10⁻³ to 10³ Hz) for 10 massive 300 mm RVEs in just 6.5 min. Leveraging this high-throughput capability, the extensive parametric analysis reveals that variations in maximum aggregate size negligibly impact the dynamic modulus under a constant volume fraction. Conversely, an optimal Interfacial Transition Zone (ITZ) thickness of ~75 µm was identified, representing a physical equilibrium between interfacial reinforcement and bulk binder cohesion. Furthermore, an analytical RVE size criterion of 1.7–5.3 times the maximum aggregate size is proposed to satisfy a 5% engineering error tolerance, providing a highly efficient numerical tool for the virtual mix design of reef pavements. Full article

High-modulus asphalt binders are increasingly used to improve rutting resistance and enable pavement thickness reduction. Conventional binder indices do not always capture the stress-dependent response of high-modulus systems under heavy loading, and quantitative rules for selecting a high-modulus additive dosage are still limited. This study develops a full-temperature-range evaluation and dosage determination framework for high-modulus additive-modified asphalt binders (HMABs) produced on an SBS-modified base binder. Four binders were prepared with high-modulus additive dosages of 0%, 17%, 22% and 28% with a binder mass basis. High-temperature performance was evaluated by PG grading and an enhanced MSCR protocol that included 0.1, 3.2, 6.4 and 12.8 kPa. MSCR temperatures were selected based on PG results. Intermediate-temperature performance was evaluated using LAS at 25 °C with VECD-based fatigue analysis on RTFO + PAV-aged binders. Low-temperature cracking was evaluated using ABCD on PAV-aged binders at −36 °C. The results show that the high-temperature PG increased with dosage, but the 22% and 28% binders fell into the same grade, indicating limited dosage discrimination by the PG test. The enhanced MSCR test captured clearer dosage differences under higher stresses. Non-recoverable compliance decreased markedly with dosage, and stress sensitivity showed an overall decreasing trend; 6.4 kPa provided higher dosage sensitivity and lower variability than 3.2 kPa. LAS test shows a non-monotonic fatigue response in which peak shear stress and predicted fatigue life increased up to 22% and then declined at 28%. At 2.5% and 5% strain, the 22% binder increased predicted fatigue life by about 273% and 83% relative to the base binder, while at 10% strain, it was about 11% lower. ABCD results show an upward shift in critical cracking temperature and a clear reduction in fracture stress at high dosages, indicating increasing low-temperature fracture risk. Therefore, high-modulus additives markedly improve high-temperature stability but introduce full-temperature trade-offs. The proposed full-temperature-range examined framework improves performance discrimination and supports dosage selection. A target dosage of 22% is recommended, and 17~22% is suggested as an engineering-controllable range for a balanced full-temperature performance, while 28% should be treated as an upper-bound option, primarily for warm regions where rutting dominates. Full article

Stone Mastic Asphalt (SMA) mixtures are widely used in high-capacity road pavements due to their durability and resistance to permanent deformation. However, although electric arc furnace (EAF) steel slag and recycled crumb rubber have been individually investigated as alternative materials in asphalt mixtures, evidence regarding their simultaneous incorporation in SMA mixtures under full-scale construction and real traffic conditions remains limited. Moreover, quantitative environmental assessments are often restricted to simplified or qualitative approaches, with limited reporting of carbon footprint results. This study investigates the combined use of electric arc furnace (EAF) steel slag aggregates and recycled crumb rubber in SMA mixtures, integrating laboratory evaluation with full-scale field application on a high-traffic motorway. Two SMA 11 mixtures were designed and assessed: one incorporating steel slag aggregates as a replacement for natural coarse aggregates, and another combining steel slag aggregates with recycled crumb rubber added through the dry process (0.8% by mixture mass). Laboratory testing included volumetric characterization, moisture sensitivity and rutting resistance, while field validation covered surface macrotexture, skid resistance, executed thickness and interlayer bonding. Both mixtures fully complied with the applicable technical specifications, achieving indirect tensile strength ratios (ITSR) above 90% and wheel-tracking slopes below 0.07 mm/10³ cycles. A simplified comparative life-cycle assessment (LCA), limited to modules A1–A3, showed a reduction in CO₂-equivalent emissions of approximately 2% for the mixture containing steel slag and up to 27% for the mixture combining steel slag and recycled crumb rubber, mainly due to the valorization of industrial by-products and end-of-life tyres. Overall, the results demonstrate the technical feasibility and potential environmental benefits of these SMA mixtures within the defined scope of laboratory verification, short-term field performance and screening LCA. The contribution of this study lies in providing applied evidence from a full-scale motorway intervention, complementing predominantly laboratory-based studies and offering a quantified environmental comparison under consistent methodological assumptions. Full article

Due to the brittleness and volume sensitivity, segmentation is necessary for the cement concrete pavement slabs currently in widespread use to mitigate thermal stress and deformation. The dimensions of segmented pavement slabs are typically constrained to 4∼6 m, which results in a large number of joints. These joints cause damages such as corner spalling and fracture under the impact of repeated loads and environmental factors. In addition, maintenance costs are significantly increased due to the numerous joints. To enhance pavement performance and extend service lifespan, this paper proposes a design methodology for large pavement slabs. This method breaks the dimensional constraint and significantly reduces the number of joints, thereby improving comfort and durability, lowering maintenance costs, and meeting the operational requirements of new aircraft types. In this paper, pavement slab thermal stress is divided into curling stress and thermal expansion stress according to different deformation types. The diurnal and annual distributions of these two types of stresses are also investigated. Moreover, the maximum dimension design of pavement slabs comprehensively considers aircraft loads, thermal stresses, and fatigue characteristics. The results indicate that the diurnal and annual distributions of curling and thermal expansion stresses exhibit sinusoidal patterns. Under different temperature gradients and slab thicknesses, the allowable maximum slab dimension is presented. It is feasible to break the 4∼6 m limit for the maximum dimension of the pavement slab, which provides a new reference for improving pavement performance and lifespan. Full article

Punchouts distress represents a major structural deficiency in Continuously Reinforced Concrete Pavements (CRCPs), contributing to premature deterioration, reduced ride quality, and increased maintenance demands. To improve the prediction of punchout occurrence, this study develops a hybrid data-driven modeling approach that combines Gradient Boosting Machines (GBMs) with Particle Swarm Optimization (PSO). The proposed framework utilizes 395 observations obtained from 33 CRCP sections in the Long-Term Pavement Performance (LTPP) database, incorporating structural, climatic, traffic, and performance-related variables. PSO was applied to systematically tune key GBM hyperparameters, including the number of boosting iterations, learning rate, and tree complexity, in order to enhance predictive accuracy. Model performance was evaluated using five-fold cross-validation, where the optimized PSO-GBM model achieved an average RMSE of 1.09 and an R² value of 0.947, outperforming conventional GBM as well as Random Forest, Support Vector Regression, Artificial Neural Networks, and Linear Regression models. Variable importance and sensitivity analyses revealed that Layer 3 thickness, pavement age, annual average daily traffic, and precipitation play dominant roles in punchout development. The consistency of residual distributions and the stability of hyperparameter sensitivity trends further confirm the robustness of the proposed framework. Overall, the results demonstrate that integrating evolutionary optimization with ensemble learning provides an effective tool for modeling complex pavement distresses and offers practical support for proactive maintenance planning and long-term management of CRCP infrastructure. Full article