Search Results (259)

Three-dimensional (3D) computational fluid dynamic (CFD) simulations have been performed to investigate the complex flow features and stripping of fluid materials from a cylindrical water drop at the late-stage in a Shock Liquid Drop Interaction (SLDI) process when the drop’s downstream end experiences compression after it is impacted by a supersonic shock wave ($Ma$ = 1.47). The drop trajectory/breakup has been simulated using a Lagrangian model and the unsteady Reynolds-averaged Navier–Stokes (URANS) approach has been employed for simulating the ambient airflow. The Kelvin–Helmholtz Rayleigh–Taylor (KHRT) breakup model has been used to capture the liquid drop fragmentation process and a coupled level-set volume of fluid (CLSVOF) method has been applied to investigate the topological transformations at the air/water interface. The predicted changes of the drop length/width/area with time have been compared against experimental measurements, and a very good agreement has been obtained. The complex flow features and the qualitative characteristics of the material stripping process in the compression phase, as well as disintegration and flattening of the drop are analyzed via comprehensive flow visualization. Characteristics of the drop distortion and fragmentation in the stripping breakup mode, and the development of turbulence at the later stage of the shock drop interaction process are also examined. Finally, this study investigated the effect of increasing $Ma$ on the breakup of a water drop by shear stripping. The results show that the shed fluid materials and micro-drops are spread over a narrower distribution as $Ma$ increases. It illustrates that the flattened area bounded by the downstream separation points experienced less compression, and the liquid sheet suffered a slower growth. Full article

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on the emission characteristics and source analysis of VOCs is important for controlling urban ozone pollution. In this study, hourly concentrations of 57 VOC species in four groups were obtained in April 2022, a period of high ozone pollution in Kunming, China. The ozone formation potential analysis showed that the accumulated reactive VOCs significantly contributed to the subsequent ozone formation, particularly aromatics (44.16%) and alkanes (32.46%). In addition, the ozone production rate in Kunming is mainly controlled by VOCs based on the results of the empirical kinetic modeling approach (K_NOx/K_VOCs = 0.25). The hybrid single-particle Lagrangian integrated trajectory model and polar coordinate diagram showed high VOC and ozone concentrations from the southwest outside the province (50.28%) and the south in local areas (12.78%). Six factors were obtained from the positive matrix factorization model: vehicle exhaust (31.80%), liquefied petroleum gas usage (24.16%), the petrochemical industry (17.81%), fuel evaporation (11.79%), coal burning (7.47%), and solvent usage (6.97%). These findings underscore that reducing anthropogenic VOC emissions and strengthening controls on the related sources could provide a scientifically robust strategy for mitigating ozone pollution in Kunming. Full article

Aviation is widely recognised to have global-scale climate impacts through the formation of ozone (O₃) in the upper troposphere and lower stratosphere (UTLS), driven by emissions of nitrogen oxides (NO_X). Ozone is known to be one of the most potent greenhouse gases formed from the interaction of aircraft emission plumes with atmospheric species. This paper follows up on previous research, where a Photochemical Trajectory Model was shown to be a robust measure of ozone formation along flight trajectories post-flight. We use a combination of a global Lagrangian chemistry-transport model and a box model to quantify the impacts of aircraft NO_X on UTLS ozone over a five-day timescale. This work expands on the spatial and temporal range, as well as the chemical accuracy reported previously, with a greater range of NO_X chemistry relevant chemical species. Based on these models, route optimisation has been investigated, through the use of network theory and algorithms. This is to show the potential inclusion of an understanding of climate-sensitive regions of the atmosphere on route planning can have on aviation’s impact on Earth’s Thermal Radiation balance with existing resources and technology. Optimised flight trajectories indicated reductions in O₃ formation per unit NO_X are in the range 1–40% depending on the spatial aspect of the flight. Temporally, local winter times and equatorial regions are generally found to have the most significant O₃ formation per unit NO_X; moreover, hotspots were found over the Pacific and Indian Ocean. Full article

This data descriptor presents the HF radar and drifter datasets, along with the methods used to process and apply them in a previously published study on the validation of surface current measurements in a region characterized by highly variable coastal dynamics. The data were collected in the framework of a large-scale Lagrangian experiment, which included extensive drifter deployment and the generation of virtual trajectories based on HF radar-derived flow fields. Both Eulerian and Lagrangian approaches were used to assess radar performance through correlation and RMSE metrics, with additional refinement achieved via Kriging interpolation. The validation results, published in Remote Sensing, demonstrated good agreement between HF radar and drifter observations, particularly when quality control parameters were optimized. The datasets and associated methodologies described here support ongoing efforts to enhance HF radar tuning strategies and improve surface current monitoring in complex marine environments. Full article

Multi-robot systems are significant in decision-making capabilities and applications, but avoiding collisions during movement remains a critical challenge. Existing decentralized obstacle avoidance strategies, while low in computational cost, often fail to ensure safety effectively. To address this issue, this paper leverages graph neural networks (GNNs) and deep reinforcement learning (DRL) to aggregate high-dimensional features as inputs for reinforcement learning (RL) to generate paths. Additionally, it introduces safety constraints through an artificial potential field (APF) to optimize these trajectories. Additionally, a constrained nonlinear optimization method further refines the APF-adjusted paths, resulting in the development of the GNN-RL-APF-Lagrangian algorithm. By combining APF and nonlinear optimization techniques, experimental results demonstrate that this method significantly enhances the safety and obstacle avoidance capabilities of multi-robot systems in complex environments. The proposed GNN-RL-APF-Lagrangian algorithm achieves a 96.43% success rate in sparse obstacle environments and 89.77% in dense obstacle scenarios, representing improvements of 59% and 60%, respectively, over baseline GNN-RL approaches. The method maintains scalability up to 30 robots while preserving distributed execution properties. Full article

This paper studies the safe trajectory tracking control of intelligent vehicles, which is still an open and challenging problem. A deep reinforcement learning algorithm based on augmented Lagrangian safety constraints is proposed to the lateral control of vehicle trajectory tracking. First, the tracking control of intelligent vehicles is described as a reinforcement learning process based on the Constrained Markov Decision Process (CMDP). The actor-critic neural network based reinforcement learning framework is established and the environment of reinforcement learning is designed to include the vehicle model, tracking model, road model and reward function. Secondly, the augmented Lagrangian Deep Deterministic Policy Gradient (DDPG) method is proposed for updating, in which a replay separation buffer method is used to solve the problem of sample correlation, and a neural network with the same structure is copied to solve the update divergence problem. Finally, a vehicle lateral control approach is obtained, whose effectiveness and advantages over existing results are verified through simulation results. Full article

This study utilized the FVCOM model to establish a hydrodynamic model for the waters from Haikou to Danzhou. Based on this framework, a numerical model for oil spill drift and diffusion was developed using the Lagrangian particle method, incorporating processes such as advection, diffusion, spreading, emulsification, dissolution, volatilization, and shoreline adsorption. Sea experiments involving drifters and dye were conducted to validate the oil spill model. The model was subsequently applied to analyze the impacts of tidal phases and wind fields on oil spill trajectories, predict affected areas, and assess risks to environmentally sensitive zones. The results demonstrate that the hydrodynamic model accurately reproduces the tidal current characteristics of the study area. Validation using drifter and dye experiments confirmed that the model’s predictive error remains within 20%, meeting operational forecasting standards. Potential sources of error include uncertainties in wind–wave–current interactions and discrepancies in windage coefficients between oil spills and drifters. Tidal currents and wind fields were identified as the dominant drivers of oil spill drift and diffusion. Under southerly wind conditions, the oil spill exhibited the largest spatial extent, covering 995.25 km² with a trajectory length of 226.92 km. A sensitivity analysis highlighted the Lingao Silverlip Pearl Oyster Marine Protected Area and Shatu Bay Beach as high-risk regions. The developed model provides critical technical support for oil spill emergency response under diverse environmental conditions, enabling proactive pathway forecasting and preventive measures to mitigate ecological damage. Full article

Titanium alloys are increasingly used in aeronautical applications, a sector that requires highly controlled materials. In particular, inclusion cleanliness is a necessary and mandatory condition for safe use in aeronautical components. During the production and processing of titanium alloys, inclusions are likely to appear, in particular high-density inclusions (HDIs) originate from refractory metals such as molybdenum or tungsten carbide. Plasma Arc Melting–Cold Hearth Remelting (PAMCHR) is one of the most effective recycling and refining process for titanium alloys. Firstly, this work reports the thermal modeling of the melting of raw materials in the melting crucible and a complete 3D numerical simulation of the thermo-hydrodynamic behavior of the metal flow in the PAMCHR furnace, based on the software Ansys-Fluent CFD V21.1. Simulation results are presented for a 100 kg/h melting test performed in a pilot furnace with a comparison between the measured and calculated pool profiles and residence time distributions that show satisfactory agreements. Additionally, a Lagrangian calculation of particle trajectories in the liquid metal pool is also performed and insemination of HDIs in the pilot furnace has been tested. Both numerical and experimental tests demonstrate the inclusion removal in the melting crucible. Full article

When a mobile robot on an overhead line carries out operations, the effects of the elastic deformation and vibration of the flexible overhead line on motion performance cannot be ignored. This study proposes a method for active compensation of the robot’s trajectory, based on the force–deformation characteristics of the overhead line. Overhead line mobile robot systems show a complex nonlinear coupled vibration problem. To simplify the flexible environment, it is modeled as a single-degree-of-freedom spring–damped system. A rigid–flexible coupled dynamics model is established using the sub-bar method and the Lagrangian method. A numerical simulation is used to compare and analyze the end trajectories of mobile robots using generalized coordinates when the overhead line is rigid and flexible, respectively, revealing the coupling mechanism between the flexible overhead line and the robot. Based on the force–deformation characteristics of the overhead line, an active robot trajectory compensation method is proposed. The experimental results show that the established rigid–flexible coupling dynamics model describes the dynamic characteristics of an overhead line mobile robot, and the active robot trajectory compensation method has certain feasibility. The proposed method provides a reference basis for the control of overhead line mobile robots and has some applicability in addressing motion compensation issues in flexible environments. Full article

Traditional elastic correction methods fail to address the significant aeroelastic interactions arising from unsteady flow fields and structural deformations during aggressive maneuvers. To resolve this, a numerical method is developed by solving unsteady aerodynamic equations coupled with a rigid–flexible dynamics equations derived from Lagrangian mechanics in quasi-coordinates. Validation via a flexible pendulum test and AGARD445.6 wing flutter simulations demonstrates excellent agreement with experimental data, confirming the method’s accuracy. Application to a slender air-to-air missile reveals that reducing structural stiffness can destabilize the aircraft, transitioning it from stable to unstable states during forced pitching motions. Studies on longitudinal flight under preset rudder deflection control indicate that the aeroelastic effect increases both the amplitude and period of pitch angles, ultimately resulting in larger equilibrium angles compared to a rigid-body model. The free-flight simulations highlight trajectory deviations due to deformation-induced aerodynamic forces, which emphasizes the necessity of multidisciplinary coupling analysis. The numerical results show that the proposed CFD/CSD-based coupling methodology offers a robust aeroelastic effect analysis tool for flexible flight vehicles during aggressive maneuvers. Full article

The validation of HF radar systems remains an area with significant scope for advancement, particularly in terms of linking data quality with system operational parameters, fully utilizing the potential of redundant data (e.g., overlapping radial measurements), and accurately capturing the spatiotemporal variability observed by independent devices, such as drifters. In this study, we conducted a large-scale Lagrangian measurement campaign in the Tuscan Archipelago, aimed at validating surface current data from the HF radar network. This radar network, a recent addition to the area, monitors an oceanographic region critical to Mediterranean dynamics. The validation was executed using different approaches: a Eulerian method, comparing the radial velocities measured by radar with drifter-derived velocities along radial directions; a Lagrangian method, contrasting the observed drifter trajectories with the synthetic virtual trajectories generated from radar-based flow fields; and radar-to-radar comparisons with the concurrent utilization of two radars in same point. Through fine-tuning of the quality control parameters and an analysis of the impact of different thresholds of such parameters, we assessed the radar’s ability to capture dynamic processes, identifying both strengths and limitations. Our results not only confirm the utility of HF radar in coastal monitoring but also provide a basis for improving calibration strategies, ultimately supporting more accurate, high-resolution radar observations in complex marine environments. Full article

Analyzing the transmission dynamics of airborne disease spores is crucial for advancing early warning and control strategies for crop diseases. This study introduces a novel approach utilizing the HYSPLIT-5 model to investigate the spore transmission patterns and pathways of airborne crop diseases. By employing the Lagrangian particle trajectory method of HYSPLIT-5 in conjunction with MeteInfoMap 3.5, the spatiotemporal frequency of cucumber downy mildew spore trajectories over extended periods was examined. The results indicate that the transmission trajectory of cucumber downy mildew spores is heavily influenced by atmospheric circulation, with spores spreading along air currents to surrounding areas. These trajectories frequently intersect, resulting in a broad transmission range, and the observed transmission patterns exhibit a degree of universality. Which provided a basis for the subsequent study of a large-scale prediction model of cucumber downy mildew. Full article

For the problem of large joint angular velocity and high input in the trajectory planning and control of robots, an explicit-time trajectory tracking for a state-constraint continuum free-floating space robot with smooth joint-path and low input is proposed. Employing the piecewise constant curvature (PCC) assumption as the modeling foundation for the continuum space robot and utilizing modified Rodriguez parameters (MRPs) to describe attitude errors, a pose error feedback kinematic model for the continuum space robot is established. Based on the Lagrangian method, a dynamic model for the continuum space robot is developed. Explicit time theory and pose feedback methods are employed for the trajectory planning of the continuum space robot. Using explicit time theory and sliding mode control, tracking control for the planned joint trajectory is conducted. The Lyapunov theory is utilized to demonstrate the convergence of the system tracking error within the explicit time. Finally, the combination of trajectory planning and tracking control enhances the control performance of the continuum space robot. Simulation results validate the effectiveness of the proposed methods. Full article

This paper investigates the dynamic modeling and robust control of a Mecanum-wheeled vehicle (MWV) under load disturbances and measurement noise. The system is modeled as a cascaded state-space representation, where the motor transfer function (PWM input → torque output) and the vehicle transfer function (torque input → vehicle speed output) are combined. The PWM-induced motor delay is linearized, and the complete dynamic model is derived using Lagrangian mechanics, addressing the limitations of conventional models that are incomplete and unable to decouple control signals from disturbance signals. For the developed model, a robust stability controller is designed by integrating Internal Model Control (IMC) with a Disturbance Observer (DOB), enhancing real-time disturbance rejection. Open-loop experiments validate the model’s accuracy, showing a Dynamic Time Warping (DTW) error of 0.2662 m, significantly lower than the 0.3198 m observed in traditional models. In closed-loop simulations, under load disturbances ($T_L=0.1$ to $T_L=-0.7$) and Gaussian noise (power: 0.0001–0.00005), the proposed IMC + DOB controller achieves 97.6% faster stabilization than IMC and 98.3% faster than PID, demonstrating superior convergence speed, robustness, and disturbance rejection. This study provides a novel control strategy that effectively handles non-square system dynamics while mitigating external disturbances in real time. The proposed framework enhances trajectory tracking accuracy and stability, with potential applications in autonomous robotics and vehicular systems. Full article

As operational scenarios become more complex and task demands intensify, the requirements for the intelligence and automation of manipulators in industry are increasing. This work investigates the challenge of posture tracking control for hydraulic flexible manipulators by proposing a discrete-time integral terminal sliding mode predictive control (DITSMPC) method. First, the proposed method develops a second-order dynamic model of the manipulator using the Lagrangian dynamic strategy. Second, a discrete-time sliding mode control (SMC) law based on an adaptive switching term is designed to achieve high-precision tracking control of the system. Finally, to weaken the influence of SMC buffeting on the manipulator system, the predictive time domain function is integrated into the proposed SMC law, and the delay estimation of the unknown term in the manipulator system is carried out. The DITSMPC scheme is derived and its convergence is proven. Simulation experiments comparing the DITSMPC scheme with the classical discrete-time SMC method demonstrate that the proposed scheme results in smooth torque changes in each joint of the manipulator, with the integral of torque variations being $5.22\times {10}^3$. The trajectory tracking errors for each joint remain within ±0.0025 rad, all of which are smaller than those of the classical scheme. Full article