The energy-conversion stability of hydropower is critical to satisfy the growing demand for electricity. In low-head hydropower plants, a gravitational surface vortex is easily generated, which causes irregular shock vibrations that damage turbine performance and input-flow stability. The gravitational surface vortex is a complex fluid dynamic problem with high nonlinear features. Here, we thoroughly investigate its essential hydrodynamic properties, such as Ekman layer transport, heat/mass transfer, pressure pulsation, and vortex-induced vibration, and we note some significant scientific issues as well as future research directions and opportunities. Our findings show that the turbulent Ekman layer analytical solution and vortex multi-scale modeling technology, the working condition of the vortex across the scale heat/mass transfer mechanism, the high-precision measurement technology for high-speed turbulent vortexes, and the gas–liquid–solid three-phase vortex dynamics model are the main research directions. The vortex-induced vibration transition mechanism of particle flow in complex restricted pipelines, as well as the improvement of signal processing algorithms and a better design of anti-spin/vortex elimination devices, continue to draw attention. The relevant result can offer a helpful reference for fluid-induced vibration detection and provide a technical solution for hydropower energy conversion.

Multiphase vortices are widely present in the metallurgical pouring processes, chemical material extraction, hydroelectric power plant energy conversion, and other engineering fields. Its critical state detection is of great significance in improving product yield and resource utilization. However, the multiphase vortex is a complex dynamics problem with highly nonlinear features, and its fluid-induced vibration-generation mechanism faces significant challenges. A fluid-solid coupling-based modeling method is proposed to explore mass transfer process with the vorticity distribution and vibration-generation mechanism. A vibration-processing method is utilized to discuss the four flow-state transition features. A fluid-induced vibration experiment platform is established to verify the numerical results. It is found that the proposed modeling method can better reveal the vibration-evolution regularities of the fluid-solid coupling process. The flow field has a maximum value in the complex water–oil–gas coupled flow process, and induces a pressure pulsation phenomenon, and its frequency amplitude is much larger than that of the water phase and water–oil two-phase flow states. In the critical generation state, the increasing amplitude and nonlinear step structure of high-frequency bands (45 Hz~50 Hz) and random pulse components can be used for the online detection of multiphase-coupling states.

Proton exchange membrane fuel cells (PEMFCs) represent a new generation of clean and efficient energy conversion devices, demonstrating broad application prospects in transportation, distributed power generation, and other fields. The geometric configuration of the cathode gas channel (GC) and the surface microstructure of the gas diffusion layer (GDL) are core factors influencing the efficiency of reactant gas transport and water management performance. However, conventional rectangular flow channels suffer from insufficient convective enhancement and restricted oxygen supply beneath the fins. Furthermore, homogeneous GDLs exhibit limited diffusion and drainage capabilities, often leading to oxygen depletion and flooding downstream of the cathode, significantly limiting overall cell performance. To address these challenges, this study designs a novel centrally positioned fin-type barrier block. A three-dimensional multiphysics numerical model integrating GDL surface microporosity with the internal barrier block flow channels is constructed to systematically investigate the synergistic mechanisms of microporous topology and flow channel structure on two-phase flow distribution, oxygen mass transfer, and electrochemical performance. The results demonstrate that this model accurately captures the dynamic evolution of flow fields within the GDL. Compared to conventional structures, significant coupling effects exist between the GDL microporous structure and the novel barrier block. Their synergistic interaction forms multi-scale mass transfer enhancement and dewatering pathways, providing quantifiable optimization pathways and structural parameter references for high-power-density PEMFC cathode design.

Proton exchange membrane fuel cells (PEMFC) are recognized as promising next-generation energy technology. Yet, their performance is critically limited by inefficient gas transport and water management in conventional flow channels. Current rectangular gas channels (GC) restrict reactive gas penetration into the gas diffusion layer (GDL) due to insufficient longitudinal convection. At the same time, the complex multiphase interactions at the mesoscale pose challenges for numerical modeling. To address these limitations, this study proposes a novel cathode channel design featuring laterally contracted fin-shaped barrier blocks and develops a mesoscopic multiphase coupled transport model using the lattice Boltzmann method combined with the volume-of-fluid approach (LBM-VOF). Through systematic investigation of multiphase flow interactions across channel geometries and GDL surface wettability effects, we demonstrate that the optimized barrier structure induces bidirectional forced convection, enhancing oxygen transport compared to linear channels. Compared with the traditional straight channel, the optimized composite channel achieves a 60.9% increase in average droplet transport velocity and a 56.9% longer droplet displacement distance, while reducing the GDL surface water saturation by 24.8% under the same inlet conditions. These findings provide critical insights into channel structure optimization for high-efficiency PEMFC, offering a validated numerical framework for multiphysics-coupled fuel cell simulations.

Three-dimensional LiDAR point clouds are extensively used in target recognition and surface defect detection. However, surface models frequently suffer from missing data due to factors such as sensor blind spots, varying surface reflectance, and multi-scan registration errors. To address this, this paper presents an adaptive multi-hole repair method specifically designed for non-uniform LiDAR point clouds. An adaptive neighborhood and angle-threshold model is constructed first that incorporates local density and curvature features to improve angle-based boundary detection. The heterogeneous hole boundaries are then classified and extracted according to the spatial distribution of the boundary points and their neighboring points relative to the boundary centroid. To preserve geometric characteristics, a variable-bandwidth mechanism is introduced to optimize least-squares fitting for multi-hole surface reconstruction. Furthermore, a boundary preprocessing strategy is designed to regularize boundary point distributions and remove erroneous samples, ensuring smooth transitions between interpolated and original points. Comparative experiments on complex surface models and high-noise LiDAR data validate the effectiveness of the proposed method. In multi-hole repair scenarios, the adaptive approach achieves an average boundary identification error rate of approximately 18%, while the reconstruction error is kept within 5%. The proposed method provides an adaptive and practical solution for repairing point clouds with multiple holes, demonstrating strong potential for real-world applications.