Resurfacing Research Articles

Effect of adding dune sand to tuff in Saharan road construction

The south region of Algeria is characterized by a wide surface, a scattered population and a very small ratio of road length per habitant. To allow the development of agricultural, industrial and touristic activities between different cities in the south of Algeria, it is necessary to maintain and to develop the road infrastructure. However the development of these infrastructures necessitates the use of huge amount of certified aggregates from quarries which is not available in the vicinity of the need. For these raisons, in the framework of sustainable development, a strategy which consists in using local materials like fine sediments (dune sand) and other types of material is engaged. The materials constituting the road layers, until today, have been limited to certain so-called noble materials (gravel, aggregates, etc.), but these are being depleted as a result of the intensive exploitation and the scarcity of quality careers. Gypso-limestone encrustation tuffs, the most used materials in pavements (base course and base course) in the Saharan areas such as southern Algeria, have shown acceptable behavior for many years until these last days, when this type of material begins to present certain limits under the effect of the intensity of the traffic. In order to promote the abundant wind sands in these regions, we are interested in developing the dune sands in the pavement as a mixture with the tuffs. The present work presents a contribution to the study of the behavior of the tuff of the Adrar region (South of Algeria) alone and mixed with the sand dunes in different formulations. The aim is to evaluate the evolution of mechanical properties including resistance to simple compression, the ability to compaction and punching (RBC). The work also discusses the influence of the addition of cement in low levels on the performance of the mixture.

Study on the improvement of fatigue and crack resistance of semi-flexible pavement materials using the mixing -molding method

This study focuses on two significant issues pertaining to conventional grout-molded semi-flexible pavement material (P-SFP): the difficult of achieving a high grouting rate and the limited scope for enhancing asphalt content, both of which contribute to the poor crack resistance of the SFP. To address these problems, the Mixed-Molding Method Semi-Flexible Pavement Material (M-SFP) is proposed, which utilizes a combination of mixed-molding method to enhance the crack resistance and fatigue life of SFP. In order to investigate the effects of asphalt film thickness and gradation type, four different gradations and five different asphalt contents of M-SFP were designed based on the volume filling theory. The effects of asphalt film thickness and gradation type on the cracking resistance and fatigue life of M-SFP were investigated through various tests, including low-temperature bending, semi-circular bending tensile, and four-point bending fatigue test. The results were then compared with those of the control P-SFP. The test results show that the strain energy density of M-SFP is increased by 24.9 % and the fracture energy is increased by 52.1 % compared with the conventional P-SFP; the number of fatigue life times under 200με, 225με, and 250με microstrain are increased by 53.6 %, 41.3 %, and 47.3 %, respectively. Based on crack resistance test results, it is recommended that the design asphalt film thickness of M-SFP exceed 10μm. Furthermore, measurements of the air void content reveal that the M-SFP exhibits significantly better compactness compared to the P-SFP. In conclusion, it shows that the Mixing-Molding method can be used to obtain semiflexible pavement materials with higher asphalt dosage, better cracking resistance, better degree of compactness, and longer fatigue life. In addition, the correlation analysis between the cracking resistance results and the rigid-flex ratio indicates that the recommended design rigid-flex ratio for SFP should be less than 2.06.

Computational renormalization for thermal conductivity of porous asphalt concrete based on hybrid finite element-neural network method

Thermal conductivity of porous asphalt concrete (PAC) directly affects PAC pavement temperature field, which is closely related to the heat island effect in summer and pavement icing in winter. Due to the large and complex pores and the uneven surface in PAC, there is measurement uncertainty using traditional laboratory tests. In this study, a finite element-neural network (FE-NN) method was proposed to predict the thermal conductivity of PAC based on the three-dimensional (3-D) heterogeneous structure. Additionally, laboratory tests were conducted to measure the thermal conductivity of PAC, fine aggregate mixture (FAM), and basalt aggregate. The results served as input parameters for the FE-NN method and were used to verify its accuracy. Based on the validated method, various factors affecting the thermal conductivity of PAC were analyzed. The analysis results show that, compared to the transient plane source (TPS) method, the backcalculation method can achieve results similar to those obtained with the TPS method for basalt aggregate and FAM, but provides more stable measurements when applied to PAC. The accuracy of the FE-NN method is acceptable, with relative errors of 1.92∼4.34 % compared to the experimental results. Besides, 2-D structural models tend to underestimate the effective thermal conductivity of PAC, with values 83.2∼84.1 % lower than those calculated by 3-D models. When the representative volume element (RVE) sizes are larger than 256×256×256, the variances show little differences and are acceptable. Furthermore, typical aggregate thermal conductivity values were used as input, revealing a nonlinear increase in the effective thermal conductivity of PAC. When the void content increased from 18 % to 24 %, the effective thermal conductivity of PAC decreased by 19.83 %. The effective thermal conductivity of PAC changes more significantly with the thermal conductivity of the aggregate than that with the variation of porosity in an interval. The analysis findings provide insights for better evaluating the pavement temperature field and heat transfer to improve the PAC pavement material designs.

Innovative Pavement Solutions: A Comprehensive Review from Conventional Asphalt to Sustainable Colored Alternatives

Climate change significantly impacts transportation infrastructure, particularly asphalt pavements. Similarly, the heat absorption of paved surfaces, especially conventional black pavements, significantly intensifies the urban microclimate. Paved surfaces, including asphalt pavements, account for over 30% of the covered surfaces and are vulnerable to rising temperatures, which cause not only pavement distress, such as rutting and cracking, but also urban heat islands (UHI). Sustainable pavement solutions, specifically colored pavements, have been investigated for their potential to mitigate these effects. This review presents an extensive overview of current pavement technologies, emphasizing conventional asphalt’s economic, environmental, and functional characteristics. A discussion of the benefits and challenges of colored pavements is also provided, including their ability to reduce UHI, enhance safety, and contribute to sustainable urban growth. This paper discusses advancements in pavement material science, the use of recycled materials, and the application of reflective coatings, providing insights into sustainable infrastructure development. Transitioning from conventional black pavements to sustainable colored alternatives is not merely a matter of material choice but a strategic transition toward resilient urban planning. Increasing demand for environmentally friendly infrastructure could prompt the construction industry to adopt colored pavements as a tool to promote environmental stewardship.

Trajectory tracking multi-constraint model predictive control of unmanned vehicles based on sideslip stiffness estimation with XGBoost algorithm

When the vehicle is driving at high speed on a slippery road, the sideslip stiffness of the tire which is closely related to the lateral force of the tire, will vary with the change of road conditions, tire inflation pressure, vertical load, and other factors. If the tire sideslip stiffness is set to a fixed value in the control system based on the model design, the uncertainty of the sideslip stiffness will cause a large error with the actual application. Therefore, in order to improve the trajectory tracking accuracy of the vehicle on the slippery road surface under the premise of ensuring the stability of the vehicle, an intelligent vehicle trajectory tracking control strategy considering the influence of sideslip stiffness is designed in this paper. In order to solve the multiple constraints of the vehicle driving on the low-adhesion road surface, a trajectory tracking controller based on the multi-constraint model predictive control algorithm is designed, and then the tire sideslip stiffness estimation strategy is designed based on the XGBoost algorithm, and the estimated sideslip deviation stiffness is added to the trajectory tracking control model. Carsim and MATLAB/Simulink are used to perform co-simulation to verify the accuracy of the proposed tire sideslip stiffness estimation and the tracking performance of the trajectory tracking controller. In order to further verify the reliability of the research content, the relevant working condition tests are carried out on the hardware-in-the-loop platform based on Carsim and LabVIEW, and the effectiveness of the trajectory tracking controller considering the influence of sideslip stiffness is verified.

Performance of natural asphalt as a paving material: A laboratory and field evaluation

The ever-growing need to build roads to meet the necessary transportation demands is challenging, especially for developing countries. Low-volume roads (LVRs) are usually the backbone of catalyzing economic growth in these countries. With impediments surrounding Petroleum bitumen (price fluctuations) and environmental concerns, scientists are putting their effort into finding an alternative. The presented research is an attempt to check if Natural asphalt can be used as a full or partial replacement of the Petroleum bitumen. To the best of the authors' knowledge, only limited studies have focused on characterizing and understanding the engineering properties of Natural asphalt. The available techniques do not provide reliable information to the road authorities and hence they are discouraged from using it in practice. Particularly for countries, where the Natural asphalt source is available, the overall dependence on importing the Bitumen could be substantially reduced. Empirical and experience-based design criteria may not be sufficient as the standards were never developed for such materials, hence, a scientific approach is required before bringing it into practice. In this research, Natural asphalt sourced from different locations in Nigeria was assessed. Before performing the mixture level tests using Marshall and Cantabro design methods, the rheological and fatigue properties of the extracted Natural bitumen were examined in the laboratory. In the design of the experiment, various percentages of Natural asphalt were added between 0 % and 20 % by total mix weight; implying that the remaining required fraction of binder was fulfilled by the addition of petroleum bitumen. By using a ranking system (supported by statistics), an optimal design of mixture was obtained which was used in the field (exposed to normal traffic) at 30 different sections. Overall, results showed a good correlation between laboratory and field performance as compared to the petroleum-based mixture which was used as a reference mixture

IRodd (intelligent-road damage detection) for real-time infrastructure preservation in detection, classification, calculation, and visualization

Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).

Real-Time Monitoring of Road Networks for Pavement Damage Detection Based on Preprocessing and Neural Networks

This paper presents a novel multi-initialization model for recognizing road surface damage, e.g. potholes and cracks, on video using convolutional neural networks (CNNs) in real-time for fast damage recognition. The model is trained by the latest Road Damage Detection dataset, which includes four types of road damage. In addition, the CNN model is updated using pseudo-labeled images from semi-learned methods to improve the performance of the pavement damage detection technique. This study describes the use of the YOLO architecture and optimizes it according to the selected parameters, demonstrating high efficiency and accuracy. The results obtained can enhance the safety and efficiency of road pavement and, hence, its traffic quality and contribute to decision-making for the maintenance and restoration of road infrastructure.

Verification of On-Site Applicability of Rainwater Road Surface Spraying for Promoting Rainwater Utilization and Analyzing the Fine Dust Reduction Effect

This study conducted a pilot test and field demonstration to analyze the feasibility of using rainwater for road surface sprinkling and its effectiveness in reducing fine dust to create sustainable cities. The pilot test results verified the effectiveness of rainwater sprinkling on road surfaces in reducing fine dust. Subsequently, to ensure field applicability, a test bed with different pavement sections was established along Ojeong-ro in Bucheon, Gyeonggi-do, and a circulatory system for reusing the runoff rainwater was installed and tested for its acceptable dust reduction effectiveness. The results showed that the section with porous pavement exhibited a significant reduction in acceptable dust levels, and a trend of decreasing pollutant levels due to the initial washing effect of rainwater was observed. However, the water quality and quantity analysis revealed that additional purification processes are necessary to reuse the water for road surface sprinkling. Based on these findings, this study suggests that expanding porous pavement and introducing purification systems are essential for installing rainwater utilization facilities to reduce fine dust in urban areas. This research provides critical foundational data that can contribute to urban environmental improvement and establish a sustainable water circulation system.

EVALUATION OF BITUMINOUS MIXES WITH EPOXY-MODIFIED ASPHALT BINDERS

Road surfaces have long been made with bituminous mix because of its low cost and versatile applications. However, environmental variables, traffic loads, and ageing frequently affect its endurance. Many additives have been introduced to overcome these problems, and epoxy resin has shown great promise. This study evaluates bituminous binder and bituminous mixes with different percentages of epoxy modification. Epoxy asphalt binder's (EAB) rheological properties were described. Following that, an evaluation was conducted on the engineering properties of an epoxy asphalt mixture (EAM). The results demonstrated that the rheological properties of EAB outperform those of neat binders. Furthermore, the outcomes demonstrated that EAM had better moisture damage performance in terms of static immersion test and retained Marshall stability test than the conventional hot dense graded bituminous mixes. According to the results, the ideal content for both VG 30 and VG 40 binders is 2% epoxy modification. Out of all the mix permutations, bituminous mixes with 2% epoxy modification yielded the best results. Comparing blends with control mixes or unmodified bituminous mixes, on the other hand, revealed a lower resistance to moisture damage than mixes with 3% epoxy modification with both binders. The study concludes that epoxy resin can significantly improve the performance and longevity of asphalt concrete roadways, offering benefits to the road construction industry.

Огляд методу визначення пластичності литої асфальтобетонної суміші, який базується на встановлені глибини занурювання випробувального стрижня

Introduction. Mastic asphalt concrete is one of the oldest road construction materials used for road pavements. Problem Statement. Mastic asphalt concrete is a type of hot asphalt concrete, a feature of which is an increased amount of mineral powder and bitumen binder, due to which mastic mixtures can be placed in the road surface without compaction. Therefore, one of the main technological indicators of the quality of mastic asphalt mixtures is their fluidity. This indicator is one of the most important for designing the composition of the mastic asphalt mix, establishing the optimal amount of bitumen binder and setting the technological temperatures for preparing the mix at the plant and placing it in the road surface. Despite this, this indicator is not currently defined or standardized in the domestic road industry. The purpose. The aim of the study was to review the method for determining the plasticity of mastic asphalt mixtures based on the immersion depth of the test rod, as well as to establish the possibility and feasibility of its use for assessing the quality of mastic mixtures.

Real-time monitoring of urban roadway health: Utilizing GPR techniques for the early detection and classification of subsurface cavity diseases

The effectiveness of ground penetrating radar (GPR) in identifying and categorizing diseases that occur underground beneath the surfaces of urban roads is investigated in this study. Both 2D and 3D forward modeling use simulation with the GprMax program to show the response characteristics of common cavity illnesses, which facilitates interpretation in practical situations. The cavity morphology classification accuracy is improved to 90.5% by using convolutional neural networks (CNNs), specifically transfer learning with AlexNet. This method outperforms existing approaches even with minimal data. Four primary types are identified from an analysis of 1965 subsurface cavity data: hollow bodies, empty bodies, loose bodies, and water-rich bodies. These categories are important for evaluating road risks such as voids and subsidence. However, it is still difficult to interpret picture features linked to cavity diseases accurately because of a variety of elements, such as anthropogenic, environmental, and geological influences. However, the accurate interpretation and recognition of image features related to cavity diseases remain challenging. Moreover, there are various factors involved in the formation of underground diseases and cavities, including geological and environmental factors, physical and chemical properties of the geotechnical materials, anthropogenic engineering activity and social population or commercial effects.

Комплексне оцінювання стану дорожнього покриву

Introduction. This article deals with the issue of reviewing existing methods and approaches to assessing the condition of the road pavement and proposes a methodology for assessing the condition of the road pavement using a complex indicator. This indicator is used to analyze the defects and destruction of the pavement determined by the visual method. Problem. The need to improve the methodology for assessing the condition of the road surface (rigid, non-rigid) by calculating the coefficient by which the designer or balance holder can assess the condition of the existing pavement. The purpose of the article. To inform road industry specialists about new trends and developments in the field of road pavement inspection of roads and airfields.

Огляд методичних підходів до планування робіт з експлуатаційного утримування автомобільних доріг

Introduction. The development of Ukraine's road network under current conditions is characterized by limited funding for road maintenance. At the same time, determining the scope and list of works based on the actual operational condition of the roads is extremely important, as it significantly affects the safety and comfort of road users, as well as the efficiency of vehicle operation. A standard norm is used to determine the planned scope of work, which is averaged for roads of the corresponding category. This simplifies calculations, but such an approach does not precisely establish the annual planned volumes of maintenance work for a specific section, as it does not consider its actual operational condition. Given the current level of funding, it is relevant to develop a methodology for determining the planned volumes and lists of maintenance work that is accurate enough, but does not require significant costs for road section inspections. Problem Statement. The determination of the scope of maintenance work is based on a comprehensive analysis of the road surface condition, forecasted traffic loads, and the allocation of budgetary resources. However, under martial law, the country’s priorities have shifted, with the focus on ensuring state defense, providing humanitarian aid, etc. Based on the current trends in the development of Ukraine’s road industry, the main task is the rational use of limited financial resources and maintaining roads in proper operational condition.

Аналіз підходів щодо оцінювання просочування опадів у ґрунт узбіччя автомобільних доріг

Introduction. The article investigates the impact of atmospheric precipitation on road structures, specifically focusing on water infiltration into the roadside soil along highways, which is a critical aspect of road infrastructure maintenance. Ensuring the reliable operation of the roadway is becoming increasingly important due to rising traffic loads and climate changes that result in increased precipitation. Continuous moisture penetration into the road embankment can lead to road degradation, creating risks for safe traffic movement and necessitating frequent repairs. It is essential to develop and implement effective methods for assessing moisture infiltration into the soil, which will help ensure the longevity and cost-efficiency of road operation. Problem Statement. With climate change and increasing intensity of precipitation, the issue of assessing its impact on road structures becomes more relevant. Moisture accumulation in the road embankment can disrupt the stability of the soil foundation, reducing the load-bearing capacity of the road surface. Research aimed at analyzing rainfall infiltration and its effect on road structures will allow the implementation of effective solutions to maintain the operational condition of roads.

Research on adaptive hydraulic drive optimization control of concrete mixing tank truck for open-pit mine.

The non-axisymmetric problem caused by the fluid sloshing in the tank of a mining concrete mixing tank truck during driving is affected by the excitation of complex road surfaces. The fluid sloshing is coupled with the dynamics of the vehicle body due to the excitation of the complex road surface. The traditional hydraulic drive proportional integral differential (PID) control method is not effective in dealing with such problems, which can easily lead to accidents such as overturning. To improve the accuracy and stability of the hydraulic drive control system, this paper proposes an optimized particle filter PID adaptive control method based on the elastic firefly (FA) algorithm to accelerate the convergence speed of control parameter optimization, and then analyzes its hydraulic drive control characteristics and structural applications, and discusses step steering and double lane change modes are simulated under filling rates of 1.5 and 2.0, respectively. The experimental results show that compared with traditional PID control, the proposed adaptive control method can significantly reduce the average speed error of hydraulic drive control to 0.03km/h and the maximum speed error to 0.17km/h. It also improves the control tracking performance and stability. The practicality of the adaptive hydraulic drive is verified in the filling rate experiments under step steering and double-lane shifting conditions. It has important reference value for the practical application of hydraulic drive control optimization of mining concrete mixing transport tank trucks.

Перспективи застосування жорсткого дорожнього одягу під час будування автомобільних доріг та удосконалення підходів до його конструювання і розрахування

Introduction. This article examines the issue of improving the methods of designing and calculating rigid road surfaces, outlined in the DSTU project “Guidelines for the Design of Rigid Road Surfaces” (hereinafter referred to as the DSTU project). The specified methods were developed on the basis of domestic and global experience in the design of highways with rigid road surfaces, analysis of current legal acts, regulatory documents, technical literature related to the object of standardization, taking into account the availability of modern road construction materials and technologies. density of traffic flow, diversity of subsoil, including in complex engineering and geological conditions, peculiarities of road and climatic regions of Ukraine, etc. Problem statement. The need for improvement and a unified approach to the design of rigid road clothing, taking into account the peculiarities of its operation, with the determination of the appropriate parameters depending on the initial data and the effective use of material and technical resources.

Winter maintenance, snow removal, winter slipperiness, use of de-icing materials and their environmental impact

Introduction. One of the most important road works is road maintenance work, which includes technical supervision of the road, road structures and right-of-way for timely detection and elimination of defects, ensuring the operation of road elements, including artificial structures, in different periods of the year, in particular, in the winter period, keeping them in proper operating condition, and others. Problem statement. The performance of works on winter maintenance, namely the use of methods of combating snow drifts, elimination of winter slipperiness, has both a positive and a negative impact on the environment, which is due to the use of technical salt as one of the methods of ice prevention and elimination. Such melting anti-icing material accelerates the destruction of the road surface, reduces productivity, pollutes the soil and water bodies. Purpose. Review of the main road works performed by road enterprises during the winter maintenance of highways and their consequences for the condition of the road surface, right-of-way, soil and water bodies. Analysis of the experience of other countries regarding ecological approaches aimed at the winter maintenance of highways, taking into account the consequences for the ecosystem.

Potholes Detection in Doppler Radar Signal’s Power Spectral Density using Decision Tree

Potholes are defects on the surface of roads, streets, or pavements brought on by depressions or holes, which are hazardous for vehicles and pedestrians, whether small divots or huge craters. Various methods have been explored to improve the accuracy of potholes detection. Existing approaches have advantages and disadvantages. This paper presents the proposed method of pothole detection utilising Doppler Radar signal's Power Spectrum Density (PSD) together with the Decision Tree classification algorithm. While continuous waveform (CW) radar is able to identify moving targets, it cannot localise the exact depth of the reflector, which is the prominent characteristic of potholes. In addition, the target's reflected signal is likely to be masked by nearby harmonics. Since the radar is moving despite the target of interest, mounting it on a moving vehicle offers a different perspective. This paper explores the potential of Doppler radar's signal for pothole detection while comparing two Machine Learning (ML) techniques. A commercially over-the-shelf (COTS) K-LC2 Doppler radar was employed to acquire pothole and non-pothole raw datasets. Doppler signal was hardly distinguished between pothole and non-pothole, either in the time or frequency domain. Hence, Doppler signals were converted to power spectral density (PSD), and PSD's features were extracted. Extracted features were applied with the coarse Decision Tree (DT) and K-Nearest Neighbours (KNN) classification algorithms. The result exhibits a better accuracy of 91.2% for 80:20 distribution by using the Decision Tree.

Assessment of body balance status in bikers: a study using R

Road traffic injuries are one of the most important and serious causes of unnatural death in India. Two-wheelers, especially motorcycle accidents contribute significantly in this regard. In order to avoid accidents and consequent losses, emphasis should be given on safe riding. Besides the condition of the vehicle, the road surface, willingness to adhere to safety regulations, body balance is a key factor in safe riding two-wheelers in order to avoid meeting with accidents of different consequences. In this backdrop, the study was aimed to assess whether there is any differences in body balances between the Bengalee adult male motorcyclists and similar individuals who do not know how to ride a motorcycle. 41 consenting individuals, among which 25 motorcylcists and 16 indivuals who do not know to ride motorcycle, were participated in the study. Anthropometric measurements were carried out using standard procedures and tools. Body balances tests like timed up and go and single limb step test along with visuo-tactile reaction time test were performed. Statistical package R 4.3.0 was used for statistical analysis. Student’s t test was performed. The study showed significant (P<0.05) differences in body balance parameters between the two groups of individuals. Which leads to the conclusion that motorcyclists shown better body balancing ability than their counter group.