Search Results (209)

The construction industry is a major contributor to the global climate crisis, prompting increasing interest in minimising the embodied carbon of structures, whether through material production regulations or the optimisation of structural elements. While a wide body of literature addresses the reduction of embodied carbon in superstructures, limited attention has been devoted to the optimisation of foundations, particularly piles. This research introduces a hybrid genetic algorithm optimisation tool designed to minimise the embodied carbon of tension piles in different soil conditions. Six different pile types are analysed: solid and hollow concrete piles, steel pipes, universal column (UC) sections, and timber piles in both square and circular forms. The optimal design parameters for each pile type on undrained clay and loose sand are presented and compared. The results demonstrate the potential for reducing the embodied carbon of tension piles when utilising optimised designs. Finally, a case study involving an 8-metre-high cross-road signpost is presented, illustrating the practical application of the proposed optimisation algorithm for reducing embodied carbon in future designs. Full article

Alcalá de Ebro is located 35 km northwest of the city of Zaragoza, on the right bank of the Ebro River at the outlet of a ravine (Juan Gastón) towards the river, with a catchment area of more than 230 km². Over time, urbanisation and agricultural development have eliminated the last stretch of the drainage channel, and these water inputs have been channelled underground, filtering through the ground. This section of the Ebro Valley rests on a marly tertiary substratum, which promotes dissolution-subbing processes that can lead to sinkholes. The ground tends to sink gradually or suddenly collapse. Many studies have been carried out to understand not only the origin of the phenomenon but also its geometry and the area affected by it in the town of Alcalá de Ebro. In this sense, it has been possible to model an area around the main access road, where numerous collapsing sinkholes have been found, blocking the road and affecting houses. It also affects the embankment that protects the town from the floods of the river Ebro. These studies have provided specific knowledge, enabling us to evaluate and implement underground consolidation measures, which have shown apparent success. Several injection campaigns have been carried out, initially with expansion resins and finally with columnar development, using special low-mobility mortars to fill and consolidate the undermined areas and prevent new subsidence. These technical solutions propose a method of ground treatment that we believe is novel for this type of geological process. The results have been satisfactory, but it is considered necessary to continue monitoring the situation and to extend attention to a wider area to prevent, as far as possible, new problems of subsidence and collapse. In this sense, the objective is to continue the control and monitoring of possible phenomena related to subsidence problems in the affected area and its immediate surroundings, to detect and, if necessary, anticipate subsidence or collapse phenomena that could affect the body of the embankment. Full article

Traditional 3D radar can only detect the planar characteristic information of a target. Thus, it cannot describe its spatial geometric characteristics, which is critical for accurate vehicle classification. To overcome these limitations, this paper investigates elevation features using 4D millimeter-wave radar data and presents a maximum likelihood estimation (MLE)-based vehicle classification method. The elevation data collected by 4D radar from a real road scenario are applied for further analysis. By establishing radar coordinate systems and geodetic coordinate systems, the distribution feature of vehicles’ elevation is analyzed by spatial geometric transformation referring to the radar installation parameters, and a Gaussian-based probability distribution model is subsequently proposed. Further, the data-driven parameter optimization on likelihood probabilities of different vehicle samples is performed using a large-scale elevation dataset, and an MLE-based vehicle classification method is presented for identifying small and large vehicles. The experimental results show that there are significant differences in elevation distribution from two different vehicle types, where large vehicles exhibit a wider range of left-skewed distribution in different cross-sections, while small vehicles are more concentrated with a right-skewed distribution. The Gaussian-based MLE method achieves an accuracy of 92%, precision of 87% and recall of 98%, demonstrating excellent performance for traffic monitoring and related applications. Full article

The fundamental material parameter used in the thermal analysis of road pavement structures is the thermal conductivity. This parameter can be determined using various methods. The main objective of this paper is to compare and evaluate the thermal conductivity test results obtained using two different measurement methods. Thermal conductivity was determined using the steady-state and transient methods. The transient method is more cost-effective and faster but tends to produce a higher dispersion of results. In contrast, the steady-state method is more challenging to apply, particularly when testing large and heavy specimens of heterogeneous materials such as road pavement materials. For this reason, it is essential to assess the differences in results obtained by these two methods when applied to road materials. Two types of materials were tested in this study: an asphalt mixture and a cement concrete. The obtained results show statistically significant differences (α = 0.05), taking into account the two methods considered. The average difference can be estimated at 10% and 11% for asphalt mixtures and cement concretes, respectively. The obtained results are important for quantifying material parameters used in thermal and coupled thermal/structural analysis of pavement structures. This is particularly relevant in areas affected by urban heat islands and in road sections used as solar collectors. Full article

The differential toll policy has emerged as an effective method for regulating expressway traffic flow and has positively impacted the efficiency of vehicular movement, as well as balanced the spatial and temporal distribution of the road network. However, the acceptance of differentiated charging policies and the range of rates associated with these policies warrant further investigation. This study employs both revealed preference (RP) and stated preference (SP) survey methods to assess users’ willingness to accept the current differentiated toll scheme and to analyze the proportion of users opting for alternative travel routes and their behavioral characteristics in simulated scenarios. Additionally, we construct a Structural Equation Model-Latent Class Logistics (SEM-LCL) to explore the mechanisms influencing differentiated toll road alternative travel choices while considering user heterogeneity. The findings indicate that different tolling strategies and discount rates attract users variably. The existing differentiated tolling scheme—based on road sections, time periods, and payment methods—significantly affects users’ choices of alternative routes, with the impact of tolling based on vehicle type being especially pronounced for large trucks. The user population is heterogeneous and can be categorized into three distinct groups: rate-sensitive, information-promoting, and conservative-rejecting. Furthermore, the willingness to consider alternative travel routes is significantly influenced by factors such as gender, age, driving experience, vehicle type, travel time, travel distance, payment method, and past differential toll experiences. The results of this study provide valuable insights for highway managers to establish optimal toll rates and implement dynamic flow regulation strategies while also guiding users in selecting appropriate driving routes. Full article

To clarify the operational characteristics and driving risks of urban underground road curves, a real vehicle driving experiment involving 20 subjects was conducted at the Jiefangbei Underground Ring Road in Chongqing. High-precision instruments were utilized to collect driving data, including vehicle speed, lateral acceleration, and longitudinal acceleration. Significance tests were performed on lateral acceleration, longitudinal acceleration, entering curve deceleration, and exiting curve acceleration. The driver behavior risk at curves was evaluated using G-G diagrams, and the distribution characteristics of curve danger points were determined. Subsequently, models were established for the relationships between lateral acceleration, entering curve deceleration, exiting curve acceleration, and curve geometric parameters. The results show that: (1) significant differences exist in lateral and longitudinal acceleration under different radius ranges; (2) the sections with the highest curve danger levels in urban underground road curves primarily concentrate within the circular curve sections of curves; (3) the number of driving risk points per unit length (m) is not correlated with curve type, but significantly related to curve radius range; (4) the relationship models between entering curve deceleration, exiting curve acceleration, and curve parameters are upward-opening quadratic functions, whereas the relationship model between lateral acceleration and curve parameters comprises two quadratic functions with different orientations. Full article

Planning in forestry should be based on accurate and reliable data. UAVs equipped with RGB cameras can enable fast and relatively cheap surveys, but their accuracy depends on many factors. Therefore, it is necessary to determine when UAVs can be used and when this type of survey gives data that does not reflect the true ground situation. This research analyzed the usability of a UAV, equipped with a RGB camera, for recording normal cross-sections and side ditch depths of the forest road in a lowland forest. The research was conducted in two time periods: during winter and spring, i.e., outside and during the vegetation season. DTMs of the area researched were created based on aerial photographs taken with the UAV, Z values of terrain points were read, and the depths of side ditches were calculated based on read Z values. The water depth in the side ditches and the vegetation height on the entire road body width were recorded to determine the influence of these two variables on the UAV survey error. Terrain points were recorded with the total station, which was the reference measurement method. An analysis of the obtained (read) DTM Z values revealed RMSE values of 10.09 cm for winter (outside vegetation) and 36.41 cm for spring (vegetation) UAV survey. The side ditch, calculated based on the DTM of the winter and spring periods of UAV recording, were statistically significantly different from the side ditch depths measured using the total station. Correcting the obtained data with water depth and vegetation height lowered the differences in Z values, as well as the ditch depths visible from ${RMSE}_Z$ (7.70 cm) for the winter UAV survey, with no statistically significant difference in side ditch depths. In the case of the correction of spring recording data, ${RMSE}_Z$ was smaller (23.41 cm) than before correction (36.41 cm), and the depth of the side ditches was still statistically significantly different. The authors conclude that water and ground vegetation can significantly affect UAV survey accuracy. In the winter period, side ditch depth measurement is possible in areas where water is not present. If water is present, manual measurement of water height and correction of obtained UAV data can improve data accuracy. On the other hand, spring or vegetation period UAV surveys are highly affected by ground vegetation height and the authors do not recommend surveys in that period. Full article

The swift advancement in monitoring and evaluation systems for road pavement conditions highlights the crucial role that this field plays in ensuring the sustainability of roads. This, in turn, contributes to the growth and prosperity of nations and enables users to enjoy the highest levels of luxury and comfort. Despite numerous studies and ongoing research, finding the most precise and efficient monitoring systems to determine the type and severity of road defects, their causes, and appropriate treatments remains a challenge. This study proposes a system that employs a camera to create an application capable of evaluating road conditions with ease by taking images while driving over the road. Based on the results, the application was accurate in identifying road defects of different severity within the same category. The proposed method was compared to the Pavement Condition Index (PCI) method, and a significant match was found in determining the type and severity of each defect on the selected road sections. More clearly, the overall accuracy of detecting and classifying block cracks, alligator cracks, longitudinal cracks, and potholes was significant for detecting and classifying the patches. Full article

Promoting alternative modes of transportation such as cycling represents a valuable strategy to minimize environmental impacts, as confirmed in the main targets set out by the European Commission. In this regard, in cities throughout the world, there has been a significant increase in the construction of bicycle paths in recent years, requiring effective maintenance strategies to preserve their service levels. The continuous monitoring of road networks is required to ensure the timely scheduling of optimal maintenance activities. This involves regular inspections of the road surface, but there are currently no automated systems for monitoring cycle paths. In this study, an integrated monitoring and assessment system for cycle paths was developed exploiting Raspberry Pi technologies. In more detail, a low-cost Inertial Measurement Unit (IMU), a Global Positioning System (GPS) module, a magnetic Hall Effect sensor, a camera module, and an ultrasonic distance sensor were connected to a Raspberry Pi 4 Model B. The novel system was mounted on a e-bike as a test vehicle to monitor the road conditions of various sections of cycle paths in Rome, characterized by different pavement types and decay levels as detected using the whole-body vibration $a_{wz}$ index (ISO 2631 standard). Repeated testing confirmed the system’s reliability by assigning the same vibration comfort class in 74% of the cases and an adjacent one in 26%, with an average difference of 0.25 m/s², underscoring its stability and reproducibility. Data post-processing was also focused on integrating user comfort perception with image data, and it revealed anomaly detections represented by numerical acceleration spikes. Additionally, data positioning was successfully implemented. Finally, $a_{wz}$ measurements with GPS coordinates and images were incorporated into a Geographic Information System (GIS) to develop a database that supports the efficient and comprehensive management of surface conditions. The proposed system can be considered as a valuable tool to assess the pavement conditions of cycle paths in order to implement preventive maintenance strategies within budget constraints. Full article

Establishing an accurate vehicle fatigue load spectrum is a critical prerequisite for fatigue life analysis and design of highway bridges. However, the time-varying and regional characteristics of vehicle loads pose significant challenges to achieving this goal. This study focuses on vehicle data collected by a weigh-in-motion system installed on a highway bridge in Chongqing, China. The statistical characteristics of vehicle-load-related parameters are analyzed, and the actual vehicle fatigue load spectrum for this section of the road is established. Specifically, vehicles are first categorized based on axle count characteristics. Then, statistical analyses are conducted on key parameters such as vehicle weight, headway time, and axle load for each vehicle type. Finally, the actual vehicle fatigue load spectrum is developed based on Miner’s linear damage rule and the equivalent fatigue damage principle, and the contributions of different vehicle types to fatigue damage are investigated. The results show that the weight distributions of different vehicle types follow a Gaussian mixture distribution, while the headway time distribution for each lane follows a log-normal distribution. A linear approximate relationship was observed between the axle loads of different vehicle types and their respective total weights. Although two-axle trucks exhibited higher frequencies, six-axle trucks contributed the most to structural fatigue damage, accounting for 53.81%. Therefore, six-axle trucks can be regarded as the standard fatigue vehicle model for this section of the road. These findings provide valuable insights for fatigue design and fatigue life assessment of highway bridges under similar vehicle loading conditions. Full article

Mechanical construction has gradually been applied in cross passages of metro lines, but more mechanical mechanisms should be revealed. The section between Jingrong Street Station and Kunjia Road Station in Suzhou Metro Line 11 adopts a mechanical construction method to construct a cross passage. A novel flat-face cutterhead, which is different from curved cutter head is first used to cut and break the main tunnel in construction of cross passage. Based on the background of practical engineering, the finite element method was applied to simulate the breaking process of the main tunnel to explore the dynamic variation in the mechanical response of the segments cut by the flat-face cutterhead. The results indicate that the maximum vertical displacement caused by cutting mainly concentrates on the top of the fully cut rings. The maximum horizontal displacement occurs at the waist on the side of the tunnel portal in the semi-cut rings. The axial force level inside both types of segment rings reaches its peak after the tunnel is formed. The maximum axial force exists at the bottom and top of the fully cut ring and semi-cut ring, respectively. The change in the displacement around the portal is not substantial before the third stage, and it begins to increase significantly from the moment the concrete at the portal is penetrated. The existence of the pre-support system effectively controls the displacement of the third and fourth fully cut rings. Emphasis should be placed on reinforcing the soil near the top and waist of the second to fifth rings. The findings demonstrate that the application of flat-face cutterhead in mechanical construction of cross passages is safe, reliable, and efficient, and can provide valuable suggestions for further cutting parameters and soil reinforcement as well. Full article

Aiming at the problem that asphalt pavement materials in plateau areas are vulnerable to freeze-thaw damage, research was carried out on asphalt pavements of representative road sections, and the temperature within the pavement structure was monitored using buried sensors. Based on this, an indoor test method for high-frequency freeze-thaw was established, and UV, thermo-oxygen-aging and high-frequency freeze-thaw tests were combined. The effects of aging and maximum aggregate particle size on the resistance of asphalt mixtures to high-frequency freeze-thaw were investigated using the splitting strength ratio, mass-loss rate and void-ratio changes by employing the newly made RS-type modified asphalt in the laboratory. At the same time, the high-frequency freeze-thaw resistance of the asphalt mixture was compared with that of the SS/SMA-13 asphalt mixture on the top layer of a representative road section. The results show that UV aging at 180 h followed by thermal-oxygen aging at 120 h has the greatest impact on the asphalt mixture; in this condition, the high-frequency freeze-thaw-cycle asphalt mixture with freeze-thaw damage is affected by the rule of change of the third-degree polynomial. In the plateau environment conditions, compared with the original pavement material (SS-type modified asphalt), the RS-type modified asphalt has better anti-aging properties, adhesion properties and elasticity performance. Full article

In recent years, advanced footwear technology (AFT) has been shown to improve performance in long-distance road running by altering biomechanics and perceived comfort. This type of footwear is now being marketed for mountain running, although its effects in such races remain unevaluated. This study aimed to examine the impact of AFT on performance, biomechanics, and perceived comfort during a simulated mountain running event. Twelve trained mountain runners participated in a 3-day experiment, with a 7-day recovery between sessions. On the first day, a maximal aerobic speed test assessed the runners’ performance levels. On the second day, participants familiarized themselves with a 5.19 km mountain circuit and comfort scale. On the third day, they completed two time trials on the same circuit, separated by 30 min of passive recovery, using conventional and AFT shoes in a randomized order. Physiological and biomechanical variables were recorded, including body mass, blood lactate, running biomechanics, vertical stiffness, shoe comfort, and rating of perceived exertion (RPE). The findings indicate that AFT does not improve performance or physiological responses during a simulated mountain race, regardless of segment (uphill, downhill, or mixed). However, AFT significantly alters running biomechanics, reducing step frequency and increasing the vertical oscillation of the center of gravity, especially in uphill and downhill sections. While overall comfort remained unchanged, specific differences were observed with AFT. Coaches and practitioners should consider these findings when using AFT in mountain running training or competition. Full article

To obtain the optimal driving visual guidance methods in sudden low-visibility fog environments, it is crucial to analyze the changes in visual characteristics and information demand under low-visibility foggy conditions. The paper constructs a driving visual information demand model for foggy environments based on visual information input and output, using Shannon’s theory and feedback control theory. Two types of foggy road sections with the same visibility, one with guidance lights and one without, were selected for real-vehicle experiments based on the driver’s blood pressure, heart rate, and driving gaze domain tests. The study found the following: (1) In sudden foggy environments, the amount of driving information obtained by drivers decreases instantly with a sudden drop in visibility, failing to meet the information demand for driving cognition, thereby disrupting the dynamic balance state of driving based on speed, visibility, and other road environment factors. The experiment also found that in low-visibility environments, the radius of the human eye’s visual gaze domain becomes smaller, with the gaze range mainly concentrated directly in front of the vehicle, and the lower the visibility, the smaller the gaze domain range; (2) Foggy conditions affect changes in drivers’ blood pressure and heart rate. Installing guidance lights with sufficient illumination at foggy sections to compensate for drivers’ visual information can effectively supplement the visual information required for safe driving; (3) The experiment indicates that the guidance effect of the lights is most pronounced when visibility is within the range of [50 m, 150 m]; however, when visibility is above 500 m, the presence of guidance lights can, to some extent, affect driving safety and increase the risk of accidents. Full article

Roads are critical components of infrastructure, and assessing their quality is essential to ensure the safe transport of people and goods, which in turn supports economic prosperity. Various factors, such as subsurface conditions, moisture content, and temperature, influence road performance and can degrade their efficiency as transportation networks. While surface road defects can often be identified through visual inspection, information about subsurface extensions, their impact on structural integrity, and potential risks remain concealed. This study aimed to perform a comparative analysis of dielectric permittivity (ε) using time-lapse Ground Penetrating Radar (GPR) measurements on pre- and post-renovated road sections. This study also sought to evaluate the effectiveness of this approach for road assessment and to employ forward modeling for a deeper understanding of road defects and their associated hazards. Results revealed that the pre-renovated road section exhibited significant fluctuations in dielectric values, ranging from 3.13 to 15.9. In contrast, the post-renovated section showed consistent values within a narrow range of 5 to 6.6. Different crack types were classified, and the mean ε for each visually identified crack type was calculated. Despite the higher frequency of transverse cracks compared to other defects, longitudinal cracks exhibited the highest mean dielectric value (~10.3), while alligator cracks had the lowest (~8.33). Numerical simulations facilitated accurate interpretation of the defects identified in the road section, providing insights into their nature and associated risks. The methodology used for crack classification and numerical simulation can be applied to other road sections globally, offering a standardized approach to road assessment and maintenance planning. Full article