Search Results (701)

Aircraft wake vortices pose significant threats to following aircraft during takeoff and landing phases. Coherent Doppler lidar provides an effective remote sensing technique for wake vortex monitoring through radial velocity measurements. However, reliable identification of wake vortices from lidar observations remains challenging due to noise and the complex multi-scale evolution of vortex structures. In this study, we propose a physics-guided multi-scale deep network (HMNet) for aircraft wake vortex identification. First, we propose a denoising module (DE) to suppress noise in radial velocity fields. Subsequently, we design a hybrid multi-scale backbone network containing a hybrid multi-scale feature extraction module (HMFE) to capture vortex structures at different spatial scales. Furthermore, we propose a feature gradient guidance module (FGGM) to incorporate physically meaningful gradient cues and enhance vortex-sensitive features. HMNet is evaluated and tested on 1401 radial velocity field data samples collected on the runway at Shenzhen Bao’an Airport. The experimental results show that HMNet achieves 97.15% accuracy, 95.83% recall, and 96.84% F1 score. Compared with the baseline VGG16 and Random Forest, HMNet improves accuracy by 6.18% and 11.88%, respectively. These results demonstrate that HMNet provides an effective solution for lidar-based wake vortex identification and can support the development of intelligent air traffic management. Full article

The mechanism by which fish enhance hydrodynamic performance through collective swimming is a research hotspot in the field of underwater bionic robots. This study employs the Immersed Boundary-Lattice Boltzmann Method (IB-LBM) to conduct numerical simulations on a two-dimensional, single-degree-of-freedom (1-DOF) autonomous propulsion bionic fish swarm. It systematically investigates the effects of swarm size and inter-individual spacing on swimming speed and cost of transport (CoT) under two typical configurations: series and parallel arrangements. Findings reveal that hydrodynamic benefits are highly dependent on the spatiotemporal evolution of flow field structures. In the series configuration, an optimal spacing range of 1.5 L to 2.0 L exists within the school, where the “wake capture” effect is pronounced. Trailing fish achieve a maximum speed increase of approximately 41.1% while significantly reducing energy consumption. However, as spacing increases to 2.5 L, the cooperative gain for front and middle-row individuals rapidly diminishes, and the lead fish even experiences significant performance loss. Uniquely, the trailing fish in the four-fish formation exhibits distinct flow field reorganization and performance recovery at the 4.5 L trailing position. In the parallel formation, the “channel effect” and “blocking effect” of the fluid dominate. The study identifies 0.4 L laterally as the critical instability spacing under the investigated kinematic regime, where strong destructive interference causes a sharp deterioration in individual swimming performance. Additionally, the parallel formation exhibits pronounced positional differentiation. Central individuals, constrained by dual lateral flow fields, experience restricted lateral wake expansion and accelerated energy dissipation, resulting in significantly weaker escape capabilities from low-speed conditions compared to marginal individuals. The vortex-dynamic mechanism revealed herein provides theoretical foundations for formation control in multi-fish biomimetic cooperative systems. Full article

This study examines the electrohydrodynamic (EHD) behavior of air bubbles rising in deionized water under a non-uniform electric field, with particular emphasis on the influence of applied voltage (0.5–3.0 kV) and gas flow rates of 30 and 40 mL ${\min }^{-1}$ (corresponding to Reynolds numbers of $R{e}_g=107$–142) on bubble dynamics. High-speed imaging reveals bubbles with equivalent diameters in the range of $d_{eq}\approx 0.8$–3.5 mm, enabling a detailed characterization of their deformation, trajectory, and interfacial response under coupled hydrodynamic and electric stresses. At $R{e}_g=107$, bubbles exhibited stable vertical trajectories with negligible lateral displacement, whereas at $R{e}_g=142$, inertial and wake effects induced deviations. Increasing $B{o}_E$ reduced lateral displacement, restoring alignment with the electric field. Bubble rise velocities increased by ∼20–30% with applied voltage due to polarization-driven EHD forces. A transition from hydrodynamically dominated to EHD-dominated regimes was identified. While polarization forces govern the initial bubble motion under a strong electric field, bubbles progressively transition downstream to a hydrodynamic regime as the electric field weakens, reducing the influence of polarization effects. These findings provide quantitative insight into coupled hydrodynamic–electrohydrodynamic interactions and support the development of predictive models for controlling bubble trajectories, with implications for electrically tunable multiphase and microfluidic systems. Full article

For AUVs operating under large-rudder-angle yaw maneuvering conditions, linearized hydrodynamic-derivative models often fail to accurately capture strongly nonlinear flow effects, and the applicability of control parameters becomes limited. To address these issues, this paper proposes a CFD-in-the-loop control simulation and parameter optimization framework for large-rudder-angle yaw maneuvers. Based on a coupled hull–propeller–rudder solution method, an unsteady CFD motion simulation model is developed that simultaneously accounts for propeller wake, rudder inflow, and hull-flow interaction, thereby enabling a strongly coupled solution of flow-field evolution and the six-degree-of-freedom motion of the vehicle. On this basis, a CFD-in-the-loop closed-loop control simulation framework is established by integrating the controller, actuator dynamic model, virtual sensors, and CFD motion simulation module into a unified framework, thereby realizing closed-loop computation of control input, flow response, motion update, and state feedback. Furthermore, under the same controller structure and parameter settings, the large-rudder-angle yaw responses predicted by the linearized hydrodynamic-derivative model and the CFD-in-the-loop simulation framework are compared and analyzed. This comparison reveals the dependence of control parameters on the underlying dynamic model and highlights their limited applicability under strongly nonlinear operating conditions. Finally, to address the high computational cost of CFD-in-the-loop simulations, a surrogate-model-based control parameter optimization method is developed to improve parameter tuning efficiency and enhance closed-loop control performance. The results show that the proposed CFD-in-the-loop control simulation framework can effectively characterize the nonlinear hydrodynamic effects arising during large-rudder-angle maneuvers, and provides a more physically consistent basis for control parameter optimization, analysis, and design. Full article

Amid the global transition to carbon neutrality, tidal current energy has become a strategic sustainable energy resource due to its high predictability, power density, and environmental compatibility. Horizontal-axis turbines show great potential for marine energy harvesting, yet the large-scale commercialization of tidal turbines is severely hindered by complex wake dynamics and the lack of reliable, efficient prediction tools for out-of-distribution (OOD) operating conditions. Traditional high-fidelity CFD methods are computationally prohibitive for engineering optimization, while conventional data-driven surrogate models suffer from poor extrapolation performance, extrapolation collapse near training parameter boundaries, and the absence of uncertainty quantification. To address these bottlenecks, this study focuses on the OOD extrapolation of wake flow prediction across tip speed ratio (TSR) distributions for a single horizontal-axis tidal turbine. A CFD-generated spatiotemporal benchmark dataset is constructed for comparative OOD evaluation across various TSR conditions with 9504 total samples. A novel physics-constrained Fourier neural operator framework named TSR-FNO is proposed to improve OOD generalization. The model integrates TSR–Lipschitz regularization to suppress extrapolation collapse and Monte Carlo Dropout to provide reliable uncertainty estimation. Extensive experiments demonstrate that the proposed method effectively reduces prediction error in unseen TSR regimes, mitigates performance degradation in far-field extrapolation, and produces well-calibrated uncertainty estimates consistent with actual prediction confidence. This work provides a data-driven surrogate modeling strategy for fast and reliable wake prediction on a common CFD-generated benchmark, supporting the efficient design, array layout optimization, and engineering deployment of tidal current energy systems. Full article

The prediction of dynamic responses of offshore wind turbine foundations under wind-wave-current multi-field coupled loads is the cornerstone of safety in offshore wind power engineering. The currently widely adopted equivalent load application method, while computationally efficient, simplifies loads into concentrated forces applied at the pile top and tower top, neglecting fluid-structure dynamic interaction mechanisms, which leads to deviations in response predictions. To overcome this limitation, this paper proposes a high-precision bidirectional fluid-structure interaction numerical framework. The fluid domain employs computational fluid dynamics (CFD) to construct an air-seawater two-phase flow model, utilizing the standard k-ε turbulence model and nonlinear wave theory to accurately simulate complex marine environments. The solid domain establishes a wind turbine-stratified seabed system via the finite element method (FEM), describing soil-rock mechanical properties based on the Mohr-Coulomb constitutive model. Comparative studies indicate that the equivalent static method significantly underestimates the displacement response of pile foundations, particularly under the extreme shutdown conditions examined in this study. This value should be interpreted as a case-specific observation rather than a universal deviation, and the discrepancy may vary with sea state, wind speed, current velocity, and wind–wave misalignment, thereby leading to non-conservative estimates of stress distribution. In contrast, the fluid-structure interaction method can reveal key physical processes such as local flow acceleration and wake–interference effects around the tower and the parked rotor under shutdown conditions, and the nonlinear interaction and resistance-increasing mechanisms between waves and currents. This model provides a reliable tool for safety assessment and damage evolution analysis of wind turbine foundations under extreme marine conditions, promoting the transformation of offshore wind power structure design from empirical formulas to mechanism-driven approaches. Full article

γ-photon tomography, which leverages the high penetration and electrical neutrality of high-energy γ-photons, offers a promising non-contact approach for industrial flow field monitoring. However, γ-photon flow-field images are inherently grayscale and exhibit probabilistic statistical imaging characteristics, leading to color banding artifacts when processed by mainstream colorization algorithms like DeOldify, which compromise structural continuity and visual consistency. To address this issue, this paper proposes a Structure Enhancement Colorization Network (SECN) model for γ-photon flow-field image colorization. A U-Net + GAN framework is employed, with ResNet101 as the generator backbone. It integrates structure-aware enhancement and multi-scale attention modules, while the discriminator incorporates enhanced blocks for improved boundary and texture discrimination. By adaptively fusing global–local features across channel and spatial dimensions, the SECN model effectively suppresses color banding artifacts and enhances structural consistency. To validate the effectiveness of the proposed algorithm, two CFD-simulated γ-photon flow-field image colorization scenarios—namely a large-scale vortex wake and a horizontal wake—are used as evaluation targets. In terms of image quality metrics, the proposed colorization algorithm achieves PSNR, SSIM, FID, and MAE values of 32.5831, 0.8612, 17.8514, and 0.0191, respectively, corresponding to improvements over DeOldify of 4.54%, 2.82%, 5.18%, and 11.16%. When considering information entropy, the proposed colorization algorithm achieves an average entropy value of 4.0257, marking a 4.44% increase compared to DeOldify’s 3.8543, demonstrating superior information preservation and reduced uncertainty in reconstructing complex probabilistic structures. Furthermore, from the perspective of parameter inversion, the temperature inversion MAPE is 7.60%, which is a significant reduction of 18.42% compared to that of DeOldify. Full article

This investigation is to address the aerodynamic noise generated from laminar flow over a D-shaped cylinder at a low Reynolds number (Re). Proposed is a novel assembly of arc-shaped splitter plates to effectively reduce the aeolian tone for the D-shaped cylinder. The two-dimensional flow field is simulated at an Re of 160 to investigate the mechanism of reducing the sound of the arc-shaped plates. The radiated sound has been predicted by Ffowcs Williams and Hawkings (FW-H) acoustic analogy. To verify calculations, the predicted results of a circular cylinder have been compared with the data in the literature. The results reveal that the introduction of the arc plates decreases the lift and drag fluctuations as well as the vortex shedding frequency in comparison with the no-arc plate case. The pressure and velocity fluctuations in the wake zone are reduced by the arc plates due to vortex shedding suppression. The application of the arc plates shows an effective control of sound, leading to a maximum reduction in sound pressure level (SPL) by almost 34 dB. Full article

In this study, systematic experiments are conducted on a vertical rigid cylinder with two degrees of freedom in the subcritical Reynolds-number regime. The selected flow conditions cover the excitation stage, the lock-in stage, and the post-lock-in stage of vortex-induced vibration. Structural displacements, hydrodynamic forces, and wake vorticity fields are measured simultaneously using laser displacement sensors, force transducers, and particle image velocimetry. The results show that the cross-flow motion remains dominant throughout the investigated range, while the in-line motion is activated through phase coupling within the lock-in region. A stage-dependent redistribution of hydrodynamic loading is identified. The loading first concentrates in the cross-flow direction during synchronization, then partially shifts toward the in-line direction under coupled motion, and finally becomes spatially dispersed as desynchronization develops. This directional redistribution moderates the peak cross-flow amplitude, broadens the lock-in region, and alters the sequence of force-coefficient peaks. The synchronized wake measurements reveal that the flow evolves from incoherent structures to organized vortex streets and then to fragmented and irregular patterns, directly reflecting the formation and collapse of directional load concentration. These findings establish a consistent linkage between hydrodynamic loading, structural response, and wake evolution, and provide experimental evidence for the coupled dynamics of two-degree-of-freedom vortex-induced vibration, offering physical insight for the design and assessment of realistic marine cylindrical structures. Full article

Low-field magnetic stimulation (LFMS) has been proposed as a non-invasive approach for modulating cortical oscillations through electromagnetic coupling. Frequency-aligned enhancement of alpha-band activity is of interest due to its association with cortical inhibitory balance and relaxed wakefulness. This study investigates whether a 10 Hz LFMS applied to the occipital area can induce measurable alpha-band modulation. Electromagnetic simulations were performed to determine magnetic flux distributions within a simplified spherical head model with magnetic susceptibility, which was approximating the brain’s parameters. The 10 Hz stimulation waveform—a positive ramp sawtooth—was analyzed in both time and frequency domains. Electroencephalographic (EEG) recordings were obtained before and after stimulation, and spectral analyses of relevant occipital channels were used to quantify the power redistributions. Simulations indicated localized magnetic field gradients in the occipital region. Post-stimulation EEG recordings showed a redistribution of spectral power toward the alpha-band, representing approximately 50% of total occipital spectral power, with relative increases exceeding 140% across the analyzed channels. These combined modeling and electrophysiological findings provide preliminary proof-of-concept evidence that frequency-aligned LFMS is associated with a redistribution of spectral power toward the alpha-band. Full article

To address the demand for a micro-power supply for vehicle suspension control, a novel harvester is proposed to recover vortex-induced vibration energy in the wake of a shock absorber. A suspension dynamic model was established to simulate the spring compression process and identify the wind-shielding condition. The spring-shock absorber assembly was then simplified as a stepped cylinder with two cross-sections. Flow-field analysis showed that the size, shape, and rising angle of the wake vortices were affected by the bluff-body geometry, Reynolds number, and boundary conditions. The downwash motion was found to directly influence vortex development, and two new vortex-connection modes were identified. These results provided guidance for harvester optimization. A two-way fluid–structure interaction model was developed to describe the electromechanical conversion behavior of the proposed harvester under flow excitation. Numerical results showed that the output voltage increased with vehicle speed. An average peak voltage of 1.82 V was obtained when the piezoelectric patches were installed two larger-cylinder diameters downstream. The optimal patch length was 120 mm, and further increasing the length did not significantly improve the harvesting performance. Finally, a full-scale prototype was tested, and the measured voltage agreed well with the simulation results. The proposed harvester can therefore serve as a potential micro-power source for low-power suspension electronics. Full article

Background/Objectives: Advanced childhood cerebral X-linked adrenoleukodystrophy (cALD) is traditionally regarded as an irreversible terminal phase of neurodegeneration driven by inflammatory demyelination and axonal loss. Experimental evidence indicates that endogenous bioelectrical fields regulate central nervous system organisation, raising the possibility that functional network collapse in cALD may be biologically modifiable, even in the presence of persistent structural damage. This study examined whether longitudinal modulation of endogenous bioelectrical network organisation is associated with sustained clinical and neurophysiological stabilisation in advanced cALD. Methods: We performed a longitudinal observational analysis of two paediatric patients with advanced childhood cerebral X-linked adrenoleukodystrophy undergoing repeated neuroregenerative treatment cycles. Standardised scalp electroencephalography was recorded during spontaneous wakefulness and repeated over months under comparable vigilance conditions. Multimodal analysis included conventional EEG, quantitative EEG, independent component analysis, and standardised low-resolution electromagnetic tomography (sLORETA). Clinical function was assessed using validated measures of consciousness, swallowing, and voluntary motor behaviour. Results: Across patients, longitudinal recordings demonstrated sustained stabilisation of consciousness, swallowing, and voluntary motor function, accompanied by reproducible reorganisation of pathological brain rhythms. Delta and theta oscillations showed a consistent topographical redistribution from limbic–frontoinsular networks towards sensorimotor and parietal integrative cortices. These changes were observed across modalities and timepoints and are unlikely to reflect spontaneous fluctuation, delayed effects of haematopoietic stem cell transplantation, or state-dependent EEG variation. Conclusions: Advanced childhood cerebral X-linked adrenoleukodystrophy is associated with disorganisation of endogenous bioelectrical network activity. In this longitudinal analysis, large-scale network reorganisation was temporally associated with sustained clinical stabilisation, supporting a view of late-stage cALD as a dynamic disorder of network-level vulnerability, rather than a fixed terminal state. Full article

In desert regions, frequent aeolian dust events lead to rapid dust accumulation on greenhouse films, critically compromising light transmittance and inhibiting crop growth. To address this challenge, this study integrated Computational Fluid Dynamics–Discrete Phase Model (CFD-DPM) simulations with field experiments to conduct a comprehensive investigation spanning from microscopic deposition mechanisms to macroscopic physiological responses. Particle characterization revealed a distinct aerodynamic sorting effect, wherein fine particles (<65 μm) preferentially adhered to film surfaces driven by airflow, contrasting sharply with the gravitational settling of coarse ground particles. Numerical simulations further confirmed that as wind speeds increased from 2 to 7 m/s, dust deposition rates exhibited a significant exponential reduction, with accumulation predominantly concentrated in the windward and wake zones. The dust layer covering the film induced a substantial reduction in the indoor daily light integral (DLI), which leads to influence tomato growth that stunted plant height and suppressed the net photosynthetic rate. Physiologically, antioxidant enzyme activities exhibited an initial surge followed by a decline, reflecting photosynthetic constraints and oxidative stress. Consequently, a high-frequency cleaning interval of 7–14 days is recommended to significantly enhance photosynthetic capacity and stress resilience. Full article

Autonomous aerial refueling is a key technology for enhancing the endurance of unmanned aerial vehicles; however, the wingtip vortices generated by the tanker create a strong three-dimensional wake-vortex flow field, whose downwash and lateral airflow can impose significant rolling moments on the follower Unmanned Aerial Vehicle (UAV), posing a serious threat to flight safety. To address this issue, this study proposes an integrated framework that combines wake-vortex risk-field modeling with optimal path planning. The classical Hallock–Burnham (HB) model is first employed to predict vortex descent and lateral transport, while a two-phase model is used to characterize the temporal decay of vortex circulation. The predicted vortex parameters are then coupled with the UAV’s aerodynamic characteristics, and the rolling-moment coefficient (RMC) is introduced as a risk metric to compute its spatiotemporal distribution in three dimensions, thereby transforming the invisible wake-vortex disturbance into a visualizable and quantifiable dynamic three-dimensional risk map. On this basis, a wake-vortex-aware path-planning algorithm based on particle swarm optimization (PSO) is developed, incorporating adaptive weighting and elitist mutation strategies. A multi-objective cost function considering path length, safety, and smoothness is further constructed to search for an optimal safe path under wake-vortex influence. Simulation results indicate that, compared with the classical A* and Rapidly-Exploring Random Tree (RRT) algorithms, the proposed method reduces cumulative risk exposure by approximately 90% and 75%, respectively, while limiting the increase in path length to about 8% (significantly lower than the increases of 40% for A* and 44% for RRT). In addition, the maximum turning angle is constrained within 10°, and the computation time remains around 0.052 s, satisfying real-time requirements. These results demonstrate that the proposed method can generate safe, efficient, and dynamically feasible paths for UAV aerial refueling and provide a valuable reference for wake-vortex avoidance in similar aerospace missions. Full article

Optical remote sensing ship detection faces significant challenges in realistic maritime scenes due to strong background clutter (e.g., docks, shorelines, wake streaks), extreme scale variation, and the elongated geometry of ships with diverse orientations. These factors frequently lead to geometric misalignment, unstable localization, and false alarms, particularly in congested ports and complex sea states. To enhance robustness under clutter while retaining the set prediction efficiency of DETR, we propose the Directional Efficient Network (DENet), a structure-aware enhancement built upon RT-DETR. DENet introduces two complementary components. First, Directional Strip Convolution (DSConv) replaces the standard $3\times 3$ convolution for spatial mixing. By predicting offsets conditioned on input features, DSConv performs strip aggregation that aligns with slender hull structures, thereby suppressing interference from line-shaped background patterns. Second, Efficient Scale Fusion (ESF) augments the Hybrid Encoder as an additive residual correction. It combines multiple receptive field branches with lightweight differential compensation to balance low-frequency context and high-frequency structural transitions, ensuring stable multi-scale fusion in cluttered scenes. Extensive experiments demonstrate the effectiveness of DENet. On ShipRSImageNet, ${\mathrm{AP}}^{\mathrm{val}}$ improves from 58.8% to 63.2% and ${\mathrm{AP}}_{50}^{\mathrm{val}}$ increases from 68.5% to 73.6%. Consistent gains are also observed on NWPU VHR-10, where ${\mathrm{AP}}^{\mathrm{val}}$ reaches 63.0% and ${\mathrm{AP}}_{50}^{\mathrm{val}}$ reaches 94.6%, alongside improvements on the Infrared Ship Database and VisDrone2019-DET, validating the method’s generalization capabilities. Full article