Li Zhou

Cavitation state transition and the underlying flow mechanism are core issues in fluid physics, especially in the underwater propulsion systems. Inflow velocity variation alters local flow structure and pressure distribution, regulating cavitation inception and critical collapse in pump-jet propulsors (PJPs). This study focuses on the fluid physics of cavitation state transition, investigating the effects of inflow velocity on cavitation inception (cavitation number σn = 3.0) and critical collapse state (σn = 1.5) in a PJP using improved delayed detached eddy simulation coupled with the Schnerr–Sauer cavitation model. The results reveal a critical advance coefficient J = 0.8 at σn = 1.5, which serves as the boundary for cavitation state transition: for J ≤ 0.6, the flow field is dominated by strong backflow in the mid-chord region, leading to severe cavitation with chaotic vortex structures, characterized by cavitation volume Cv = 0.0106 and coverage area Cs = 93.41% at J = 0.2; for J ≥ 0.8, the flow transitions to a forward-flow dominated state, vortex structures recover to organized horseshoe and tip vortexes, and Cs = 48.69% at J = 0.8. At σn = 3.0, cavitation is strongly suppressed, with Cv at J = 0.2 only 0.93% of that at σn = 1.5, and the flow field remains stable despite occasional excitation force spikes. A key new finding is that inflow-driven flow pattern transition governs cavitation regime shift, where backflow-vortex-collapse coupling causes sudden hydrodynamic degradation. Furthermore, the interquartile range of rotor excitation force, which reflects flow unsteadiness, is approximately 2.4 times higher at J = 0.2–0.6 than at J = 0.8, confirming the close correlation between flow stability and cavitation state. This study provides theoretical guidance for cavitation suppression in underwater propulsion systems.

As an efficient and inexpensive acquisition platform, Unmanned Aerial Vehicles (UAVs) are particularly suitable for image acquisition in 3D ship reconstruction tasks. However, path planning in ship reconstruction tasks is often required to consider the energy consumption of UAV batteries and the applicability of the reconstruction method, which introduces challenges to the efficient reconstruction of high-fidelity 3D ship models. To address the above challenges, this paper proposes a Neural Radiance Field (NeRF) representation-based efficient UAV path planning framework for high-fidelity 3D ship reconstruction. First, a multi-modal adaptive generation strategy for rays in NeRF is proposed by fusing the features of the point cloud and image. Second, a novel reward function and a viewpoint partitioning optimization guidance strategy for the deep reinforcement learning of the UAV path planning framework are proposed to ensure the efficiency and robustness of ship reconstruction tasks. To further optimize the 3D reconstruction result of the ship, a local adaptive distance-aware sampling policy is proposed to boost the overlap rate of the image data, which enhances the framework’s applicability for downstream reconstruction tasks. Finally, we demonstrate the efficiency and applicability of the UAV path planning framework through a series of experiments.

Collisions between ships and sea ice pose a significant threat to maritime safety, making it essential to detect sea ice and perform safety-oriented path planning for polar navigation. This paper utilizes an optimized You Only Look Once version 5 (YOLOv5) model, designated as YOLOv5-ICE, for the detection of sea ice in satellite imagery, with the resultant detection data being employed to input obstacle coordinates into a ship path planning system. The enhancements include the Squeeze-and-Excitation (SE) attention mechanism, improved spatial pyramid pooling, and the Flexible ReLU (FReLU) activation function. The improved YOLOv5-ICE shows enhanced performance, with its mAP increasing by 3.5% compared to the baseline YOLOv5 and also by 1.3% compared to YOLOv8. YOLOv5-ICE demonstrates robust performance in detecting small sea ice targets within large-scale satellite images and excels in high ice concentration regions. For path planning, the Any-Angle Path Planning on Grids algorithm is applied to simulate routes based on detected sea ice floes. The objective function incorporates the path length, number of ship turns, and sea ice risk value, enabling path planning under varying ice concentrations. By integrating detection and path planning, this work proposes a novel method to enhance navigational safety in polar regions.

When ships navigate in ice-covered waters, their propellers inevitably collide with sea ice, causing safety problems. Understanding the ice loads and structural responses during propeller–ice interactions is crucial to optimizing propeller design and ensuring operational safety. Unlike conventional hydrodynamic analysis of propellers, the structural response analysis of ice-strengthened propellers operating in polar regions involves a complex nonlinear fluid–structure interaction among ice, water, and the propeller, which remains a challenging research topic in the current academic field. This study establishes a multiphase ice–water–propeller coupling model using the nonlinear finite element method to investigate the dynamic response of ice class propeller under various ice conditions. With the nonlinear finite element analysis software LS-DYNA, a sea ice model is developed by combining the cohesive element method with elastic-brittle material failure model. The arbitrary Lagrangian–Eulerian method is adopted for multiphase coupling, aimed to analyze the propeller response under combined influence of seawater and sea ice. Numerical simulation results are compared with experimental results, indicating that peak load and average errors are within 15%, and load duration errors within 5% by considering water effect. Neglecting water effect, the deviation between simulated and experimental resultant moment peak is up to 43%. An ice–propeller milling model was proposed to examine dynamic impact processes, nonlinear ice loads, and the stress and deformation distribution on propeller blades during milling. The results reveal that under direct contact, ice loads exhibit low-frequency discrete characteristics, with significant stress concentrations at blade edges and roots, and large deformations at blade tips and leading edges. The findings show that milling depth and propeller speed significantly affected load duration, with greater milling depth and ice floe velocity resulting in increased ice loads and deformation areas. The multiphase coupling model effectively simulates different ice–propeller interaction processes, providing insights into ice loads and structural responses and offering important guidance for propeller design and operational strategies in polar environments.

The cryosphere constitutes a vital component of the Earth’s system

During the submarine's surfacing process, the rotor of the pump-jet propulsor (PJP) is subjected to nonuniform hydrodynamic loads and cavitation, inducing cavitation-induced noise. In this paper, the hybrid Reynolds Averaged Navier–Stokes/Large Eddy Simulation method, the Schnerr–Sauer model and Ffowcs Williams–Hawkings equations are adopted to explore the hydrodynamics, excitation force, radiation noise, cavitation evolution of the PJP with different cavitation numbers σn and oblique angles θ. The results show that when the σn decreases from 1.5 to 1.0, the rapid development of cavitation causes the hydrodynamic performance of the PJP to deteriorate rapidly, and the total thrust coefficient KT decreases by 28.5%. The influence of σn on the excitation force is less than that of the θ. When θ equals 0 deg, its excitation force is approximately 1.5 times that when θ is 6 deg. As θ increases from 6 deg to 24 deg, the excitation force increases rapidly, and the excitation force of KT increases by 4 times. The contribution of the excitation force to noise is reflected below 300 Hz, while the noise in the range of 300–5000 Hz is caused by cavitation. When θ is equal to 0 deg, the spatial distribution of cavitation is relatively uniform, the cavitation volume change rate is the fastest, and the collapse frequencies are almost the same. The cavitation-induced noises are superimposed on each other, and its total sound pressure level is nearly 7 dB higher than that when θ is 6 deg. This research provides a theoretical basis for the anticavitation and low-noise design of the PJPs.