Search Results (405)

The thermo-mechanical degradation of the base–subgrade interface in airport pavements was investigated using a three-dimensional sequentially coupled finite element framework in ABAQUS 2023, in which progressive interfacial debonding was described by a bilinear cohesive-zone model through the damage variable CSDMG. The results show that thermal loading markedly accelerates interface degradation when combined with moving wheel loads. Compared with the wheel-loading-only condition, thermo-mechanical coupling advances the first damage initiation from 0.04993 h to 0.00254 h and shortens the severe-degradation stage from 1.000 h to 0.00927 h. This acceleration is attributed to a thermal stress pre-weakening effect, whereby constrained thermal deformation partially consumes the available cohesive resistance and shifts the interface closer to the softening threshold before external loading is applied. A decomposition of the mixed-mode initiation criterion further indicates that the first damage event is governed by synergistic normal–shear interaction, with the normalized contribution ratio (t_n/t_n⁰)²:(t_s/t_s⁰)² = 0.38:0.62, showing that wheel-induced shear is the dominant trigger while tensile opening induced by thermal curling provides substantial preconditioning assistance. In addition, a representative normalized comparison between simulated average CSDMG and cumulative AE hit count demonstrates a consistent stage evolution from distributed deformation to accelerated localization and residual stabilization. These findings indicate that the base–subgrade interface should be treated as a temperature-sensitive weak layer in airport pavement assessment, particularly near joints and other discontinuity-controlled regions. Full article

To address the lack of systematic quantitative studies on waterborne epoxy resin (WER)-modified emulsified asphalt regarding its rheological optimization and engineering applicability, this study fills the gap by preparing WER-modified emulsified asphalt via a two-step process. New findings reveal that 20% WER content significantly enhances elastic components, creep–recovery, fatigue life, and fracture energy. The main objective is to establish a theoretical basis for high-performance pavement materials. Modified emulsified asphalt specimens with different waterborne epoxy resin contents were prepared using a two-step method of “emulsification followed by compounding”. The stability of the emulsions was quantitatively evaluated by zeta potential, storage stability, particle size distribution, and demulsification time. Their rheological parameters, multi-stress creep–recovery characteristics, fatigue life, and low-temperature crack resistance were systematically tested across the full temperature range using a dynamic shear rheometer and a bending beam rheometer. In addition, the bonding performance, strength development behavior, and water resistance durability were comprehensively assessed through pull-out tests, Marshall stability and splitting strength tests, as well as freeze–thaw cycle tests. These properties were compared with those of unmodified emulsified asphalt (UEA-0) and SBR-modified emulsified asphalt (SBR-EA). With an increase in waterborne epoxy resin content, the elastic component of the modified asphalt improved significantly, and the phase angle continuously decreased. The specimen with 20% waterborne epoxy resin content (WER-EA-20) exhibited the best performance: its phase angle was lower than those of the other groups under high-, medium-, and low-temperature conditions. After seven creep–recovery cycles, its creep–recovery rate remained at 33%, substantially higher than the 8% observed for the unmodified specimen. The fatigue life reached 15,000 cycles under a shear stress of 2.1 MPa. At −10 °C, the fracture strength was 0.92 MPa, and the fracture energy reached 21.4 J. Furthermore, the pull-out strength of WER-EA-20 was 0.86 MPa, with the failure mode identified as asphalt cohesive failure. After 37 days of curing, the Marshall stability reached 22.5 kN, and the splitting strength was 1.36 MPa. After 40 freeze–thaw cycles, the freeze–thaw splitting strength ratio (TSR) of WER-EA-20 remained above 75%, representing an improvement of more than 110% compared to the unmodified UEA-0 (TSR ≈ 35.5%), which highlights the significant enhancement in water resistance imparted by the waterborne epoxy resin. Compared to SBR-EA, WER-EA-20 has a higher softening point, a lower suitable mixing temperature, and better anti-aging properties. Waterborne epoxy resin can effectively improve the viscoelastic properties and overall road performance of emulsified asphalt, and the modification effect increases with increasing dosage. Full article

Moisture-induced damage is one of the primary causes of premature distress in asphalt pavements, leading to reduced service life and increased maintenance costs. Although nanomaterials have shown potential in enhancing asphalt performance, the underlying composite interaction mechanisms among nanomaterials, asphalt binder, and aggregate phases under moisture exposure are still not fully understood. In addition, comparative evaluations under consistent experimental conditions remain limited. This study investigates the influence of five nanomaterials: nano-silica (NS), nano-alumina (NA), nano-titanium dioxide (NT), nano-zinc oxide (NZ), and carbon nanotubes (CNT) on the physical and mechanical properties of asphalt binders and mixtures, with particular emphasis on moisture damage resistance. The nanomaterials were incorporated at dosages of 1.5%, 3.0%, 4.5%, and 6.0% by binder weight. Binder performance was evaluated using conventional and performance grading (PG) tests, while mixture performance was assessed through Marshall properties and moisture susceptibility indicators, including the tensile strength ratio (TSR) and the index of retained strength (IRS). Fluorescence microscopy (FM), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR) were employed to investigate nanomaterial dispersion characteristics, microstructural morphology, and physicochemical interactions within the asphalt composite system. The results indicate that nanomaterial modification reduced penetration and increased softening point and Marshall stability, reflecting enhanced stiffness and thermal resistance, although ductility decreased at higher dosages. Significant improvements in moisture resistance were observed, particularly under conditioned states. The TSR increased from 81.2% for the control mixture to 92.4% for NS and 91.7% for NA, while the IRS improved from 72.7% to 88.5% for NS. Statistical analysis indicated that both nanomaterial type and dosage significantly affected TSR and IRS performance, with dosage exhibiting comparatively greater influence on moisture resistance improvement. FM and SEM analyses revealed comparatively better dispersion and lower agglomeration tendency for NS and NA, which corresponded to their superior moisture resistance performance. FTIR analysis indicated that the modification process was predominantly physical, with no major formation of new chemical functional groups. Among the investigated nano materials, NS at 6% dosage exhibited the most pronounced improvement, followed by NA at similar dosage levels. Overall, the findings suggest that nanomaterial modification can considerably improve the moisture resistance and mechanical performance of asphalt mixtures under laboratory conditions. However, higher nanomaterial dosages may adversely affect binder workability due to increased viscosity, particularly in CNT-modified binders. Full article

Magnitude alone fails to capture the full complexity of pavement roughness; its spatial distribution along a road is equally vital for effective maintenance planning. While traditional assessment has long relied on specialized survey vehicles, the rise of mobile crowdsensing now allows for massive data acquisition via smartphone sensors. This study investigates the spatial structure of pavement roughness using crowdsensed data from the SmartRoadSense platform. Roughness is quantified through the Power of Prediction Error (PPE) indicator derived from smartphone accelerometer signals. The dataset consists of 475 observations sampled at 20 m intervals over approximately 9.5 km of the A3/E45 motorway in southern Italy. A multi-scale spatial–statistical framework is adopted to analyse the roughness signal. The analysis includes the evaluation of scale-dependent statistical descriptors (mean and coefficient of variation), as well as spatial correlation, spectral, and entropy-based measures. The results indicate a short spatial correlation length (approximately 60–100 m) and the absence of a dominant spatial wavelength, suggesting that pavement roughness behaves as a localized multiscale process. A complementary segmentation analysis based on Classification and Regression Trees (CART) is performed to explore the spatial partitioning of the roughness signal. Our analysis indicates that segmentation complexity spikes once the minimum node size drops below roughly 10 observations. This trend points to the existence of localized irregularities that coarser scales simply overlook. Ultimately, these results suggest that mean roughness values alone are insufficient for describing pavement condition and that hybrid spatial–statistical approaches may support more scalable, data-driven, and spatially targeted pavement monitoring strategies for sustainable transportation infrastructure management. Full article

To address the lack of long-term, wide-area surface deformation observations along the geologically complex Dangxiong–Yangbajing section of the G6 Expressway in the frozen-ground region of the Qinghai–Tibet Plateau, where conventional monitoring is insufficient, we applied Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) to retrieve surface deformation within a 2.0 km corridor on both sides of the highway from 24 November 2021 to 26 December 2024, and to characterize the spatiotemporal evolution of deformation. We then integrated eight explanatory factors (slope, surface roughness, distance to rivers, distance to faults, surface soil moisture, precipitation, land surface temperature (LST), and fractional vegetation cover (FVC)). Geodetector was used to quantify their explanatory power and spatial heterogeneity with respect to deformation. The results show pronounced spatially uneven settlement along this highway segment, with maximum annual settlement rates exceeding −45 mm/a. Five settlement centers were identified, including two major pavement subsidence zones. Distance to faults and soil moisture showed higher single-factor explanatory power, whereas FVC, precipitation, and LST also contributed to deformation heterogeneity. Interaction detection further indicated that the interactions between fault-related conditions with vegetation, soil moisture, precipitation, and LST substantially enhanced the explanatory power, suggesting that the deformation pattern was associated with multi-factor coupling rather than a single dominant environmental factor. These findings demonstrate the utility of integrating SBAS-InSAR with Geodetector analysis for corridor-scale highway deformation assessment and provide a remote sensing basis for targeted hazard assessment and risk mitigation for highways in frozen-ground environments. Full article

To address the application requirements of dynamic simulation for sudden deep pavement potholes, this study presents an automated cover plate control device that integrates concealment, rapid response, and high load-bearing capacity, thereby overcoming the inherent contradiction between “portable yet weakly load-bearing” and “highly load-bearing yet inflexible” that has long limited conventional cover plate solutions. The core of the device comprises a cover plate mechanism consisting of a UHPC–Q235 composite cover plate, a distributed truss, and specially configured connecting rods, together with a winch hoisting mechanism, a hydraulic locking and rapid-release mechanism, and an embedded steel frame structure. Together, these modules realize a complete operational cycle of “closed load-bearing support → hydraulic release → gravity-driven rotation → winch reset.” Theoretical analysis and experimental measurements demonstrate that hydraulic release can be accomplished within 0.5 s, the cover plate can form a standard collapse pothole of 2000 mm in diameter within approximately 1 s, and a single cycle requires approximately 11 s, thereby faithfully reproducing the dynamic process of sudden pavement collapse. Refined mechanical design and ABAQUS finite element simulations verify that under the most adverse loading conditions, the stress in all structural components remains below the material design strength limit, with clear and reliable load transfer paths maintained in all operational states. The integrated camouflage design achieves over 95% visual and tactile similarity to the existing pavement surface, meeting the design requirement of concealment under normal conditions. The proposed device offers a high-fidelity physical simulation solution for autonomous vehicle perceptual training under emergent road hazards and for roadway safety assessment. Full article

Reliable pavement condition assessment using UAV-derived orthophotos remains challenging under manual flight conditions, where acquisition parameters are not predefined and photogrammetric quality is highly operator-dependent. This study evaluates how UAV flight configuration influences orthophoto quality and operational usability for road infrastructure assessment in real-world manual survey scenarios. Eight flight treatments combining altitude (30–40 m AGL), flight speed (low/normal), and image capture interval (2–3 s) were tested over an urban–peri-urban road segment in Misantla, Veracruz, Mexico, using a DJI Air 3S platform. Orthomosaic quality was assessed through ground sampling distance (GSD), tie-point density, multiplicity, RMS reprojection error, dense cloud size, orthomosaic continuity, and a criteria-based interpretability index supported by field observations. Results show that while altitude controls spatial resolution, resolution alone is insufficient for reliable pavement assessment. Configurations with higher image overlap and photogrammetric redundancy (notably Treatment 1 (T1) and Treatment 3 (T3)) achieved superior geometric consistency, reduced seam artifacts, and improved detection of subtle surface irregularities. In contrast, reduced-overlap configurations produced complete but less interpretable orthomosaics. The study provides experimentally validated operational guidelines for optimizing UAV flight parameters under manual conditions, bridging the gap between controlled photogrammetric theory and practical infrastructure monitoring. Full article

Urban green spaces (UGSs) are increasingly recognised as critical infrastructure for mitigating climate extremes and promoting public health; indeed, the microclimatic mechanisms through which vegetation structure translates into measurable improvements in human comfort at the neighbourhood scale are of significant interest, particularly in the context of new urban developments. This study examines the cooling effects of an urban redevelopment project in the Marconi district of Imola, Italy, using ENVI-met (Version 6.0.0, ENVI-met GmbH, Essen, Germany) simulations to compare ex ante (current) and ex post (planned) scenarios under extreme heat conditions. Physiological Equivalent Temperature (PET) was computed at the pedestrian level for both standard adult and elderly models to assess spatial patterns of thermal comfort. The results demonstrate that tree canopies are the primary determinant of local cooling, with newly planted trees reducing PET by up to 3.5 °C at the core of the regenerated block and by 1–2 °C along adjacent pavements, while grass and low vegetation provided negligible mitigation. However, new buildings generated localised warming bands of 0.5–2 °C along façades, revealing a trade-off between densification and outdoor liveability. Elderly populations experienced slightly stronger thermal stress near buildings, highlighting spatial concentrations of vulnerability. These findings reinforce the need to prioritise tree planting and canopy management as core climate adaptation strategies, while simultaneously addressing near-building heat accumulation through integrated design approaches such as façade greening and ventilation preservation. The study demonstrates the value of spatially explicit microclimate simulation for evidence-based urban planning, contributing to the development of sustainable and liveable urban environments. Full article

The pavement surface temperatures in Iraq are remarkably high, causing the asphalt to deteriorate quickly, shortening its service life. While a large amount of corn husk, an agricultural waste, is available for use as an asphalt modifier, researchers have not yet fully investigated this option. In this study, the use of corn husk fiber powder (CHFP) as a long-term modifier for asphalt binders and mixtures that are exposed to high-temperature conditions is evaluated. CHFP was mixed into a 40–50 penetration grade asphalt binder at concentrations ranging from 0.0% to 0.6% by weight. Performance was assessed using laboratory tests such as penetration, softening point, rotating viscosity, dynamic shear rheometer (DSR), aging (RTFOT and PAV), and wheel tracking. The findings revealed that CHFP greatly lowers penetration while increasing the softening point, indicating increased stiffness and high-temperature stability. Rheological research showed an increase in the rutting parameter (G*/sinδ) and viscosity, as well as reduced temperature susceptibility. At the mixed level, CHFP reduced rut depth while improving dynamic stability, indicating increased resistance to permanent deformation. The best performance was obtained at 0.3% CHFP, after which, improvements decreased due to probable dispersion constraints. The performance improvement is related to the creation of a reinforcing fiber network and the absorption of light asphalt components. Overall, CHFP is a promising, environmentally friendly and cost-effective addition for increasing asphalt pavement performance and promoting sustainable waste management. Full article

Polyurethane (PU) mixtures are a promising high-strength, rapid-curing alternative to conventional asphalt, but their widespread application is hindered by slow curing rates and sensitivity to ambient moisture. To address these limitations, this study systematically evaluated the efficacy of three additives—lignin-based fiber, Glauber’s salt, and green vitriol—in regulating the curing behavior and performance of PU mixtures. Marshall stability, volumetric properties, and moisture resistance were measured under both outdoor and controlled laboratory curing conditions. Lignin fiber uniformly accelerates early-stage curing by enhancing moisture distribution via capillary action. Glauber’s salt releases crystalline water, drastically boosting early-age strength (by 162.4% after 2 days) but at the cost of an increased air void content (up to 8.1%) and reduced long-term water stability (residual stability <80%). Green vitriol acts through Fe²⁺ catalysis and crystalline water release, with its effectiveness being highly temperature- and delay-time-dependent. Combining fiber with Glauber’s salt yields the highest early strength but the shortest construction window (<1 h) and the most severe volumetric deterioration beyond the optimal delay time. All mixtures achieved high ultimate strength after sufficient curing (7 days), but the improvement varied significantly with additive type—ranging from 52.2% (fiber alone) to 162.4% (Glauber’s salt alone). Moreover, even under ideal curing, incomplete –NCO conversion persisted, indicating intrinsic cross-linking limitations. The residual stability of all mixtures fell below the 80% specification for conventional asphalt, suggesting that this metric alone is insufficient for assessing the moisture resistance of high-strength PU mixtures. This study demonstrates that while additives significantly enhance early-age performance, their application requires carefully optimized dosage, delay time, and temperature control to balance early strength gains with long-term volumetric integrity and durability. The findings provide revised evaluation metrics and practical guidelines for implementing PU mixtures in rapid pavement construction and repair. Full article

Fatigue crack deterioration in flexible pavements results from structural loading, traffic demand, material aging, and climatic exposure; yet, Ethiopian pavement models remain largely empirical, with little mechanistic foundation. This study develops a hybrid mechanistic–empirical and artificial neural network framework to forecast fatigue crack progression along a five-kilometer segment of the Woldia–Jeneto road in northern Ethiopia, built in 2015 and assessed after ten years of service. ERAPave layered elastic analysis computed critical horizontal tensile strain at the asphalt base, using the ERA manual recommendation of the Australian fatigue criterion for tropical areas, deriving cumulative damage indices via Miner’s rule. These outputs, alongside material properties, soil indices, traffic, climate, and temporal variables, formed an 18-feature input vector, which was trained using Latin–Hypercube Sampling and leave-one-out cross-validation under data-scarce conditions. Critical tandem-axle loads of 200.2 kN produced tensile strains of 182.7–199.83 με and damage ratios of 0.39–0.76 within fatigue lifetimes of 10.46–20.12 million ESALs, exceeding the 7.93 million ESAL design threshold. The model achieved R² = 0.9997 and MAPE = 1.64%; these figures reflect five-station training conditions and synthetic augmentation rather than unconditional generalization accuracy. Ten-year forecasts place Station 5 at structural failure within three years, supporting evidence-based pavement maintenance planning. Full article

The three-dimensional (3D) texture of pavement surfaces critically influences skid resistance, noise, and rolling resistance, but high-resolution 3D acquisition is time-consuming and requires specialized equipment. This study investigates the use of a conditional generative adversarial network (cGAN) to predict 3D pavement texture from more efficiently acquired 2D reflectance intensity images. Co-registered 3D height maps and intensity data were captured using a high-precision line laser scanner. The intensity images were preprocessed into three representations: raw intensity, histogram-equalized, and watershed-segmented images. Four input configurations, each stacking three channels of these representations, were evaluated to determine the optimal input. Additionally, the proposed cGAN was compared with mainstream image-to-image translation models using the best-performing input. Model performance was assessed using root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM). The results show that the configuration using only histogram-equalized images achieved the best overall performance (SSIM = 0.4065). In the model comparison, the proposed cGAN attained the highest SSIM. These findings indicate that the proposed approach can produce 3D texture maps that capture the main structural features of pavement surfaces, suggesting its potential for efficient surface characterization. Full article

Cracks are among the most common pavement distresses, and their timely detection is crucial for road maintenance. Existing methods struggle to completely capture elongated and irregular cracks, often resulting in fragmented detection outputs, which leads to the inaccurate assessment of crack length and affects the reliability of pavement condition evaluation. To address this issue, this paper proposes a dual-path crack segmentation network that integrates CNN and Transformers. The CNN branch incorporates a dynamic multi-branch convolution module to enhance the directional perception and structural modeling of elongated cracks. The Transformer branch employs a lightweight DCNv4 module to replace traditional self-attention mechanisms, effectively capturing long-range dependencies while reducing computational complexity. A multi-path fusion module is designed to achieve the collaborative enhancement of dual-path features, improving the semantic representation of continuous crack regions. Additionally, a combined loss function of BCE and Dice is adopted to alleviate the severe class imbalance between crack and background pixels, further improving the completeness of crack segmentation. Experiments on four datasets, including CFD, DeepCrack537, Gaps384, and Crack500, demonstrate that the proposed model outperforms all compared methods in terms of F-score and mIoU. Ablation studies further validate the effectiveness of the dual-path architecture and its key modules in improving performance. Furthermore, in field validation on real road scenarios, the pavement condition index (PCI) calculated based on the proposed method shows an average deviation of only 0.81 compared to manually interpreted ground truth, demonstrating the practical value of continuous crack detection for pavement maintenance assessment. Full article

Stabilizing weak soils is a well-known pavement and geotechnical engineering technique. This technique involves introducing minimal cementitious materials to improve the soil’s geotechnical characteristics. This paper investigates the use of recycled industrial polymer waste (IPW) as a reinforcement material in the presence of cementitious binders to stabilize weak silty sand soil (SM), supporting sustainable engineering practices. The randomly distributed IPW were added as percentages of 0%, 5%, and 10% to a mixture of lime soil and cement soil, with varying amounts of 0% to 6% of lime (L) and 0% to 6% of ordinary Portland cement (OPC), respectively. The laboratory experiments were conducted on natural and stabilized samples in wet (unsoaked) and submerged (soaked) conditions. The experimental program included Proctor compaction, California bearing ratio (CBR), unconfined compressive strength (UCS), durability tests, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction analyses. The resilient modulus (Mr) was estimated using an empirical equation. The outcomes of this experimental study show that adding a combination of IPW shreds with a small amount of L and/or OPC to the SM soil provides a significant increase in the UCS, CBR, durability and Mr values compared with case of SM with only L, which allows for superior characteristics and increases strength and stiffness parameters throughout any phase of earthwork construction design, resulting in stronger and stiffer subgrades. These results were reinforced by microstructural observations from SEM, EDS, and DRX, confirming the formation of cementitious gels and chemical compounds, consistent with the macro-scale mechanical improvements. The expected practical outcomes include potential reductions in pavement thickness, which can help lower pavement stabilization costs and extend its service life. Additionally, the use of waste materials to replace raw materials contributes to decreased energy consumption and emissions, although detailed assessments are needed to quantify these effects. Full article

Moisture damage is a common hidden distress in asphalt pavements in hot and rainy regions, where it can rapidly develop into severe surface deterioration if not detected in time. To address this issue, this study proposes an automated framework integrating ground-penetrating radar (GPR) data and the YOLOv13 model for multi-scale moisture damage detection on the Jingang Expressway in Cambodia. A total of 1672 GPR images containing moisture damage were collected through field surveys using a 2.3 GHz GPR system. Based on field statistical analysis, the detected damage was classified into three scale levels: large-scale (>2 m), medium-scale (0.8–2 m), and tiny-scale (<0.8 m). Several recent YOLO variants were compared, and YOLOv13s was identified as the optimal model, achieving the best balance between detection accuracy and inference efficiency, with an mAP@0.5 of 85.3% and an FPS of 48. The proposed method was further validated through laboratory and field tests. The results indicate that the developed framework can effectively detect and localize multi-scale moisture damage under practical engineering conditions, providing a non-destructive and efficient approach for pavement condition assessment in hot and rainy regions. By enabling early-stage detection of moisture damage deterioration, the proposed framework may contribute to more sustainable pavement maintenance and long-term transportation infrastructure management. Full article