Search Results (25)

In periodic technical inspections (PTIs), evaluating the braking efficiency of light passenger vehicles at their Maximum Authorized Mass (MAM) presents a practical challenge, as bringing laden vehicles to inspection is often unfeasible due to logistical and infrastructure limitations. The fBrake method is proposed to overcome this issue by estimating braking efficiency at MAM based on measurements taken from vehicles in more accessible loading conditions. In this study, the fBrake method is validated by demonstrating the equivalence of its efficiency estimates extrapolated from two distinct configurations: an unladen state near the curb weight and a partially laden condition closer to MAM. Following the UNE 26110 standard (Road vehicles. Criteria for the assessment of the equivalence of braking efficiency test methods in relation to the methods defined in ISO 21069), roller brake tester measurements were used to obtain force data under both conditions. The analysis showed that the extrapolated efficiencies agree within combined uncertainty limits, with normalized errors below 1 in all segments tested. Confidence intervals were reduced by up to 74% after electronics update. These results confirm the reliability of the fBrake method for M1 and N1 vehicles and support its adoption as an equivalent procedure in compliance with UNE 26110, particularly when fully laden testing is impractical. Full article

Nitrogen is a vital nutrient and plays a pivotal role in maintaining ecosystem equilibrium. Owing to human activities, particularly industrial production, vehicle emissions, fossil fuel combustion, and the improper use of chemical fertilizers, nitrogen pollution has emerged as a pressing global environmental issue. It exacerbates air pollution, water eutrophication, and soil acidification, all of which pose profound risks to both ecosystems and human health. This review conducts a holistic analysis of nitrogen sources and the current status of nitrogen pollution, with a particular focus on the treatment of nitrogen-laden wastewater. It assesses various nitrogen pollution remediation technologies, including biological and physicochemical methods. In recent years, the application of novel metal–phenolic networks (MPNs) has garnered considerable scholarly attention. As innovative materials, it has been demonstrated that MPNs have great potential in nitrogen removal. For example, studies have demonstrated that iron–tanninate has the capacity to remove over 95% of ammonium nitrogen. Despite the progress made with current remediation methods, each approach has inherent limitations, such as long treatment durations, high energy demands, and poor selectivity for diverse nitrogen pollutants. Therefore, sustained research endeavors and technological innovation are indispensable for advancing nitrogen pollution control technologies. It is against this backdrop that we conducted this review. This study summarizes and analyzes the current status of nitrogen pollution and nitrogen removal technologies, and provides an overview of novel nitrogen removal MPNs. MPNs are promising and innovative materials with great potential, although current research is still at the laboratory stage and is ongoing. Full article

Formation flying of multiple unmanned aerial vehicles (UAVs) has attracted much attention for its versatility in cooperative tasks. In this paper, a distributed formation planning method is proposed for UAVs. First, we design a path searching algorithm, swarm-A*, which can enhance the cohesion of a swarm, i.e., preventing the disintegration of the swarm when it encounters an obstacle. Then, after waypoint reallocation, a formation trajectory optimization framework is formulated. Smooth formation trajectories for UAVs to travel safely in obstacle-laden environments can be obtained by solving the optimization problem. Next, a tracking controller based on sliding mode control is designed, ensuring that the UAVs follow the planned formation trajectories under dynamic constraints. Finally, numerical simulations and experiments are conducted to validate the effectiveness of the proposed method. Full article

Recently, there has been a growing interest in understanding how respiratory particles spread within passenger cars, especially in light of ongoing challenges posed by infectious diseases. This study experimentally investigates dispersion patterns of respiratory airborne particles (<1 µm) within these confined spaces. The main objective is to introduce a manikin-based method for studying particle dispersion and assessing in-cabin air quality. To achieve this, a respiratory manikin as a particle source has been developed and tested under various use-cases, including variations in source emission (breathing vs. speaking), the HVAC ventilation mode (fresh and recirculation), and the blower level of the HVAC system (low and high). The findings reveal that for an infection source on the first row of the vehicle when cabin airflow originates from the front panel, the seat directly behind the particle source is associated with the highest particle exposure, while the seat adjacent to the source offers the lowest exposure. Among the tested configurations, the recirculation mode with an active HEPA filter and high blower level shows the lowest particle concentration at recipients’ breath levels during both breathing and speaking. These findings can be used to enhance the design of passenger cars to reduce the transmission of potentially pathogen-laden particles. Full article

Background/Objectives: Glioblastoma multiforme (GBM) is the most common high-grade primary brain cancer in adults. Despite efforts to advance treatment, GBM remains treatment resistant and inevitably progresses after first-line therapy. Induced neural stem cell (iNSC) therapy is a promising, personalized cell therapy approach that has been explored to circumvent challenges associated with the current GBM treatment. Methods: Herein, we developed a chitosan-based (CS) injectable, biodegradable, in situ forming thermo-responsive hydrogel as a cell delivery vehicle for the treatment of GBM. Tumoricidal neural stem cells were encapsulated in the injectable CS hydrogel as stem cell therapy for treatment of post-surgical GBM. In this report, we investigated the safety of the injectable CS hydrogel in an immune-competent mouse model. Furthermore, we evaluated the persistence and efficacy of iNSC-laden CS hydrogels in a post-surgical GBM mouse model. Results: The injectable CS hydrogel was well tolerated in mice with no signs of chronic local inflammation. Induced neural stem cells (iNSCs) persisted in the CS hydrogels for over 196 days in comparison to 21 days for iNSCs (cell injection) only. GBM recurrence was significantly slower in mice treated with iNSC-laden CS hydrogels with a 50% increase in overall median survival in comparison to iNSCs (cell injection) only. Conclusions: Collectively, we demonstrated the ability to encapsulate, retain, and deliver iNSCs in an injectable CS hydrogel that is well tolerated with better survival rates than iNSCs alone. Full article

The aim of this work was to perform a simulation analysis of the dynamics of a freight wagon with a variant vibration damping: dry friction and viscous damping. The following mathematical models of the damping characteristics are presented: the Maxwell model and the Kolsch model. The differences among the types of damping were first analyzed based on the dynamic responses of the 1 DOF model. Simulation studies were then carried out in a VI-Rail environment with the use of S-curved track models comprising short straight sections connecting the curves. The track models differed in the values of curve radii, cant, and length, which made it possible to run at different speeds. The multibody model of the vehicle represents a typical two-axle freight wagon. The dynamics of the wagon model were investigated for two states: empty and laden. Standard kinematic and dynamic values were compared in order to investigate if the nature of the damping has a significant impact on the dynamic properties of a freight wagon. The analysis of the simulation study showed that replacing dry friction damping with the viscous one can generally reduce forces acting on the wheel–rail contact, which, in turn, can be related to improving the running behavior of wagons while reducing the negative impact on the track. Full article

Unmanned Surface Vehicles (USVs) operating in complex traffic conditions in island reef waters often require different types of algorithms. Therefore, selecting a dynamic path-planning algorithm with strong adaptability has become a new challenge. This paper proposes a dynamic adaptive path planning algorithm for USVs, incorporating an improved Dynamic Window Approach (DWA) with fuzzy logic and the International Regulations for Preventing Collisions at Sea (COLREGS). The algorithm is designed by integrating three key aspects: evaluation function, fuzzy control, and COLREGS. First, to enable USVs to approach the target point more safely and quickly during navigation, an additional target point attraction sub-function is introduced, extending the original evaluation function. Furthermore, to ensure robust dynamic path planning for USVs across various water environments, such as narrow channels, reef-laden waters, and open seas, fuzzy logic is integrated with the improved DWA algorithm. Since USVs must comply with COLREGS during navigation, the algorithm incorporates these regulations, enhancing the DWA algorithm with fuzzy logic to ensure compliance. Finally, simulation experiments validate the proposed algorithm, demonstrating that the planned paths are safer and more stable, ensuring the safe navigation of USVs in compliance with COLREGS. Full article

This study introduces fBrake, a novel simulation method now designed for use in periodic technical inspections of M₁ and N₁ vehicle categories, addressing challenges posed by Directive 2014/45/EU. The directive mandates that braking efficiency must be measured relative to the vehicle’s maximum mass, which often results in underperformance during inspections due to vehicles typically being unladen. This discrepancy arises because the maximum braking forces are proportional to the vertical load on the wheels, causing empty vehicles to lock their wheels prematurely compared to laden ones. fBrake simulates the braking forces of unladen vehicles to reflect a laden state by employing an optimal brake-force distribution curve that aligns with the vehicle’s inherent braking behavior, whether through proportioning valves or through electronic brake distribution systems in anti-lock-braking-system-equipped vehicles. Our methodology, previously applied to heavy vehicles, involved extensive experimentation with a roller brake tester, comparing the actual braking performances of dozens of vehicles to those of their simulated counterparts using fBrake. The results demonstrate that fBrake reliably replicates the braking efficiency of laden vehicles, validating its use as an accurate and effective tool for braking system assessments in periodic inspections, irrespective of the vehicle’s load condition during the test. This approach ensures compliance with regulatory requirements while enhancing the reliability and safety of vehicle inspections. Full article

Energy management strategies typically employ reinforcement learning algorithms in a static state. However, during vehicle operation, the environment is dynamic and laden with uncertainties and unforeseen disruptions. This study proposes an adaptive learning strategy in dynamic environments that adapts actions to changing circumstances, drawing on past experience to enhance future real-world learning. We developed a memory library for dynamic environments, employed Dirichlet clustering for driving conditions, and incorporated the expectation maximization algorithm for timely model updating to fully absorb prior knowledge. The agent swiftly adapts to the dynamic environment and converges quickly, improving hybrid electric vehicle fuel economy by 5–10% while maintaining the final state of charge (SOC). Our algorithm’s engine operating point fluctuates less, and the working state is compact compared with Deep Q-Network (DQN) and Deterministic Policy Gradient (DDPG) algorithms. This study provides a solution for vehicle agents in dynamic environmental conditions, enabling them to logically evaluate past experiences and carry out situationally appropriate actions. Full article

This paper presents investigations of rail vehicle bogies of the Y25 type. The Y25 bogie family is one of the most commonly used freight car bogie designs. In addition to several significant advantages characterising this design, several disadvantages have also been observed since the beginning of more than fifty years of its operation in several types of cargo vehicles. One of these defects observed in real systems is its “unsatisfactory running stability”, particularly for long straight tracks. This paper used the commercial engineering software VI-Rail (2010.13.0) to create a model of a gondola car (type 412W Eaos) with two Y25 bogies. The car model was tested in empty and loaded (maximum permissible load) modes. Its motion along straight and curved tracks with different radii values was analysed. The vehicle velocity was changed from a few m/s to the maximum values for which stable solutions of the model existed. For each route, the nonlinear critical velocity was determined, defining the maximum operating velocity of the modelled car. The model solutions were recorded, while just one was selected to present the results—the first wheelset’s lateral displacement y_lw. Conjecture about its “imperfect running quality” on curved tracks was confirmed. The possible appearance of self-exciting wheelset vibrations in the modelled car’s operating velocity range in a laden state was also observed. The research results on the impact of changes in the bogie suspension parameters on the vehicle model’s stability are presented. The crucial parameter in the bogie suspension was indicated. Reducing its value by several percent about the nominal value increases the critical velocity of the car to values higher than the maximum operating velocity of the modelled vehicle. Full article

In the Inner Mongolia region, sand and dust storms are prevalent throughout the year, with sand erosion having a particularly significant impact on the performance of wind turbine blades. To enhance the performance stability of wind turbines and reduce operation and maintenance costs, this study delves into the specific impact of sand-laden wind erosion on the aerodynamic performance of scaled-down wooden wind turbine blades. The experiment conducts vehicle-mounted tests on scaled models of 1.5 MW wind turbine blades that have been eroded by wind-sand flows from different zones, analyzing the changes in aerodynamic performance of wind turbines caused by the erosion. The results indicate that with an increase in the angle of installation, both the overall power output and the wind energy utilization coefficient of the wind turbines show a declining trend. The power outputs of both the partially eroded group and the fully eroded group are unable to reach the rated power level of 100 W. Compared to the uneroded group, the leading-edge eroded group demonstrated higher power output and wind energy utilization coefficients across most wind speed ranges. This finding verifies the possibility that the drag-reducing effect caused by pits from leading-edge erosion has a positive impact on the aerodynamic performance of the blades. It also provides a new research perspective and strong evidence for the study of erosion effects on wind turbine blades and the optimization of their aerodynamic performance. Full article

The use of affine maneuver control to maintain the desired configuration of unmanned aerial vehicle (UAV) swarms has been widely practiced. Nevertheless, the lack of capability to interact with obstacles and navigate autonomously could potentially limit its extension. To address this problem, we present an innovative formation flight system featuring a virtual leader that seamlessly integrates global control and local control, effectively addressing the limitations of existing methods that rely on fixed configuration changes to accommodate real-world constraints. To enhance the elasticity of an algorithm for configuration change in an obstacle-laden environment, this paper introduces a second-order differentiable virtual force-based metric for planning local trajectories. The virtual field comprises several artificial potential field (APF) forces that adaptively adjust the formation compared to the existing following control. Then, a distributed and decoupled trajectory optimization framework that considers obstacle avoidance and dynamic feasibility is designed. This novel multi-agent agreement strategy can efficiently coordinate the global planning and local trajectory optimizations of the formation compared to a single method. Finally, an affine-based maneuver approach is employed to validate an optimal formation control law for ensuring closed-loop system stability. The simulation results demonstrate that the proposed scheme improves track accuracy by 32.92% compared to the traditional method, while also preserving formation and avoiding obstacles simultaneously. Full article

The development of intelligent task allocation and path planning algorithms for unmanned surface vehicles (USVs) is gaining significant interest, particularly in supporting complex ocean operations. This paper proposes an intelligent hybrid algorithm that combines task allocation and path planning to improve mission efficiency. The algorithm introduces a novel approach based on a self-attention mechanism (SAM) for intelligent task allocation. The key contribution lies in the integration of an adaptive distance field, created using the locking sweeping method (LSM), into the SAM. This integration enables the algorithm to determine the minimum practical sailing distance in obstacle-filled environments. The algorithm efficiently generates task execution sequences in cluttered maritime environments with numerous obstacles. By incorporating a safety parameter, the enhanced SAM algorithm adapts the dimensional influence of obstacles and generates paths that ensure the safety of the USV. The algorithms have been thoroughly evaluated and validated through extensive computer-based simulations, demonstrating their effectiveness in both simulated and practical maritime environments. The results of the simulations verify the algorithm’s capability to optimize task allocation and path planning, leading to improved performance in complex and obstacle-laden scenarios. Full article

The realistic simulation of the dynamic responses of a moving articulated vehicle has attracted considerable attention in various disciplines, with the identification of the vehicle model being the prerequisite. To this end, a double-sensor hump calibration method (DHCM) was developed to identify both unladen and laden vehicle models, consisting of a sensor layout optimization step and a system identification step. The first step was to optimize the number and position of sensors via parameter sensitivity analysis; the second was to inversely identify the vehicle system based on sensor responses. For comparison, the DHCM and the existing single-sensor hump calibration method (SHCM) were used to calibrate a small-sized vehicle model and a multi-axle articulated vehicle model. Vertical accelerations of the vehicle models were then simulated and characterized by power spectral densities (PSDs). Validation against experimental measurements indicated that the PSDs of the models identified with the DHCM matched the measured PSDs better than those of the SHCM, i.e., the DHCM-identified model accurately simulated the dynamic response of an articulated vehicle with relative errors below 16% in the low-frequency range. Therefore, the DHCM could identify models of small-sized vehicles and multi-axle articulated vehicles, while the SHCM was only suitable for the former. Full article

Osteoarthritis (OA) is the most common form of joint disease affecting articular cartilage and peri-articular tissues. Traditional treatments are insufficient, as they are aimed at mitigating symptoms. Multipotent Stromal Cell (MSC) therapy has been proposed as a treatment capable of both preventing cartilage destruction and treating symptoms. While many studies have investigated MSCs for treating OA, therapeutic success is often inconsistent due to low MSC viability and retention in the joint. To address this, biomaterial-assisted delivery is of interest, particularly hydrogel microspheres, which can be easily injected into the joint. Microspheres composed of hyaluronic acid (HA) were created as MSC delivery vehicles. Microrheology measurements indicated that the microspheres had structural integrity alongside sufficient permeability. Additionally, encapsulated MSC viability was found to be above 70% over one week in culture. Gene expression analysis of MSC-identifying markers showed no change in CD29 levels, increased expression of CD44, and decreased expression of CD90 after one week of encapsulation. Analysis of chondrogenic markers showed increased expressions of aggrecan (ACAN) and SRY-box transcription factor 9 (SOX9), and decreased expression of osteogenic markers, runt-related transcription factor 2 (RUNX2), and alkaline phosphatase (ALPL). In vivo analysis revealed that HA microspheres remained in the joint for up to 6 weeks. Rats that had undergone destabilization of the medial meniscus and had overt OA were treated with empty HA microspheres, MSC-laden microspheres, MSCs alone, or a control vehicle. Pain measurements taken before and after the treatment illustrated temporarily decreased pain in groups treated with encapsulated cells. Finally, the histopathological scoring of each group illustrated significantly less OA damage in those treated with encapsulated cells compared to controls. Overall, these studies demonstrate the potential of using HA-based hydrogel microspheres to enhance the therapeutic efficacy of MSCs in treating OA. Full article