Search Results (222)

Background/Objectives: Severe acquired brain injury (sABI) disrupts early rehabilitation because arousal fluctuates, trunk control is fragile, and agitation limits therapy tolerance; land-based practice is frequently constrained by fall risk and staffing. We aim to reframe aquatic therapy as a programmable multisensory environment to stabilize arousal and support axial alignment before conventional impairment targets are feasible. Here, programmable denotes the deliberate titration and reporting of water depth, turbulence or perturbation, temperature, body orientation, and flotation and manual support as intervention inputs. Methods: This perspective integrates principles from neurobehavioral assessment, motor control, and immersion physiology to propose the Arousal–Alignment–Action loop as a falsifiable model and to define manipulable aquatic inputs (water depth, turbulence or perturbation, temperature, body orientation, and flotation and manual support) as dosing parameters. We outline a pragmatic testing ladder (within-session micro-experiments, feasibility studies, and embedded evaluations) and a minimal outcomes and confounder set to support cumulative evidence. Results: The framework links state regulation to alignment and goal-directed behavior, specifies predictions that can fail, and highlights boundary conditions (sedation, autonomic instability, pain, recent surgery or wounds, and cervical or cardiopulmonary constraints). A minimal outcome package spanning arousal/responsiveness, trunk control, behavioral dysregulation, participation/tolerance, and basic physiology is proposed, with optional objective adjuncts for mechanism-oriented studies. Conclusions: Treating water as a measurable and titratable medium, rather than a generic modality, may reduce early intensity bottlenecks and improve implementability and comparability of aquatic neurorehabilitation research in medically stable sABI; however, the model is intended as hypothesis-generating until supported by stronger direct clinical evidence. Full article

Oil leakage in oil-immersed power transformers poses a significant threat to grid reliability, potentially causing severe electrical accidents and environmental pollution if not detected in time. Detecting oil leakage outdoors, however, remains challenging due to the impact of weather conditions such as fog, humidity, and rain, which obscure the leakage signs and complicate real-time detection. To address these challenges, we propose a solution that integrates infrared thermal imaging with a CNN-SVM hybrid architecture. The core of this approach lies in shifting from traditional Softmax-cross-entropy-based empirical risk minimization (ERM) to maximum-margin-based structural risk minimization (SRM). A fully fine-tuned MobileNetV3 transforms low-contrast, boundary-softened infrared thermal images—often affected by fog and moisture—into a more discriminative high-dimensional feature space, where positive and negative samples become linearly separable. This is followed by replacing Softmax with a linear SVM and using hinge loss to enforce a margin constraint, which maximizes the classification margin and improves robustness to input perturbations. Experimental results show that our proposed method outperforms all compared models, achieving an accuracy of 0.990, significantly higher than ResNet50_BCE (0.908), EfficientNetB0 (0.925), YOLOv11n-CLS (0.930), and ViT (0.929). In terms of F1-Score (0.989) and AUC (0.995), MobileNetV3-SVM also demonstrates excellent performance, ensuring outstanding classification capability. Additionally, the model achieves an inference latency of only 6.3 ms, demonstrating excellent real-time inference performance, highlighting its potential for transformer oil monitoring applications. This research contributes to SDG 6 by preventing industrial water pollution resulting from transformer oil runoff, thereby protecting vital water sources in remote environments. Full article

Dust pollution has emerged as a critical issue in a wide range of industrial applications, creating an urgent demand for effective strategies to mitigate particle deposition. Recent experimental studies have demonstrated that superhydrophobic coatings represent a promising class of self-cleaning materials, primarily attributed to their hierarchical rough structures and intrinsically low surface energy. Nevertheless, the underlying self-cleaning mechanisms of superhydrophobic surfaces have not yet been fully elucidated. This work examines particle deposition on superhydrophobic surfaces featuring stochastic roughness distributions through computational modeling. Surface topographies were generated using Fast Fourier Transform techniques. An integrated lattice Boltzmann–discrete element method (LBM–DEM) framework simulated particle transport in superhydrophobic-coated channels. Particle–fluid coupling was achieved via the immersed moving boundary approach, while particle–surface interactions employed a modified Johnson–Kendall–Roberts (JKR) adhesion model. Parametric studies quantified effects of particle size, interfacial energy, flow Reynolds number, and topographical statistics on deposition dynamics. Experimental validation demonstrates good agreement between numerical predictions and measurements. Smaller particles exhibit a lower tendency to deposit on superhydrophobic surfaces, whereas increasing surface energy significantly enhances particle deposition due to stronger adhesion forces and the suppression of particle resuspension. In addition, higher Reynolds numbers effectively reduce particle deposition. The revealed self-cleaning mechanisms provide theoretical guidance for the design of high-performance self-cleaning coatings, and the identified effects of particle and surface parameters offer practical insights for anti-pollution engineering applications. Full article

The wake characteristics behind a transom stern vessel play a crucial role in determining its hydrodynamic performance, resistance, and environmental impact. This hydrodynamic phenomenon involves violent wave breaking, posing significant challenges for experimental analysis. In this study, we explore the complex wake dynamics behind a transom stern vessel using high-fidelity three-dimensional numerical simulations. A sharp volume of fluid method is employed to capture the gas–liquid interface, while the immersed boundary method is applied to simulate the ship hull boundaries. A distinct advantage of the present simulation is the capability to conduct quantitative analysis within the turbulent two-phase mixing region characterized by significant air entrainment, which is difficult for traditional experimental and theoretical approaches. The research focuses on the interaction between free surface dynamics, air entrainment and turbulent vortex structures, which collectively shape the wake region. The main flow features of wakes, including wave patterns across various Froude numbers, air entrainment and the evolution of bubbly wakes, are investigated. Furthermore, the correlation between turbulent vortex structures and violent interface breaking is examined. Full article

The recent development of 3D generative AI encompassing generation and editing technologies has been increasingly investigated to advance immersive applications. To enrich visual aesthetics, 3D stylization techniques focus on transferring artistic effects from reference style images to 3D scenes. However, existing 3D stylization techniques primarily focus on global style transfer, which can result in unwanted modifications to background regions and a lack of localized control. To address these limitations, we propose LocalGaussStyle, a novel approach for localized style transfer on scenes represented by 3D Gaussian splatting. The proposed pipeline consists of two phases: object localization and localized stylization. First, 2D instance segmentation masks are projected into a 3D scene to precisely localize target objects. Next, a boundary-aware optimization is designed to perform style transfer and mitigate style leakage caused by the spatial overlap of Gaussians. In addition, geometry-decoupled adaptive densification (GDAD) is employed to enhance the geometric resolution of Gaussians within the target object, thereby improving the representation capacity. The LocalGaussStyle facilitates high-fidelity style transfer that preserves the geometry and appearance of the non-target regions. In terms of style fidelity and background preservation, the effectiveness and efficiency of the proposed method are demonstrated through extensive experiments conducted on various scenes and reference style images. Full article

To explore the influence of inter-formation variables on swimming performance during fish schooling, this paper adopts the sharp interface immersed boundary method based on virtual cells to conduct numerical research on the swimming of three-fish and four-fish swarms with different formations and spacings. The study finds that both streamwise spacing and lateral spacing have significant impacts on the swimming performance of fish schools. In the three-fish formation, when the tandem arrangement has a streamwise spacing of 1.3 times the body length (L), the trailing fish achieve the highest swimming efficiency; when the parallel arrangement has a lateral spacing of 0.25L, the fish in the middle position exhibits the optimal swimming performance. In the four-fish formation model, fish in symmetric positions within the same swarm have similar hydrodynamic performance. For the diamond formation, under the configuration of streamwise spacing 1.2L and lateral spacing 0.5L, the propulsive efficiency of the trailing fish is markedly diminished; however, for the rectangular formation, all trailing fish obtain lower swimming efficiency, and a stable 2S-type vortex structure appears in the wake under the configuration of streamwise spacing 1.5L and lateral spacing 0.5L, which is conducive to thrust generation. The conclusions of this paper can provide certain hydrodynamic advantages and support the development of bionic underwater vehicles and robot technology. Full article

The settling and rising of spherical microplastic particles with different Reynolds numbers, $Re$, were studied using a fully coupled large eddy simulation–discrete element method (LES-DEM) model, where the particles were treated using the immersed boundary method. Twelve different simulations were performed to find the drag coefficient $C_D$, particle trajectories, and wake patterns of both settling and rising microplastic particles. Results were compared to experimental findings from the literature and the comparisons show that the present LES-DEM model produces accurate values for $C_D$ when $Re\lesssim 310$ and qualitatively captures both wake patterns and particle trajectories for $1\lesssim Re\lesssim 5235$. Full article

Cold-bent glass has been utilized in a number of landmark projects globally, owing to its cost-effectiveness and low carbon footprint. To investigate the impact of cold bending loads on the long-term performance of insulating laminated glass, this paper proposes a durability testing method for cold-bent glass. This method is based on the hypothesis that the failure of the glass sealing system is caused by the cold bending process. It is novel in its use of full-scale glass panel specimens subjected to the maximum design cold-bend curvature to replicate the worst-case sealing boundary conditions present in actual installations. This method comprises three components: cold bending, cyclic immersion in water, and high–low temperature cycling. The durability is evaluated by assessing the laminating condition and sealing performance of the insulating laminated glass before and after testing. In total, 24 insulating glass samples from an actual engineering project were studied by the proposed methodology. The results indicate the following: (1) the proposed method demonstrates strong operational feasibility, suitable for durability testing and the assessment of cold-bent insulating laminated glass across diverse dimensions; (2) no significant quality or sealing issues were observed in the tested samples during the tests, suggesting that durability is minimally affected when the glass’s cold bending warpage is controlled within certain range; and (3) a discernible trend observed in the full-scale test data is that cold bending results in increased misalignment and decreased argon content. These findings provide a valuable reference for the design and construction of cold-bent glass curtain wall projects. Full article

Fluid–structure coupling is a prominent and hot topic in computer graphics and virtual reality. The hybrid technique known as FLIP combines the benefits of grid-based and particle-based techniques. Nevertheless, a significant problem is figuring out how to accomplish fluid–structure coupling interaction based on the FLIP technique framework. We propose an immersed boundary approach to handle the problem of realistic fluid–structure coupling interaction under the FLIP framework. The benchmark test results demonstrate that, in addition to producing rich fluid–structure coupling interaction results, our novel technique also effectively reflects the effects of moving obstacle boundaries on the flow and pressure fields, thereby expanding the application area of the FLIP method. Full article

The rapid expansion of China’s photovoltaic (PV) industry has led to a significant increase in decommissioned PV modules. To address the high energy consumption and environmental impact of traditional recycling techniques, this study proposes a novel method that integrates DMPU solvent recycling with pyrolysis for recovering PV cell sheets. DMPU, an organic solvent with low volatility, non-toxicity, and excellent recyclability, was used in this study. The effects of temperature and treatment duration on the structural integrity of silicon cell sheets were systematically evaluated, establishing optimal parameters: immersion in DMPU at 200 °C for 60 min, followed by pyrolysis at 480 °C for 60 min. A case study was conducted on a small-scale recycling facility with a daily processing capacity of 200 standard PV panels, encompassing system boundaries such as transportation, pretreatment, and pyrolysis. The recycling process consumed 2.14 × 10⁹ kJ of energy annually, reducing CO₂ emissions by 9357.2 tons. Compared to conventional methods such as pyrolysis, mechanical dismantling, and chemical dissolution, the proposed approach employing a green, recyclable solvent markedly reduces energy consumption and carbon emissions, offering notable environmental benefits. Full article

This study develops a two-dimensional numerical model to investigate the hydrodynamic performance of a floating breakwater coupled with flexible wave-dissipating structures (FWDS). The model integrates the immersed boundary method with a finite element structural solver, enabling accurate simulation of fluid–structure interactions under wave excitation. Validation against benchmark cases, including cantilever beam deflection and flexible vegetation under waves, confirms the model’s reliability. Parametric analyses were conducted to examine the influence of the elastic modulus and height of the FWDS on wave attenuation efficiency. Results show that structural flexibility plays a crucial role in modifying wave reflection, transmission, and dissipation characteristics. A lower elastic modulus enhances energy dissipation through large deformation and vortex generation, while higher stiffness promotes reflection with reduced dissipation. Increasing the height of the FWDS improves overall wave attenuation but exhibits diminishing returns for long-period waves. The findings highlight that optimized flexibility and geometry can effectively enhance the energy-dissipating capacity of floating breakwaters. This study provides a theoretical basis for the design and optimization of hybrid floating breakwaters integrating flexible elements for coastal and offshore wave energy mitigation. Full article

Complex fluid–particle interactions are ubiquitous in natural environments and engineering applications, with their underlying mechanisms often attributed to interparticle attraction and repulsion. To understand the interaction mechanism between the dual particles, this study examines the setting process of dual particles using the Immersed Boundary-Lattice Boltzmann Method (IB-LBM), with a focus on the effect of the density difference between particles. Two typical configurations—tandem and side-by-side—are considered in the analysis. In the tandem configuration, when ${\rho }_{LP}/{\rho }_{TP}<1$, the TP inevitably kisses the LP due to its greater settling velocity, thus initiating the classical drafting-kissing-tumbling phenomenon. As the density of the TP further increases, the attractive effect exerted by the LP on the TP becomes weak. Conversely, when ${\rho }_{LP}/{\rho }_{TP}>1$, kissing between two particles is mainly determined by the density of LP. Whether kissing occurs between the two particles depends on a critical value ${\rho }_{LP}/{\rho }_{TP}=1.2:1.14$. Although the LP’s attraction to the TP strengthens with increasing LP density, beyond this certain threshold, this attraction becomes insufficient for the TP to catch up with the LP. In a side-by-side configuration with two particles of different densities, their interaction evolves from initial attraction to subsequent repulsion. This phenomenon is not observed in pairs of particles with identical density. Moreover, with increasing density difference between the particles, the attractive effect from the higher-density particle on the lower-density one strengthens, whereas the repulsive interaction between them gradually weakens. When the particle density ratio reaches $1.4:1.14$, the lateral migration of the particles becomes very small; although they still interact with each other, the effect becomes extremely weak. This work systematically elucidates the influence of density disparity on particle interaction, providing insights into understanding more complex multiparticle system dynamics. Full article

Advection–diffusion–reaction-type interface models have wide-ranging applications in environmental science, chemical engineering, and biological systems, particularly in modeling pollutant transport in groundwater, reactive flows, and drug diffusion across biological membranes. This paper presents a novel numerical method for the solution of these models. The proposed method integrates the meshless collocation technique with the finite difference method. The temporal derivative is approximated using a finite difference scheme, while spatial derivatives are approximated using radial basis functions. The interface across the fixed boundary is treated with discontinuous diffusion, advection, and reaction coefficients. The proposed numerical scheme is applied to both linear and non-linear models. The Gauss elimination method is used for the linear models, while the quasi-Newton linearization method is employed to address the non-linearity in non-linear cases. The $L_{\infty }$ error is computed for varying numbers of collocation points to assess the method’s accuracy. Furthermore, the performance of the method is compared with the Haar wavelet collocation method and the immersed interface method. Numerical results demonstrate that the proposed approach is more efficient, accurate, and easier to implement than existing methods. The technique is implemented in MATLAB R2024b software. Full article

Nonlinear water waves (NWWs) can be generated by the vertical bottom disturbance, which represents the conceptual processes of the rise of seabed rupture under seismic loads. To explore the correlation between the disturbance parameters and the wave features, a Reynolds-averaged Navier–Stokes (RANS) model is applied, with the flow turbulence and fluid–structure interaction (FSI) being resolved by the k–ɛ model and the immersed boundary method (IBM), respectively. The free surface is tracked using the volume of fluid (VOF) method. After validating against the theoretical solutions and experimental results, the effects of disturbance duration and bulk on the wave features at the source region (the generation stage) and offshore direction (the propagation stage) are systematically discussed. The fixed maximal vertical displacement is considered, with four moving durations and five disturbance widths being simulated, resulting in four disturbance velocities and five disturbance bulks. The results indicate that the proposed RANS model can accurately create various wave patterns (including the linear, solitary, and tsunami-like waves) generated by bottom disturbances. Special attentions are paid to the tsunami-like wave. The wave evolution exhibits strong dependence on disturbance duration and width, with shorter durations triggering earlier soliton fission and longer widths accelerating phase celerity. These findings highlight the critical role of disturbance parameters in governing soliton formation and energy propagation patterns, which are vital in disaster forecasting. Full article

This study addresses the trade-off between accuracy and efficiency in predicting the aerodynamics and wakes of large wind turbines. We developed a unified immersed boundary–actuator line framework with large-eddy simulation. The actuator line efficiently represents blade loading, while the immersed boundary method (IBM) with a wall model resolves near-blade turbulence. The solver uses a staggered Cartesian discretization and is accelerated by a hybrid CPU/GPU implementation. An implicit signed-distance geometry treatment and a ghost cell wall function based on Spalding’s law reduce near-wall grid requirements and eliminate body-fitted meshing. Flow past a three-dimensional cylinder at Re = 3900 validates the accuracy and good grid convergence of the IBM. For the wind turbine, three meshes show converged thrust and torque, with differences below 1% between the two finer grids. At the rated condition (U_∞ = 11.4 m/s), thrust and torque agree with STAR-CCM+ and FAST, with deviations of 6.3% and 1.2%, respectively. Parametric cases at 4–10 m/s show thrust and torque increasing nonlinearly with inflow, approximately quadratically, in close agreement with reference models. As wind speed rises, the helical pitch tightens, the wake broadens, and breakdown occurs earlier, consistent with stronger shed vorticity. The framework delivers high fidelity and scalability without body-fitted meshes, offering a practical tool for turbine design studies and extensible wind plant simulations. Full article