Search Results (31,603)

This paper investigates the cooperative formation control problem in unmanned surface vehicles (USVs) with prescribed performance constraints under complex marine conditions including external disturbances, model uncertainties, actuator faults, and input saturation. A novel fault-tolerant control (FTC) algorithm is developed by integrating cooperative learning neural networks (NNs), distributed disturbance observers, and the backstepping technique. Specifically, the learning NNs adaptively approximate system uncertainties, and the learned weight information is shared among vehicles to enhance cooperative cognition. Additionally, an auxiliary dynamic system and an actuator configuration matrix are designed to compensate for input saturation and propeller failures. Theoretical analysis based on the Lyapunov method proves that all signals in the closed-loop system are bounded, and the formation tracking errors strictly remain within the predefined transient and steady-state performance bounds. Finally, simulation experiments involving a group of four USVs validate the proposed algorithm. The results demonstrate that the USVs can rapidly converge to and maintain the desired quadrilateral formation shape despite time-varying disturbances and actuator efficiency loss. Furthermore, comparative simulation results indicate that the proposed cooperative learning FTC scheme significantly reduces velocity tracking error oscillations compared to traditional non-learning methods, explicitly verifying its superior robustness and fault-tolerant capabilities. Full article

Motor vehicle exhaust in urban tunnels can cause nitric oxide (NO) to accumulate, severely degrading air quality both inside the tunnel and in the surrounding environment. Photocatalytic technology is an efficient, secondary-pollution-free approach with clear potential for treating tunnel exhaust; however, parametric analyses for practical tunnel engineering applications remain limited. Using computational fluid dynamics (CFD), this study developed a numerical model to simulate photocatalytic NO degradation in a congested tunnel and examined how the surface reaction rate, coating extent, and longitudinal coated section affect NO reduction performance. The results show that NO reduction efficiency increased with the surface reaction rate; however, once the surface reaction rate constant exceeded 2.11 × 10⁻⁴ m/s, further gains diminished and the efficiency approached a plateau due to mass-transfer limitations. With respect to the coating extent, full four-wall coating (sidewalls, ceiling, and road surface) provided the best performance, followed by three-wall coating (excluding the ceiling). Moreover, because the road surface lies in a region of high pollutant concentration and low air velocity, coating on the road surface achieved a markedly stronger reduction effect than coating on the sidewalls or the ceiling. In the simulated 500 m tunnel, the downstream coated section achieved a markedly higher NO reduction efficiency in the ambient environment outside the tunnel (5.9%) than the upstream coated section (1.0%), approaching that of the full-length (500 m) coated section (6.6%). Therefore, in practical engineering applications, priority should be given to coating strategies targeting the downstream section and the road surface in order to balance NO reduction performance and economic cost. Such a strategy is beneficial not only for improving tunnel air quality, but also for promoting sustainable pavement and tunnel-surface engineering by reducing unnecessary coating area and enabling a more resource-efficient and cost-effective use of photocatalytic materials. These findings provide theoretical and methodological support for the sustainable design and application of photocatalytic coating systems in urban tunnels. Full article

The physical characteristics of a heated non-Newtonian Eyring–Powell fluid in a conduit with sinusoidally moving ciliated walls are highlighted in this analytical study. The impact of mass transmission is considered in this model. The dimensional form of the governing equations is simplified using the long-wavelength estimation and suitable transformations to produce a set of dimensionless partial differential equations with pertinent boundary conditions. To solve it, the perturbation technique is utilized applying polynomial solutions. The solutions of temperature, concentrations, and velocity profiles are obtained, and then are further analyzed through graphical results. An accurate mathematical solution for the pressure gradient is achieved by integrating the velocity profile over the elliptic cross-section. The non-Newtonian Eyring–Powell fluid flows quicker through this vertical ciliated elliptic duct than the Newtonian fluid. Moreover, the cilia elliptic movement eccentricity and the wave number for metachronal wave have a dual effect on the velocity profile. Increasing the dimensionless flow rate and occlusion leads to an increase in closed contour size, as seen in the streamline description. Full article

Ice adhesion on exposed structures remains a major operational challenge, motivating the search for passive, material-based anti-icing strategies. Molecular dynamics offers a controlled way to investigate ice–surface interactions beyond the limits of experimental setups. In this work, we develop a simulation framework to model the impact of solid hexagonal ice droplets on metallic substrates. Ice impacts are simulated across a range of velocities (10–120 m/s), temperatures (120–250 K), and face-centred cubic surface materials (gold, copper, silver, aluminum, and nickel). Using LAMMPS, mW water force-field, EAM/Alloy metal potentials, and Lennard-Jones water–surface interactions, we quantify phase evolution through angular order parameter and quasi-liquid layer measurements, complemented by the CHILL+ algorithm in OVITO. By isolating all external factors, we show that melting increases with velocity and temperature and correlates with substrate properties: metals with high thermal diffusivity and low Young’s modulus tend to decrease post-collision ice melting. The ratio of the former to the latter, a derived index of merit Υ, significantly correlates with melting percentage and identifies silver as the most effective anti-ice material examined. Statistical analyses strongly suggest that these surface properties influence interfacial melting, supporting the use of this modelling framework for screening and designing anti-icing materials. Full article

This paper studies the dynamics of a low-density gas directly injected onto a flat wall, focusing on the influence of different pressure ratios (PRs) and plate position. Due to safety reasons, Helium (He) was employed as substitute to reproduce the mixing characteristics of hydrogen. A Nd:YAG laser has been used to generate the luminous background in the constant volume chamber (CVC) and vegetable oil particles as trackers to identify the induced flow-field. Two configurations were investigated: the first, with a flat wall perpendicularly positioned at an axial distance of 10 mm from the injector tip, and the second with the same plate at 30 mm downstream of the injector, inclined at 30°. The pressure of injection was swept from 20 to 50 bar, while the backpressure inside the CVC ranged from 2 to 6 bar to enable the reproduction of five different values of PRs: 3, 4, 7, 10 and 17. The comparison of the results in the two configurations has highlighted the role of the plate at short distance in decelerating the jet speed (230 m/s to 160 m/s) while improving the vorticity intensity (+10%). In addition, a stagnation region was observed to form on the flat wall, downstream of the injector axis for 10 mm configuration. In this area the velocity ranged from 50% to 60% compared to the average jet speed. This phenomenon was noted to be less pronounced with the 30 mm, 30° configuration that led to a more contained speed reduction to 150–160%. Full article

Thermal management is critical for maintaining the safety and performance of lithium-ion batteries. Phase change materials (PCMs) have been widely studied as passive cooling media due to their high latent heat capacity, but major technical challenges remain due to their relatively low thermal conductivity and nanoparticle sedimentation in composite systems. In this work, a composite phase change material (PCM) consisting of paraffin wax, a microencapsulated phase change material (MicroPCM 28D), and nano carbon black is developed to enhance thermal stability and suppress particle sedimentation through increased viscosity of the PCM matrix. Five capsule geometries fabricated by fused filament fabrication (FFF) 3D printing are experimentally investigated under airflow velocities ranging from 0 to 10 m s⁻¹. Wind tunnel experiments with infrared thermography are used to evaluate the thermal response of the PCM capsules. The results show that airflow velocity and capsule geometry strongly influence heat dissipation behavior. Compared with conventional wax composites, the MicroPCM 28D composite capsules reduce peak temperature by approximately 2–4 °C under airflow velocities of 0–10 m/s. These findings provide insights into geometry-regulated convection and stable composite PCM design for lithium-ion battery thermal management systems. Full article

Purpose: The primary aim of the present study was to examine the extent to which participation in organized youth basketball training contributes to physical activity across intensity zones during training sessions in relation to biological maturation status. Methods: Participants were classified into three maturity groups based on predicted age at peak height velocity (PHV): −2.5 to −1.5, −1.5 to −0.5, and ≥−0.5 to 0.83 years from PHV. Data from two training sessions per participant were averaged to obtain representative individual values. One-way analyses of variance (ANOVAs) were used to examine differences in anthropometric, physical performance, and field performance variables between PHV groups. Physical activity patterns were analyzed using two-way mixed-design ANOVAs with PHV stage as the between-subject factor and intensity zone (MET- and HRR-based) as the within-subject factor. Results: Across all maturity groups, approximately 10–17% of total training time was spent in light-intensity activity, while the majority of time was accumulated in moderate-to-vigorous intensity zones (approximately 35–50%, depending on the classification method). Significant maturity-related differences were observed in anthropometric variables and physical performance measures, with more mature players demonstrating superior sprint performance, jumping ability, and grip strength. Field performance indicators also differed between PHV groups, with more mature athletes exhibiting higher external and internal training loads. In contrast, no significant interactions or main effects of PHV stage were observed for physical activity intensity distribution. Conclusions: Organized basketball training contributes substantially to moderate-to-vigorous physical activity accumulated during training sessions. However, these findings reflect training-specific activity and should not be interpreted as representing total daily physical activity. No differences in activity intensity distribution were observed between maturation groups, although this finding should be interpreted with caution, given methodological limitations. These results highlight the need to consider biological maturation when designing youth training programs. Full article

With changes in the global energy structure, ammonia has emerged as a favorable hydrogen storage medium due to its excellent properties. This work details the synthesis of a barium-doped cobalt–iron alloy catalyst via subsequent heat treatment. This alloy efficiently catalyzes the decomposition of ammonia into hydrogen. The results showed that using characterization methods such as TEM and XRD indicated that adding Ba to this system could regulate the microstructure of the Co-Fe alloy. After calcination, the barium promoted a reduction in the particle size of Co-Fe nanoparticles, enabling their uniform dispersion on the surface and a more uniform dispersion and improving the accessibility of the exposed surface. The optimized catalyst (0.05Ba-0.25CoFe/CeO₂) achieved an ammonia conversion of 93.2% at 550 °C under a gas hourly space velocity of 30,000 mL·g_cat⁻¹·h⁻¹. Mechanistic analysis based on XPS and CO₂-TPD results indicated that the barium optimized the electronic structure and alkaline sites of Co-Fe, promoted the desorption of nitrogen, and thereby accelerated the reaction kinetics of ammonia decomposition. This research provides a strategic method and theoretical basis for designing high-performance non-precious metal catalysts for ammonia decomposition. Full article

Two-phase displacement between cement slurry and drilling fluid in wellbore systems is inherently nonlinear, interface-dominated, and strongly affected by geometric confinement, posing substantial challenges to efficient and stable numerical simulation. Conventional CFD approaches rely on mesh discretization and explicit interface tracking, which become computationally demanding and sensitive to grid quality in complex geometries and convection-dominated regimes. To address these limitations, this study develops a unified physics-informed neural network (PINN) framework for directly solving the coupled incompressible Navier–Stokes and Volume of Fluid (VOF) equations governing pressure-driven displacement. The framework is first validated against canonical transient flows and then applied to two-phase displacement in parallel-plate channels, semicircular bends, and a casing–annulus geometry representative of well cementing operations. The predicted velocity, pressure, and volume fraction fields exhibit strong agreement with ANSYS Fluent (2024R1) results, with relative errors generally around 5%, thereby demonstrating physical consistency and numerical stability without mesh generation or pressure–velocity splitting, while also showing favorable computational efficiency for the cases considered. Sensitivity analyses demonstrate that a smoother casing-shoe geometry significantly enhances PINN convergence, while higher Péclet numbers deteriorate training stability by increasing convection-dominated stiffness and optimization difficulty. The results demonstrate that the proposed PINN framework, with its mesh-free and geometrically flexible characteristics, is a promising approach for modeling multiphase displacement in cementing applications. Full article

Starvation is a fundamental physiological stressor that triggers conserved adaptive responses across species, however, its effects are shaped by both developmental stage and prior nutritional history. This study aimed to investigate the effects of acute nutrient deprivation in Artemia franciscana, comparing newly hatched nauplii and adult individuals previously exposed to reduced caloric intake during development. Organisms were subjected to starvation for 24, 48, and 72 h, and mortality, morphometric parameters, and locomotor activity were assessed, complemented by in silico analysis of starvation-related pathways. Starvation induced distinct responses between groups, with markedly higher mortality in adults compared to nauplii. While these differences reflect developmental stage-associated responses, they are also influenced by prior nutritional history. Body length was significantly reduced under starvation in both developmental stages, while antennal length remained largely unchanged. Locomotor activity, including distance travelled and swimming velocity, was consistently decreased, indicating energy-conserving behavioral adaptation. Partial recovery of locomotor performance and antennal length was observed following restoration of feeding. Bioinformatic analysis suggested the presence of conserved autophagy-related genes and enrichment of pathways associated with autophagy and TOR signaling. However, these findings should be interpreted as hypothesis-generating, given the reliance on a proxy species for pathway inference. These findings indicate that starvation responses in A. franciscana are shaped by an interaction between developmental stage and prior nutritional history, supported by conserved stress–response pathways, highlighting the potential of this model for studying metabolic stress responses. Full article

This study investigates the aerodynamic, aeroacoustic, and psychoacoustic behaviour of a side-by-side twin-propeller Unmanned Aerial Vehicle (UAV) system operating under both static and forward-flight conditions, with particular focus on the effects of asynchronous rotational speeds. Experiments were conducted using two identical five-bladed constant pitch propellers with a diameter of 9 in (228.6 mm) and a pitch to diameter ratio of 1. Rotational speed differences between 0 and 300 rpm were examined in 50 rpm increments at inflow velocities of 0 m/s, 14 m/s and 24 m/s. The results show that variations in rotational speed have a significant influence on both acoustic levels and perceived annoyance. Asynchronous operation causes the dominant tonal peak at the blade passing frequency to split into two components, reducing tonal reinforcement. This produces noise level reductions of approximately 2 dB in static and high advance ratio conditions, increasing to about 5 dB reduction at low advance ratios. Psychoacoustic metrics show greater sensitivity to tonal structure than to overall sound pressure level, with annoyance reductions of about 5% in static conditions and up to 15% at low advance ratios. A modest aerodynamic penalty of about 5% at $\Delta N=50$ rpm is observed, increasing with larger speed mismatches. Full article

Existing research primarily focuses on ordinary straight roads or curves; however, there is a notable lack of recent research on continuous curves. This research employs Computational Fluid Dynamics (CFD) dynamic mesh technology to numerically simulate the external flow field during vehicle overtaking on a continuous curve resembling a sine wave. This study conducts a numerical simulation to analyze the external flow field of vehicles during overtaking on a continuous curve, similar to a sine curve, using CFD. Using different initial velocities, the study analyzes lateral force on the vehicle body during overtaking. It investigates how dynamic changes in the external flow field affect vehicle dynamics by employing tetrahedral meshes, the SST k-ω turbulence model, and UDF programming. To address emergency overtaking scenarios during medical vehicle rescues, a four-factor orthogonal experimental design was employed to identify the safest overtaking condition: overtaking a small vehicle (5 m × 1.8 m) at 22 m per second with 1.5 times the vehicle width and no crosswind. Regression lines were fitted to the data, yielding a nonlinear regression equation that can predict road conditions, thereby providing theoretical support for intelligent driving systems. Full article

In air jet looms, relay nozzles are critical components in governing airflow velocity and air consumption during the weft insertion process. Although computational fluid dynamics (CFD) offers high-fidelity simulation for aerodynamic analysis, its computational burden hinders its practicality in iterative aerodynamic design of relay nozzles. To address the challenge, this study proposes a data-driven framework integrating a Chebyshev polynomial Kolmogorov–Arnold Network (Chebyshev KAN) surrogate model with an Improved Multi-objective Red-billed Blue Magpie Optimizer (IMORBMO). The accuracy of the Chebyshev KAN model was benchmarked against conventional multilayer perceptrons (MLP), convolutional neural networks (CNN), and the standard Kolmogorov–Arnold Network (KAN). Experimental results demonstrate that the Chebyshev KAN model achieves the lowest mean absolute error (MAE) of 0.103 for airflow velocity and 0.115 for air consumption. Building upon the non-dominated sorting and crowding distance strategies, IMORBMO was developed, incorporating an adaptive mutation mechanism by information entropy for improvement of convergence, diversity, and uniformity of the Pareto-optimal solutions. Comprehensive evaluations on the ZDT and WFG benchmark suites confirm that the IMORBMO consistently attains the best and highly competitive performance, yielding the lowest generation distance (GD), inverted generational distance (IGD) values and the highest hypervolume (HV). Applied to the aerodynamic optimization of a relay nozzle, the proposed framework delivers an optimal aerodynamic design that increases airflow velocity by 10.5% while reducing air consumption by 15.4%, as verified by CFD simulation. The steady-state flow field was simulated by solving the Reynolds-Average NavierStokes equations with the k−ω turbulent model, utilizing Fluent 2025.R2. No-slip wall, inlet pressure and outlet pressures are boundary conditions to the relay nozzle surfaces. This work establishes a computationally efficient and accurate optimization paradigm that holds significant promise for aerodynamic design and other complex real-world engineering applications. Full article

High-temperature proton exchange membrane fuel cells (HT-PEMFCs) coupled with methanol reforming hold promise for distributed energy systems, yet channel hydrodynamics and geometry optimization remain underexplored. This study develops a 3D multiphysics model to investigate coupled behaviors in HT-PEMFCs fueled by methanol reformate. Results reveal bifurcation-induced Dean vortices have dual effects: they cause flow maldistribution (15–18% velocity deviation) and contribute 50% of inlet pressure loss, while generating a lateral pumping effect that enhances local mass transfer. A continuous parametric sweep of channel widths (0.9–1.9 mm) identifies a voltage-dependent performance crossover—narrower channels (1.3 mm) excel at high voltages by improving electronic conduction, whereas wider channels (1.5 mm) perform better at low voltages by mitigating mass transfer limitations. These findings provide quantitative design criteria for optimizing flow field geometry in HT-PEMFC stacks. Full article

This paper develops an extended Cucker–Smale model that integrates nonlinear velocity alignment with state-dependent binding forces to achieve stable, collision-free flocking in multi-agent systems. Our framework introduces two dedicated control mechanisms: a velocity-dissipative term $\left(K_1\right)$ for accelerated convergence, and a distance-regulating term $\left(K_2\right)$ for formation cohesion and collision avoidance, which collectively ensure stable flocking. Rigorous Lyapunov analysis establishes provable guarantees for asymptotic velocity alignment and collision safety under verifiable initial energy conditions. Numerical simulations validate the theoretical predictions for a 20-agent swarm; scalability analysis demonstrates effective coordination in systems of up to 100 agents and reveals that velocity synchronization improves substantially—with errors decreasing by nearly two orders of magnitude—as $K_2$ increases from 0.05 to 0.50. A Pareto-optimal parameter region ($K_2\in [0.15,0.30]$) is identified, which achieves sub-centimeter-per-second alignment accuracy while maintaining energy consumption below 35% of the baseline. The proposed framework provides a theoretically rigorous yet practically viable solution for applications demanding guaranteed safety and precise coordination, such as UAV formations, robotic swarms, and autonomous vehicle platoons. Full article