Pavement Damage Research Articles

Magnesium chloride deicer and asphalt: a multiscale approach to adhesion and damage characterisation

The combined effects of magnesium chloride (MgCl2) deicer and freeze-thaw (F-T) accelerate the progression of moisture-induced damage in asphalt pavements. A multiscale approach was employed to evaluate adhesion and debonding mechanisms in systems of a polymer-modified asphalt binder and different aggregates subjected to various concentrations of aqueous MgCl2 solutions and F-T cycles. Pull-off tests conducted on binder-aggregate samples revealed that the pull-off strength and failure mechanism were affected by the salt concentrations and aggregates’ mineralogies. Investigating the adhesion and debonding using the surface free energy, a thermodynamic approach, showed that depending on the aggregate type, lower salt concentrations could accelerate adhesion decay at a higher rate compared to higher salt concentrations. Atomic force microscopy study revealed that salt concentration and F-T cycles significantly affected the microstructure, morphology, and micromechanical characteristics of the asphalt binder, contributing to an accelerated loss of adhesion in asphalt binder-aggregate systems.

Super-resolution Crack Image Generation for Fixed PTZ-Camera Based Highway Pavement Crack Recognition

Abstract Among the various diseases that inevitably occur on expressways, cracks are the most common and are significant indicators of highway pavement damage. Timely and accurate crack recognition is urgently required for highway maintenance. Highway pavement crack recognition depends mainly on human visual inspection and expressway maintenance vehicles. These approaches are very time-consuming, labor-intensive, and difficult to implement in civil engineering. Cost-effective fixed PTZ (pan/tilt/zoom)-camera based crack recognition was investigated in our previous work. However, for pavement cracks captured at long camera distances, the limited resolution of the PTZ-vision results in low-resolution crack images. In addition, the cracks are weak features, such that the crack pixels density and distribution are significantly affected by the background noise, making it difficult to recognize these cracks. Aiming at to solve these problems, a high-order kernel based modified bicubic interpolation is proposed to typically reveal and characterize discrete pixel variations, obtaining high-quality super-resolution crack images, and improving the recognition performance of cracks. Extensive experiments in relation to crack datasets captured by PTZ-cameras on G4/highways in China are conducted to verify the performance of the proposed method. Two measurement parameters Just Noticeable Blue (JNB) and Structural Similarity Index (SSIM) confirm the high-quality of the super-resolution crack images. Experimental comparisons demonstrate that super-resolution crack images based crack recognition achieves out-performance, such that the mAP, precision (P), recall (R), and F1-score are increased to $95.3\%, 97.3\%, 96.1\%$, and $97.4\%$, respectively. This method proves the feasibility of high-efficiency crack recognition using modified bicubic interpolation for fixed PTZ-vision based expressways maintenance engineering.

Impact of Farm Equipment Loading on Rigid Pavement Performance Using Finite Element Analysis

The increase in agricultural product sales in recent years has led to the use of larger hauling and application equipment to transfer farm productions. This rapid shift in equipment size has raised a concern about their potential to cause significant damage in pavements and bridges. The study reported in this paper (part of a larger pooled fund study initiated in 2007) discusses the impact of farm equipment loading on rigid pavement performance based on Finite Element (FE) analysis. The study considered various types of farm equipment to determine the pavement responses and to quantify their damage on rigid pavement systems. The ISLAB2005 FE pavement response model was employed for numerical modeling and analysis of the test sections subjected to farm equipment loading. The results of FE analysis demonstrated that the rigid pavement damage caused by farm vehicles is governed by their axle weight rather than the gross vehicle weight. The FE analysis also showed that the damage resulting from farm equipment loading coupled with PCC slab curling could have a devastating effect on concrete pavement performance.

Effects of Non-Linear Thermal Stress on Fatigue Damage of Airport Concrete Pavements

Thermal stress caused by temperature distribution in concrete slab is important in the structural design of airport concrete pavements. Airport concrete pavement slab is very thick, therefore, temperature in the slab varies nonlinearly throughout the slab depth. In this study, a method for estimating thermal stress in a concrete slab with 3DFEM analysis and heat transfer analysis was developed. The thermal stresses for airport concrete pavements with various thicknesses and climate conditions were calculated with the method for one year period and relative frequency distributions (RFDs) of the thermal stresses were obtained. Influence lines of load stress due to aircraft gear were also calculated with 3DFEM. The fatigue damages were estimated from the RFDs, the lateral distributions of the gear, combined stresses and fatigue curve of concrete. Based on the results, effects of the nonlinearity of thermal distribution and air temperature on the fatigue damage of airport concrete pavements were investigated in terms of the optimal thickness of concrete slab.

Strategi Pemeliharaan Dan Model Hubungan Antara Nilai Kekasaran Jalan Dan Nilai Kondisi Perkerasan Kaku Dengan Metode IKP Dan IRI Studi Kasus Jalan Lingkar Selatan Kota Cilegon

Damage to roads indicates a condition where the structural and functional aspects of the road are no longer able to provide optimal service to the traffic passing through it. If road damage occurs, it can result not only in the obstruction of economic and social activities but also in the occurrence of accidents. To determine the level of damage and the type of repairs needed for a road segment under review, a method is required. In this study, the IKP method (Pavement Condition Index) and IRI method (International Roughness Index) are used. The objectives of this research are to determine the road damage level using the IKP method on the South Cilegon Ring Road, to determine the road roughness level using the IRI method on the South Cilegon Ring Road, to compare the values of road damage level using the IKP and IRI methods on the South Cilegon Ring Road, and to address road damage based on the road condition assessment results. The results of this study show that there are five types of damage on the South Cilegon Ring Road in both the right and left lanes: Line cracks, Punchout, Plate Separator, Corner cracks, and Large patches. The smoothness level (IRI) on the South Cilegon Ring Road in the left lane is in good condition with percentage values of 60% for good, 15% for fair, and 25% for severe damage. Meanwhile, in the right lane, the road condition is good with percentage values of 75% for good, 20% for fair, and 5% for light damage. The proposed solution for road condition management on the South Cilegon Ring Road as a whole, following Regulation of the Minister of Public Works No. 13/PRT/M/2011, is a routine maintenance program. The relationship between the road roughness value (IRI) and the road pavement damage value (IKP) is analyzed through regression analysis, resulting in the equation IKP = 0.0012(IRI)^2 – 0.1648(IRI) + 8.8719.

Pavement Disease Visual Detection by Structure Perception and Feature Attention Network

Balancing detection performance and computational efficiency is critical for sustainable pavement disease detection in energy-constrained scenarios. However, existing visual methods often struggle to adapt to structural transformations and capture critical features of pavement diseases in complex environments, while their computational demands can be resource-intensive. To address these challenges, this paper proposes a structure perception and feature attention network (SPFAN). The network includes a structure perception module that employs the updated deformable convolution technique. This technique enables the model to dynamically adjust and focus on the actual pavement disease regions, improving the accuracy of feature extraction, especially for diseases with irregular shapes and sizes. Additionally, the convolutional block attention module (CBAM) is integrated to optimize feature map attention across channel and spatial dimensions, enhancing the model focus on critical disease features without significantly increasing complexity. To further improve robustness, the generalized intersection over union (GIoU) loss function is adopted, ensuring better stability across targets of varying shapes and sizes. Experimental results on real-world pavement disease images show that the mAP@0.5 of the proposed SPFAN increases from 66.2% to 71.2%, an improvement of 7.55%, while the F1-score also increases by 9.03%, compared to the baseline YOLOv8n model. Furthermore, while achieving significant accuracy improvements, the proposed method maintains a similar parameter count as the baseline, preserving its low computational demands and high efficiency, making it suitable for real-time pavement damage detection in energy-constrained environments.

LOAD TRANSFER RESTORATION AT JOINTS

The development of a cost-effective method for restoring load transfer at concrete pavement joints has significant implications for maintaining the longevity and usability of roadways. Recognizing early signs of damage in concrete pavements, a French team proposed an innovative solution to restore load transfer by using a method that involves minimal machinery and low amounts of resin for anchoring. This method notably differs from existing techniques by its efficiency, reduced costs, and ability to handle high traffic levels without significant road closures. Initial in-situ tests demonstrated the method's effectiveness in reducing deflections and ensuring the perfect transmission of loads across joints, suggesting its short-term viability. The method, characterized by drilling holes across the joint and inserting a specially designed connector, addresses the challenges of early joint deterioration without extensive machining or the use of large quantities of resin. Further developments led to the design of a complex key that combined metallic and spring elements to ensure constant compression and adaptability to thermal conditions. However, this approach was eventually simplified to a connector system that achieved the desired load transfer restoration with even greater efficiency. Practical applications of this method on French roadways and the development of specialized machinery for rapid installation highlight its potential to significantly extend the service life of concrete pavements at a lower cost compared to traditional maintenance strategies. This method's adoption could transform concrete pavement maintenance, offering a sustainable solution to common deterioration challenges faced worldwide. (Abstract generated by AI tool ChatGPT 4)

EFFECT OF HIGH TIRE PRESSURES ON CONCRETE PAVEMENT PERFORMANCE

This study, conducted by Construction Technology Laboratories, Inc. for the Portland Cement Association, investigates the impact of high tire pressures on concrete pavement performance. With the increasing use of trucks equipped with radial tires and high tire pressures, significant pavement damage has been observed across major highways in the United States and Canada. Unlike asphalt pavements, for which extensive research programs have been initiated, the effects of high tire pressures on concrete pavements have been less thoroughly studied. This research aims to fill that gap by examining how high tire pressures influence concrete pavement response, service life, and performance characteristics. Field testing across six sites in Wisconsin and Pennsylvania involved loading pavement sections with trucks equipped with tires at pressures ranging from 80 to 120 psi. Measurements of pavement strains, deflections, and the subsequent analysis suggested that increased tire pressure does not significantly affect concrete pavement response. Additionally, surveys of truck tire pressures in various states revealed that operational pressures are substantially higher than those used during the AASHO Road Test, upon which many pavement design equations are based. Despite the higher pressures, the research found no significant impact on pavement performance, indicating that current pavement thickness design procedures, which do not consider the effects of increased tire pressure, may still be adequate. This conclusion is supported by both theoretical analyses and field test data, which collectively indicate that increased tire pressures up to 120 psi do not significantly affect the performance or service life of concrete pavements. The study's findings suggest that existing design methodologies for concrete pavements remain valid, even in the face of changing tire technologies and usage patterns. (Abstract generated by AI tool ChatGPT 4)

Experimental Study of the Dynamic Behavior of Stabilised Marl with Lime

The variable characteristics of weathered marl cause engineering problems, particularly in geotechnics, and require in-depth studies to design structures. Where these characteristics are poor, lime is used to stabilize the soil. Experimental research is being carried out on various Tizi-Ouzou marls composed of different percentages of CaCO3. The aim is to study their behavior in the presence of quicklime and its impact on the evolution of their geotechnical characteristics to provide effective and economical solutions for stabilization. These marls are mixed with increasing percentages of lime and subjected to a series of tests in which cyclic shear is essential for simulating dynamic effects. The results obtained confirm the improvement in their geotechnical characteristics. On the one hand, interstitial pressures and cyclic deformations have decreased, thus avoiding the risk of liquefaction, subsidence, or settlement. On the other hand, cyclic stresses and resistances have increased, resulting in better resistance of these stabilized marls to dynamic stresses. Finally, the number of cycles required to reach failure has increased, thus reducing the risk of pavement damage. These results depend primarily on the percentage of CaCO3in the marl. Doi: 10.28991/CEJ-2025-011-01-09 Full Text: PDF

Critical response analysis of asphalt pavement on concrete curved ramp bridge deck considering tire-bridge interaction

ABSTRACT This study developed a full-scale concrete curved ramp bridge deck finite element (FE) model, which considered the effect of tire-bridge interaction. In this full-scale FE model, an inflated tire model was developed to simulate the rolling tire load. The tire-bridge interaction equations were established based on the different interaction modes of the driving and driven wheels with the deck pavement. The effects of travel speed, curvature radius and load position on the critical response of bridge deck pavement was analysed. The results indicated that the deck pavement above the mid-span and flange cantilever panel exhibited greater critical tensile stress and strain values; whereas the bearing end diaphragm and the flange longitudinal diaphragm contributed the maximum critical shear stress. In the vertical depth direction, the damage induced by the traffic load mainly initiated at the deck pavement surface, and shear damage was more prone to occur between the layers of different paving materials. The reduced curvature radius and increased travel speed both promoted the appearance of unbalanced damage in the inner and outer tire loading zones. Besides, the smaller curvature radii and higher travel speeds would result in more severe local damage of deck pavement.

FEM for improvement of damage prediction of airfield flexible pavements on soft and stiff subgrade under various heavy load configurations of landing gear of new generation aircraft

Abstract This study establishes the state-of-the-art requirements verification process applied to compute the damage of flexible airfield pavement from new French rational method. Flexible pavement structures with platforms A, B, C, and D, recommended by International Civil Aviation Organization (ICAO), were modelled under static loading of bogies from heavy weight aircrafts A340, B777, and A380 using Cast3M 3D finite element modelling. From the results of these computations, it appears that these structures A, B, C, and D recommended by ICAO are not equivalent from the point of view of mechanical behaviour as claimed by the empirical method for the design of aeronautical bituminous pavements with abacus. The representation of the strain shapes was done with 3D and 2D profiles to improve the quality of response and to clearly identify the critical areas when an aircraft bogie is passing. The four- and six-wheels bogies of the aircraft A380 are more destructive to flexible pavements than the bogies of the other aircrafts tested in this study. The calculation of damage according to the new French rational method for aeronautical flexible pavements revealed that the main damage to these pavements is due to the fatigue of the bituminous layers and not the rutting of subgrade and the unbound granular material layers.

Surrogate modelling of surface roughness for asphalt pavements using artificial neural networks: a mechanistic-empirical approach

ABSTRACT Pavement surface smoothness (or roughness) is crucial for traffic safety, driving comfort, and fuel efficiency. As a widely applied roughness indicator, an accurate forecasting of the International Roughness Index (IRI) and its deterioration is essential for the design, maintenance, and management of asphalt pavements. Previous studies have used field measurement data or AASHTOWare Pavement ME Design simulations for the development of machine learning (ML) models to streamline the IRI modelling. However, these models frequently lack the accuracy and robustness of the measurement data or high-fidelity computational simulations they are intended to surrogate. To address this issue, we employed a new adaptive sampling technique to generate an informative yet efficient pavement damage database from Pavement ME simulations. Utilising Artificial Neural Networks (ANNs), we engineered two types of surrogate ML models: (a) Model I, an ANN-based IRI predictive model, and (b) Model II, a hybrid model combining ANN-based predictions of rutting, fatigue damage, and thermal cracking with closed-form relationships between these indicators and IRI. Our findings show that Model II outperforms Model I in IRI modelling accuracy both globally and locally. Moreover, Model II matches IRI simulations of Pavement ME while providing enhanced efficiency and adaptability to a broader spectrum of design considerations.

Real-time pavement distress detection based on deep learning and visual sensors

Pavement ageing significantly affects traffic safety and requires timely maintenance. However, accurately identifying pavement conditions from images captured by in-vehicle cameras remains challenging. This paper proposes a lightweight pavement distress detection method, MASL-YOLO. To address multi-scale defects, the method employs multi-scale channel mix convolution to enhance feature fusion, thereby improving the sensitivity to pavement damage. A multi-path aggregation attention mechanism and deformable convolutions are used to enhance adaptive sampling, strengthening feature extraction in the backbone. Integrating a large-kernel separable structure into the spatial pyramid pooling fusion further enhances the network's generalisation capability in complex environments. Experiments show that MASL-YOLO achieves an mAP of 85.5%, a 5.1% improvement over YOLOv8n and operates at 73.7 frames per second, meeting real-time requirements. The model, integrated with the RealSense D455 visual sensor and the GNSS module on the detection vehicle, achieved fast and effective pavement distress detection in field tests.

Effects of using lannea coromandelica gum and coal waste in hot mix asphalt pavement on vehicle overloading

Abstract The predominant type of pavement currently in use is flexible pavement constructed with a hot asphalt mixture. However, with economic development advancing in various regions, transportation challenges, such as vehicle overloading, especially in developing nations, have emerged. It is crucial to enhance and innovate the materials used in asphalt mixtures, which form the primary structure supporting pavement loads, to address these issues effectively. Incorporating green materials sourced from natural and waste sources becomes essential for promoting sustainable development. This study investigates the utilization of materials derived from the sap of the lannea coromandelica tree, known for its natural resin-like adhesives, as well as coal waste as a filler in asphalt mixtures. Laboratory experiments were conducted alongside vehicle load data analysis, focusing on excessive vehicle loads on roads. The findings indicate that incorporating these green materials enhances the modulus value of the asphalt mixture, particularly in the lannea coromandelica gum with fly ash (LCGFA) mixture, which amounted to 4161 Mpa, followed by the lannea coromandelica gum with bottom ash (LCGBA) mixture by 3729 Mpa, compared to the control mixture, hot mix asphalt concrete. Additionally, these results influence the Truck Factor value of vehicles. The higher the truck factor value, the impact on the pavement structure is due to the vehicle load transmitted through the vehicle axis, which is forwarded by the pavement to the subgrade. The adoption of LCGFA and LCGBA reduces the Truck Factor value from 5,386 to 4,980 under the LCGFA mix and 5,143 under the LCGBA mix, indicating decreased pavement damage caused by the wheel axles of overloaded vehicles. Consequently, utilizing these green materials is considered capable of providing enhanced durability and environmental benefits to pavement structures. In addition, this material can be used by field practitioners to reduce material costs and environmental impact.

Simulation and application research of rubblization for aged cement concrete pavement

Simulation and application research of rubblization for aged cement concrete pavement

Full-scale testing and monitoring of geosynthetics-stabilized flexible pavement in Alberta, Canada

Full-scale testing and monitoring of geosynthetics-stabilized flexible pavement in Alberta, Canada

ANALISIS KUALITAS KOMBINASI VACUUM RESIDUE DAN HOT ROLLED SHEET PADA INFRASTRUKTUR JALAN

Roads are infrastructure that function as a link between one region and another that is used by the general public, and is passed by various types of motorized vehicles. Road pavement damage often occurs before reaching the design age due to peeling due to excessive moisture. The use of vacuum residue (VR) in hot rolled sheet (HRS) mixtures for road construction involves several important technical and economic considerations. This study analyzed the Marshall characteristics of HRS mixture properties using VR. The VR used came from AMP PT. Pertamina Persero with an average asphalt content of 5.88%. The results showed that the Marshall parameters that did not meet were voids in the mixture (VIM) and voids filled with asphalt (VFA), for other parameters had met the 2018 Bina Marga specifications. The Marshall stability value obtained was 1979.55 kg with a Marshall Quotient of 395.91 kg / mm. Based on the results obtained, it shows that the use of VR in the HRS mixture can increase the Marshall stability value.

Centrifuge tests study on settlement and damage modes of bridge approaches using deep-seated slab

Centrifuge tests study on settlement and damage modes of bridge approaches using deep-seated slab

Pavement crack detection based on depth-supervision FRRN model

Timely detection of early pavement distress is crucial for effective pavement maintenance. A promising approach involves the segmenting the road surface cracks area from its images. However, the previously employed full-resolution residual network (FRRN), when employing a large number of full-resolution residual units (FRRUs), is susceptible to challenges such as exploding and vanishing gradients. Addressing these issues, this paper has introduced a depth supervision mechanism into FRRN, leading to the development of the Depth Supervision FRRN (DSFRRN) model, designed specifically for accurate segmentation of cracks in road images. This model enhances nonlinear expressiveness while retaining essential features, achieving high precision in pavement crack segmentation. Through experimental validation using a dataset comprising 1565 images of damaged pavements, the result demonstrate that DSFRRN outperforms the original FRRN in terms of both F1 score and Jaccard index, accurately delineating cracks. Consequently, the automated pavement damage detection method presented herein facilitates cost-effective and efficient pavement inspection, contributing to the safeguarding of roadway surfaces and transportation infrastructure.

Analisis index kerusakan Jalan Rigid Pavement dengan metode Pavement Condition Index (PCI) pada Jalan Lebaksono – Jalan Purwojati Ngoro, Kabupaten Mojokerto

The lebaksono - purwojatingoro mojosari city is an industrial road. Various heavy and light vehicles pass through the road, causing road damage. Evaluation of road damage conditions is needed to monitor the level of road damage that occurs on a road section. This study aims to determine the level of damage that occurs. The method used in assessing the condition of this pavement damage is the PCI (Pavement Condition Index) method, conducting a visual survey by viewing and analyzing damage based on the type, level of damage and quantity of damage to serve as the basis for carrying out maintenance and repair activities. . The results of evaluating the condition of the lebaksono - purwojatingoro road section using the PCI method obtained divided slab damage (26.2%), patching small (7.82%), spalling corner (5.07%), shrinkage cracks (0. 85%), line crack (17.18%), spalling joint (4.79%), patching large (22.82%), punchout (0.85%), corner break (10.42), joint seal (1.13%), durability crack (0.85%), blow up / buckling (0.28%), popout (1.69%).