Search Results (26)

This study investigates the fracture initiation and propagation mechanisms of continuously reinforced concrete–asphalt (CRC+AC) composite pavements under the synergistic effects of diurnal temperature fluctuations and non-uniform tire loading. A three-dimensional (3D) thermo-mechanical coupled finite element (FE) model was developed, with its underlying mechanical framework validated through laboratory-scale model tests conducted at 20 °C. The experimental results, involving strain monitoring at varying depths, demonstrated a high degree of consistency with numerical predictions in terms of spatial strain distribution, thereby ensuring the model’s reliability in capturing interlayer load-transfer efficiency. Building upon this validated mechanical foundation, numerical simulations were extended to analyze the low-temperature fracture response. The numerical results indicate that the maximum longitudinal and transverse tensile stresses in the asphalt layer are concentrated at the pavement surface, whereas the maximum shear stress occurs at a depth of 2–3 cm near the leading and trailing edges of the wheel load. Under low-temperature gradients, the Mode I stress intensity factor (K_I) at the crack tip exhibits a distinct diurnal opening–closing–reopening pattern, peaking at approximately 220 kPa·m^1/2 during the early morning hours (05:00–06:00). Furthermore, numerical simulations reveal the significant sensitivity of shear-sliding to axle loads; specifically, the peak Mode II stress intensity factor (K_II) increases monotonically from 190 to 230 kPa·m^1/2 as the axle load rises from 10 t to 16 t. Under non-uniform contact pressure, longitudinal cracking is primarily characterized by a mixed Mode I and Mode II mechanism driven by coupled tensile and shear stresses, whereas transverse cracking is dominated by Mode II shear failure. These findings suggest that implementing targeted traffic restrictions for overloaded vehicles during identified high-risk time windows can significantly enhance the structural durability and service life of composite pavements in cold regions. Full article

Reliable traffic load characterization remains a critical challenge in many African countries due to the lack of continuous field measurements. This study developed an integrated dynamic traffic monitoring and weigh-in-motion system on representative highways in Kenya to obtain long-term, multi-source traffic data. Traffic operations were quantified across hourly, weekly, and monthly scales, including flow variability, vehicle class composition, axle loads, overload behavior, and speed distributions. Results indicate that the spatiotemporal characteristics of traffic volume show pronounced short-term fluctuations but strong long-term stability. Despite their lower proportion, multi-axle heavy trucks dominate structural loading, with overload ratios exceeding 80% and gross weights approaching 100 t. Over 60% of vehicles operate at medium-to-low speeds (20–60 km/h), extending load duration and increasing pavement damage potential. These combined effects indicate that average indicators alone underestimate true loading demand. The proposed framework provides field-based traffic load spectra and a transferable methodology for traffic monitoring and pavement design optimization across developing regions in Africa. Full article

Heavy and overloaded freight traffic strongly affects pavement performance, yet short-term weigh-in-motion (WIM) measurements are not easily converted into design-oriented traffic inputs. Using the Nairobi Southern Bypass in Kenya as a case study, this study develops axle load spectrum (ALS) and equivalent single axle load (ESAL) indicators from more than 1.5 million axle group records collected between June and December 2025 and proposes an XGBoost-based conditional axle load spectrum (CA-ALS) framework. The data revealed strongly right-skewed load distributions, with a limited number of heavily loaded axle groups dominating pavement damage. Compared with the static ALS by axle group type baseline, the CA-ALS reduced log loss from 2.7563 to 2.6709 in conditional spectrum prediction. In the December 2025 tandem axle benchmark, the CA-ALS increased the ESAL-based verification input by 6.0% at b = 4 and 11.1% at b = 5 relative to the stronger static reference. A legal-load-capped counterfactual analysis further showed that, for all heavy vehicles, observed overloading increased ESAL by 161.0% at b = 4 and 239.4% at b = 5. These results indicate that the CA-ALS provides condition-sensitive traffic inputs for design traffic verification, scenario-based pavement checks, and overload-sensitive evaluation based on short-term WIM observations. Full article

Vehicle loads constitute the dominant source of dynamic excitation for small- and medium-span bridges, exerting a critical influence on bridge safety and service performance. However, vehicle load characteristics exhibit pronounced temporal variability and strong regional heterogeneity, which poses challenges for accurately characterizing the in-service loading conditions of bridges in specific regions using conventional dynamic load models. Therefore, this study focuses on the actual operational characteristics of vehicles on the Lieshihe bridge and the effects of vehicle loads and proposes a stochastic vehicle load simulation method based on the Monte Carlo sampling technique and weigh-in-motion (WIM) measured data. Initially, the recorded vehicle data are classified into representative vehicle models, and statistical analyses are conducted to characterize lane-dependent traffic flow variations and the occurrence patterns of vehicle overloading. Subsequently, axle number and axle spacing are selected as the core indicators for vehicle classification, based on which vehicles are categorized into five representative vehicle types. The changing patterns of axle load, vehicle weight, vehicle speed, etc., for each vehicle type are studied, and corresponding probability density distribution models are established to describe the stochastic nature of vehicle characteristics. Finally, using the Monte Carlo method combined with important attributes of vehicle flows, a stochastic vehicle load model is established based on the spatial–temporal characteristics. The results demonstrate that the vehicle weight on the bridge exhibits a Gaussian mixture distribution with multi-peaks, characterized by similar peak magnitudes but markedly different occurrence frequencies; axle load shows a single-peak distribution of Gaussian distribution with small differences in peak values and frequencies. Full article

Despite continued efforts by the Korean government to improve road safety, truck-related accidents remain disproportionately fatal, with a rate approximately 2.6 times higher than that of passenger vehicles. Although legal regulations prohibit overloading and improper loading, existing enforcement practices—primarily dependent on low-speed weigh-in-motion (WIM) systems—are limited in coverage and responsiveness. This study develops and validates standardized test procedures for detecting overloading and improper loading in commercial freight vehicles using a high-speed weigh-in-motion (HS-WIM) system. The HS-WIM system offers advanced sensing capabilities, including vehicle speed, length, axle configuration, and weight measurement at highway speeds. However, Korean HS-WIM performance standards currently lack detailed guidance, especially concerning group axle load testing and asymmetric cargo detection. To address these regulatory and technical gaps, a comprehensive set of test scenarios was designed based on domestic and international standards. A dedicated testbed was constructed, and 12 commercial vehicle types were tested under varied speeds and loading conditions. The proposed procedures reliably detect violations, and the study introduces evaluation criteria that improve HS-WIM system accuracy and support future enforcement and policy development in Korea. Full article

Overloaded trucks directly contribute to road infrastructure deterioration and undermine safety, posing significant challenges to sustainability. This makes enforcement to reduce their numbers and impacts essential. Weigh-in-motion (WIM) systems use road-embedded sensors to measure truck weights and enforce regulations. However, WIM cannot be installed on all routes, and some overloaded truck drivers can detour to avoid them instead of giving up overloading if the detour penalty is still lower than the extra profit from overloading. This paper focuses on optimal WIM location planning for overloaded truck management, incorporating a demand shift and user equilibrium model based on the utility functions of overloaded and non-overloaded trucks. The presented framework includes an upper-level problem for WIM placement and a lower-level problem for demand shifts and traffic assignments among overloaded trucks, non-overloaded trucks, and light-duty vehicles for a given WIM placement. Particularly, at the upper level, the primary objective is to minimize the traffic loadings, i.e., the expected equivalent single-axle load–kilometers per unit time, with the secondary objective of minimizing the total traffic disruptions over the target network. Simulations and sensitivity analyses are conducted through a numerical example. Consequently, this study proposes an optimal WIM placement framework that considers drivers’ utility-based route choice and social costs such as ESAL and traffic congestion. Full article

Weigh-in-motion systems can measure the number of axles to obtain a vehicle’s type and upper limit of weight, which, combined with the weight measured by the system, can be used for highway toll collection and overload management. This paper proposes a new modular system based on multi-sensor fusion and neural network axle recognition to address issues concerning the high failure rate of axle recognition devices and low weighing accuracy. We use a modular system consisting of multiple weighing platforms, enabling whole-vehicle-load weighing with multiple vehicles traveling through platforms. In addition, we propose a sequential generation model based on a Transformer and Gated Recurrent Unit to calculate the weighing signal generated by the weighing sensors, and then obtain the number of axles and the gross vehicle weight. Finally, the axle recognition algorithm and modular systems are tested in multiple scenarios. The accuracy of the axle recognition is 99.51% and 99.84% in the test set and the toll station, respectively. The weighing error of the modular system in the test field is less than 0.5%, and 99.18% of vehicles had an error of less than 5% at the toll station. The modular system has the advantages of high accuracy, consistent performance, and high traffic efficiency. Full article

This study presents a detailed analysis of the stability of weigh-in-motion sensors used at vehicle weighing stations. The objective of this research was a long-term assessment of reading variability, with a particular focus on the sensors’ application in automated measurement stations. These investigations constitute a critical component of modern traffic management systems and vehicle overload control. The analysis covered the period from 2022 to 2024, incorporating data from vehicles participating in regular traffic as well as dedicated control runs using vehicles with known wheel and axle load distributions. The study also considered changes in road surface conditions, particularly rut depth, and their variations over the examined period. The findings revealed that, despite the lack of station calibration over the three-year period, the observed parameters exhibited only minor changes. These results confirm the high stability of the applied measurement system and its ability to maintain measurement accuracy over extended operational periods, which is essential for its practical application in real-world traffic conditions. Full article

In recent years, bridge collapses resulting from vehicle overloading have underscored the crucial necessity for real-time monitoring of traffic conditions on bridges, making pavement-based weigh-in-motion systems indispensable for large bridges. However, these systems usually have poor durability and will cause traffic interruptions during their installation and maintenance processes. This paper addresses the challenge of recognizing vehicle loads by proposing a vehicle load identification method based on machine vision and displacement influence lines. The technology consists of three essential steps. Firstly, machine vision technology is utilized to identify vehicle trajectories. Following this, the displacement response, monitored by millimeter-wave radar, is integrated to calculate the influence lines of the structure’s displacement. Lastly, an overall least squares method incorporating a regularization term is applied to calculate axle weights. The efficacy of the proposed method is validated within the monitoring system of a specific continuous beam. Importantly, the calibration of vehicles and the validation dataset rely on information monitored by the pavement-based weigh-in-motion system of adjacent arch bridges, serving as ground truth. Results indicate that the identification errors for gross vehicle weight do not exceed 25%. This technology holds significant importance for identifying vehicle weights on small to medium-span bridges. Due to its cost-effectiveness, easy installation, and maintenance, it possesses a high potential for widespread adoption. Full article

Hyperforin (HPF) is an acylphloroglucinol compound found abundantly in Hypericum perforatum extract which exhibits antidepressant, anti-inflammatory, antimicrobial, and antitumor activities. Our recent study revealed a potent antimelanoma effect of HPF, which hinders melanoma cell proliferation, motility, colony formation, and induces apoptosis. Furthermore, we have identified glutathione peroxidase-4 (GPX-4), a key enzyme involved in cellular protection against iron-induced lipid peroxidation, as one of the molecular targets of HPF. Thus, in three BRAF-mutated melanoma cell lines, we investigated whether iron unbalance and lipid peroxidation may be a part of the molecular mechanisms underlying the antimelanoma activity of HPF. Initially, we focused on heme oxygenase-1 (HO-1), which catalyzes the heme group into CO, biliverdin, and free iron, and observed that HPF treatment triggered the expression of this inducible enzyme. In order to investigate the mechanism involved in HO-1 induction, we verified that HPF downregulates the BTB and CNC homology 1 (BACH-1) transcription factor, an inhibitor of the heme oxygenase 1 (HMOX-1) gene transcription. Remarkably, we observed a partial recovery of cell viability and an increase in the expression of the phosphorylated and active form of retinoblastoma protein when we suppressed the HMOX-1 gene using HMOX-1 siRNA while HPF was present. This suggests that the HO-1 pathway is involved in the cytostatic effect of HPF in melanoma cells. To explore whether lipid peroxidation is induced, we conducted cytofluorimetric analysis and observed a significant increase in the fluorescence of the BODIPY C-11 probe 48 h after HPF administration in all tested melanoma cell lines. To discover the mechanism by which HPF triggers lipid peroxidation, along with the induction of HO-1, we examined the expression of additional proteins associated with iron homeostasis and lipid peroxidation. After HPF administration, we confirmed the downregulation of GPX-4 and observed low expression levels of SLC7A11, a cystine transporter crucial for the glutathione production, and ferritin, able to sequester free iron. A decreased expression level of these proteins can sensitize cells to lipid peroxidation. On the other hand, HPF treatment resulted in increased expression levels of transferrin, which facilitates iron uptake, and LC3B proteins, a molecular marker of autophagy induction. Indeed, ferritin and GPX-4 have been reported to be digested during autophagy. Altogether, these findings suggest that HPF induced lipid peroxidation likely through iron overloading and decreasing the expression of proteins that protect cells from lipid peroxidation. Finally, we examined the expression levels of proteins associated with melanoma cell invasion and metastatic potential. We observed the decreased expression of CD133, octamer-4, tyrosine-kinase receptor AXL, urokinase plasminogen activator receptor, and metalloproteinase-2 following HPF treatment. These findings provide further support for our previous observations, demonstrating the inhibitory effects of HPF on cell motility and colony formation in soft agar, which are both metastasis-related processes in tumor cells. Full article

Cracking is one of the main distresses in asphalt pavement. At present, few studies have been conducted on the cracking performance of asphalt mixtures from the field due to the difficulty of sample collection. Therefore, this study aims to assess the cracking resistance of in-service asphalt pavement at intermediate temperature using a large number of field cores in Jiangsu province, China. A semi-circular bending (SCB) test at 25 °C was conducted on field-cored samples covering three asphalt layers from 16 in-service road sections that represent a combination of influencing factors, including air void, mixture type, service age, cumulative number of equivalent single-axle loads (ESALs), and overload rate. The flexibility index (FI) and tensile strength were calculated from the experimental data as cracking performance evaluation indices. According to the analysis of variance results, at the top layer, ESALs and service age had a strong influence on cracking resistance. The decline rate of FI became slower with increasing ESALs. The most rapid decline in crack resistance with service age occurred on medium-traffic-level sections that served for over 14 years. At the middle layer, the overload rate replaced service age as a significant factor for FI. At the bottom layer, the air void was the only significant factor affecting the cracking resistance. In general, as the depth of layer increased, the effect of traffic load and service age decreased, whereas the effect of material properties increased. In addition, the FI and tensile strength were more sensitive to traffic load and air void, respectively. Full article

A new type of plastic and basalt fiber composite (PB) modifier, which is composed of waste plastic and basalt fiber using a specific process, was used for bus lanes to address severe high-temperature deformation diseases due to the heavy loads of buses. The dense gradations of asphalt mixture with a nominal maximum aggregate size of 13.2 mm (AC-13) and 19 mm (AC-20) were selected to fabricate asphalt mixtures. The impact of the modifier PB on the high-temperature rutting resistance, low-temperature crack resistance, and water damage resistance was investigated experimentally. The experimental results showed that adding the modifier PB could enhance the rutting resistance and water damage resistance of asphalt mixtures significantly while maintaining the low-temperature crack resistance. Then, PB-modified asphalt mixtures of AC-13 and AC-20 were employed into a typical pavement structure of a bus lane in Yangzhou city, China, and three types of designed pavement structures were proposed. On this basis, statics analyses of all of the designed structures were performed using the finite element method. The statics analyses revealed that, compared with the standard axle load, the actual over-loaded axle made the pavement structure of the bus lane suffer a 30% higher stress and vertical deformation, leading to accelerated rutting damage on the bus lanes. The addition of the modifier PB could make the pavement structure stronger and compensate for the negative effect caused by the heavy axle load. These findings can be used as a reference for the pavement design of urban bus lanes. Full article

Based on the knowledge of the dimensional and mass features of a forwarder, a model was developed to assess its mobility during timber forwarding uphill in a safe and eco-efficient way. The model is based on knowledge of the position of the forwarder’s centre of gravity, its declared payload and the length of the loaded timber, as well as the gradeability for uphill timber forwarding based on the traction characteristics of the vehicle. The model connects two research approaches, (1) vehicle–terrain approach (distribution of axle loads depending on the longitudinal terrain slope) and (2) wheel–soil approach (estimation of the traction characteristics of the forwarder based on the wheel numeric), concerning previous research: (i) underload on the front axle of the vehicle, (ii) overload on the rear axle of the vehicle, (iii) permissible tire load, (iv) minimal soil bearing capacity, (v) wheel slip. Simulation modelling for the assessment of the forwarders’ mobility range during timber forwarding uphill was conducted on an example of an eight-wheel Komatsu 875 forwarder, with a declared payload of 16,000 kg, equipped with 710/45-26.5 tires, for which the position of the centre of gravity was determined by the method of lifting the axle. The results of the distribution of the adhesion load on the front and rear axles of the forwarder indicated that, during timber forwarding of 16,000 kg and 4.82 m long hardwood logs on a terrain slope below 68%, there is no critical unloading on the front bogie axle, nor overloading on the rear bogie axle, i.e., wheel tire overload that could limit forwarder mobility. For the specified range of longitudinal terrain slope, a minimal cone index of 950 kPa for an exemplary forwarder is an environmental factor and was calculated based on the nominal ground pressure of the reference (heavier loaded) rear wheels of the vehicle. The forwarders’ mobility range was determined by the intersection curves of the gradeability (based on forwarders’ traction characteristics at wheel slip of 25% vs. cone index) and the curve of the minimal soil cone index. Full article

The aim of the study was to investigate the actual axle loads of vehicles used for the transport of sawmill by-products, resulting from the total weight of the transport set (GVW) at different times of the year and depending on the type of sets and transported assortment. Sawmill by-product loads were divided into groups: wood chips, sawdust, slabs and recycled wood. The research was carried out at the recipient of the sawmill by-products as well as at the producer. The GVW was determined on the basis of weighing the entire set on a stationary scale at the premises of the companies. The load on the individual axles of high tonnage truck units was measured using Model DINI ARGEO WWSD portable truck scales with a 3590M309 weighing terminal. Almost 230 transports were analyzed. It was shown that the average GVW is 39.25 t for transport sets with a load of 22.44 t of sawmill by-products with the usage of the semi-trailer capacity of 0.85. For all transport sets, the average load on the individual axles range from 6.72 t (axle 5 in a six-axle truck and trailer-TT) to 10.29 t for axle 2 in a truck and semi-trailer (TST), where the highest occurs on axle 2 of the truck (drive axle). The influence of the type of transport set (TST or TT) and the type of the assortments on the axle load is shown, and the existing correlations are at the level of 0.604–0.669 for axles 3–5 in the TST set. The static axle loads of the transport sets for the sawmill by-products and the distribution of the total weight of the set among the axles are different from those for roundwood transport. Full article

The variety of wood loads and their parameters (humidity, density, assortment) are often the cause of the increased total weight of the vehicle (GVW). With significant GVW exceeding, forest roads are exposed to high-tonnage vehicles, which results in vehicle axle loads above the accepted design parameters for the pavement. The purpose of this study was to investigate the real axle loads of round wood transport vehicles arising from the gross vehicle weight (GVW) of the transport set in different seasons of the year and depending on the type of transport set and the type of wood assortments. Measurements of axle loads for round wood truck transport sets were carried out on the sites of three large wood industry companies from the north of Poland, which process different types of wood. The load on the individual axles of the high tonnage truck units was measured using model DINI ARGEO WWSD portable truck scales with a 3590M309 weighing terminal with 0.01 t graduation. In total, measurements were taken for 904 round wood deliveries made by different transport sets: a truck and trailer set with 473 deliveries, including 344 deliveries by six-axle sets, a truck, and semi-trailer with 334 deliveries, where 193 were made by six-axle sets. The lowest axle load for all the sets occurred on axle one in the range of average values 7.07–7.86 t with a spread of results from 4.49 to 10.20 t. The highest average axle loads of 9.15–12.43 t was found on the axle for all the observed transport sets, where a maximum value of 14.52 t was also found. There were statistically significant differences in the values of the loads on individual axles depending on the type of truck set and type of wood assortment. Comparative analysis by the Kruskal–Wallis test of all axle load results depending on the vehicle types and number of axles, showed statistically significant differences. When analyzing the axle loads in five-axle sets with respect to the delivery date, statistically significant differences were found for all the axles. These differences occurred mainly for measurements performed in the summer and other seasons, the most visible of which were on the second and third axle. The loads of transported wood (assortments) also influenced the resulting axle loads, which was confirmed by statistical analysis. For most axles, there are differences in the axle loads for sets with MS (medium-size, industrial wood) deliveries and other assortments. Additionally, on axles 4–5, there are differences between Ls (large-size) deliveries and other deliveries (multiple mean rank test). In the case of TS transport sets, there is no big difference between the axle loads, only in the case of short assortment Ms where the second and third axles have higher average axle loads of just over 10 t. In the truck and trailer combinations (TT), the highest average axle loads are on the fourth and fifth axle in the range 8.5–12.0 t, with lower values for shorter 3.7 m and Ms grades. The distribution of the total gross vehicle weight of the set is, on average, 58–60% to the truck (three axles) and 40–42% to the trailer/semi-trailer (two axles) in five-axle sets and in six-axle sets, the truck and trailer/semi-trailer (three axles). Full article