This study aims to investigate the shock load characteristics during implosion and the thermodynamic response mechanisms of a ceramic pressure hull in the extreme deep-sea environment. A numerical simulation method for the implosion of a deep-sea ceramic pressure hull is proposed using a compressible multiphase flow model that ensures pressure-velocity-temperature equilibrium and adaptive mesh refinement (AMR).

The proposed method enables accurate prediction of shock waves and precise capture of the flow field. Then, underwater implosion experiments of the ceramic pressure hull are conducted to verify the effectiveness of the numerical method. Finally, a numerical study on the implosion of a ceramic pressure hull at a depth of 10 000 m reveals the characteristics of the shock load and thermal effects during implosion. The implosion of a deep-sea ceramic pressure hull at different water depths and temperatures is studied numerically, and the effects of these factors are analyzed.

The implosion of a deep-sea ceramic pressure hull releases shock waves outward and produces a significant thermal effect when the gas is highly compressed. As the ambient pressure increases, the peak overpressure of the implosion shock wave decreases, and the shock wave attenuation rate increases. However, the ambient water temperature has little effect on the implosion characteristics of the ceramic pressure hull.

This study provides insights into the implosion characteristics of deep-sea ceramic pressure hull, offering valuable theoretical insights and engineering implications for the assessment and mitigation of underwater implosion effects.

This study aims to investigate the dynamic behavior and flow field characteristics of trans-medium submersibles during underwater straight-line navigation and turning maneuvers.

To this end, computational fluid dynamics simulations were employed, using the VOF multiphase flow model and the SST k–ω turbulence model to establish a numerical model of the underwater navigation of the trans-medium submersibles. The accuracy of the numerical method was validated by comparing the experimental total drag data for the DARPA Suboff submarine model at various speeds with the numerical calculation results. On this basis, numerical simulations and analyses of underwater straight-line navigation and turning maneuvers of the trans-medium submersible were conducted, focusing on the effects of ducted propeller rotation speed and tail fin deflection angle on the underwater straight-line navigation and turning performance of the submersible.

The research results indicate that during straight-line underwater navigation, the forward speed of the trans-medium submersible exhibits an approximately linear relationship with the propeller's rotational speed. For instance, as the propeller speed increases from 600 r/min to 4800 r/min, the forward speed rises from 1.1 m/s to 8.1 m/s. At the same time, the pitch moment becomes less negative with increasing propeller speed (from −0.35 N·m to −0.17 N·m), indicating that the submersible remains stable in pitch during high-speed navigation. The propeller speed has little effect on the surface pressure distribution and the structure of the surrounding flow field. During underwater turning, the turning radius is mainly determined by the tail fin deflection angle and is largely unaffected by the propeller speed. The turning radius decreases with increasing tail fin deflection angle (from 3.35 times the submersible's body length to 0.75 times), though the rate of decrease diminishes. In contrast, the turning speed is affected by both the propeller speed and the tail fin deflection angle. The thrust generated by both propellers increases with higher propeller speeds and larger tail fin deflection angles. During turning, the thrust of the outer propeller consistently exceeds that of the inner propeller, and the thrust difference increases with greater tail fin deflection. Furthermore, tail fin deflection during turning leads to a significantly asymmetric surface pressure distribution on the submersible. This asymmetry becomes more pronounced with increasing tail fin deflection and is closely associated with the asymmetric flow characteristics of the surrounding flow field.

This study provides a reference for the design and performance analysis of trans-medium submersible configurations.

To investigate the acoustic target strength (TS) characteristics of extra-large unmanned underwater vehicles (XLUUVs), this study conducts a systematic analysis of the TS characteristics of the Orca XLUUV in the 1–10 kHz frequency band.

Based on the Orca model, the finite element method is applied to calculate its TS in the 1–3 kHz frequency band, while the planar element method is employed for the 3–10 kHz band. The results are compared with those obtained from the Benchmark model. To provide a more comprehensive evaluation of unmanned underwater vehicle (UUV) stealth performance, the concept of angular detection probability is introduced. Additionally, a scaled model experiment is conducted in a water tank, and a correction method is proposed for the experimental TS measurements.

The TS characteristics of the Orca model are first analyzed. Compared with the Benchmark model, the Orca model exhibits superior stealth performance in the azimuthal direction, along with additional advantages in the circumferential direction at higher frequencies effects that become more pronounced as frequency increases. For experimental cases in which the distance between the hydrophone and transducer does not meet the far-field conditions, the measured TS values are corrected, yielding improved consistency with the simulation results. This validates the accuracy of the numerical simulation results.

The findings of this study provide a theoretical foundation for optimizing underwater detection systems and enhancing the stealth design of UUVs.

To address the challenges in multi-AUV formation maneuvering, such as limited state perception and transmission capabilities, acoustic communication delays, data loss, and reduced observability due to the lack of position information exchange, this study proposes an event-triggered metrology−communication unified framework with a Lyapunov-based model predictive formation control method (ETMCU−LMPC). The proposed approach aims to enhance formation stability and tracking accuracy.

First, by integrating the formation communication topology with system states, an event-triggered mechanism based on state observation is established. This mechanism leverages relative measurements among AUVs to mitigate delays and data loss caused by acoustic communication failures, while improving system observability in the absence of position information exchange. Second, a distributed model predictive controller based on Lyapunov theory is designed. The controller employs backstepping to construct contractive constraints, ensuring recursive feasibility, and incorporates adaptive Kalman filtering (AKF) to compensate for measurement noise, thereby guaranteeing closed-loop stability.

Simulation results of the formation control for five AUVs (1 leader and 4 followers) show that, compared with the traditional LMPC, the proposed ETMCU−LMPC method reduces the convergence time from 8 s to 6 s, the maximum error from 1.12 m to 0.36 m, and the steady-state error from 0.57 m to 0.06 m. Additionally, the control input exhibits greater stability.

The proposed method can effectively cope with communication anomalies, improve the reliability of multi-AUV formations under scenarios with limited state perception and transmission, and thus possesses practical engineering significance.

To address the challenge of simultaneously maintaining formation integrity and enabling flexible obstacle avoidance for multi-unmanned underwater vehicle (multi-UUV) formations in complex underwater environments, this paper proposes a global path planning method that supports adaptive formation reshaping.

The proposed method is built upon an affine transformation framework that maps the cooperative path planning problem of the multi-UUV system into a two-dimensional affine parameter space. First, a front-end path search is conducted using an improved rapidly-exploring random tree* (RRT*) algorithm. By integrating fast exploration and iterative optimization phases, a weighted k-dimensional (KD) tree, a hybrid sampling mechanism, and adaptive tuning of sampling parameters, this algorithm efficiently generates an initial sequence of affine states. Subsequently, a B-spline-based back-end optimizer employs a gradient descent method to minimize a comprehensive objective function that accounts for trajectory smoothness, UUV kinematic feasibility, environmental collision safety, and the cost associated with adaptive formation scaling. The optimization process yields a continuous and smooth trajectory of affine parameters that satisfies multiple constraints.

Lake experiments demonstrate that the proposed planning method can generate safe and feasible formation paths. It successfully guided the multi-UUV formation through a simulated narrow obstacle region, while the actual velocities and accelerations of the UUVs remained within the predefined feasibility constraints.

The proposed global planning method, based on affine transformation, effectively generates safe and feasible paths for multi-UUV formations navigating complex obstacle environments by enabling adaptive formation reshaping. This method significantly enhances the autonomy and environmental adaptability of marine unmanned vehicles, and holds great value for advancing the development and practical application of marine unmanned systems technology.

To address the low docking accuracy of autonomous underwater vehicles (AUVs) in complex underwater environments, a multi-feature fusion vision-based method is proposed.

A self-developed rudderless vector propulsion AUV with four thrusters was used, and the dark channel prior (DCP) dehazing algorithm was adopted for image enhancement. An improved Canny edge detection algorithm was combined with color threshold segmentation to achieve multi-feature fusion. The minimum enclosing circle method was utilized for circle center positioning, and coordinate transformation was performed to calculate the relative position and orientation for docking.

Unity 3D simulations and pool experiments revealed a distance-dependent trend: both mean difference and root mean square error decreased as docking distance decreased. Closer distances yielded higher visual ranging accuracy and docking precision. When the docking distance was less than 2 m, the positioning error was maintained below 5 cm, with an overall success rate of 88%.

The proposed method fulfills the accuracy requirements for AUV autonomous docking and provides a highly robust solution for underwater equipment recovery.

To address the inherent trade-off between large-scale exploration and high-precision manipulation in existing underwater vehicles, a novel morphable underwater intervention robot is developed. Designed for operations at depths of up to 1000 m, the robot integrates low-drag cruising with dual-arm collaborative capabilities, meeting the stringent inspection and maintenance requirements of offshore wind farms and subsea oil and gas platforms.

The overall design specifications were first established, followed by the optimization of the integrated design workflow. The configuration of the robot's pressure-resistant hulls and equipment layout were finalized, with the development of key components, including the morphing mechanism (lead screw lifting mechanism) and pressure-resistant hulls. Strength verification of key components was performed using finite element analysis (FEA) under a 12 MPa hydrostatic load, simulating a depth of 1000 m. Subsequently, the endurance and maneuverability during cruising mode, as well as the manipulator workspace and stability during manipulating mode, were systematically evaluated. Finally, hydrodynamic drag characteristics were verified through CFD simulations, and a coupled vehicle-manipulator dynamic model was developed in Matlab to validate the robot's self-recovery, disturbance rejection, and coupling suppression performance.

The results indicate that the internal layout is rational, with critical components meeting the operational requirements for 1000 m deep-sea environments. The maximum stress within the pressure hulls remains below the yield strength of the selected materials. In cruising mode, the robot achieves a maximum endurance of 7 h, and the configured propulsion system ensures high underwater maneuverability. At a cruise speed of 6 kn, the longitudinal drag is recorded at only 725.06 N, significantly lower than that in manipulating mode, demonstrating superior low-drag characteristics. In manipulating mode, the central buoyancy module is raised by 270 mm, increasing the vertical distance between the center of gravity and the center of buoyancy by 0.054 m. As a result, the maximum restoring moment increases by 202.1% compared to cruising mode, significantly enhancing operational stability. The heeling self-recovery time is reduced from 180 s to 60 s, alongside improved anti-disturbance capabilities. Furthermore, the dual-arm workspace effectively covers the lateral, forward, and downward regions of the vehicle, ensuring an efficient and collaborative operational envelope.

By utilizing autonomous configuration switching, an overall design scheme for a morphable underwater intervention robot with multi-task execution capability was proposed. This design effectively combines low-resistance detection in cruising mode with high-stability operation in manipulating mode, offering an innovative solution for underwater operations in complex deep-sea scenarios.

This study aims to develop a dynamic model of the longitudinal profile motion of wave gliders by modeling the umbilical cable as multiple hinged rigid rods, and to investigate the effects of environmental and umbilical cable parameters on the longitudinal motion characteristics.

Based on reasonable assumptions and simplifications, the umbilical cable was modeled as a series of homogeneous, multi-segment rigid rods connected by hinges. The Lagrangian method was employed to construct a multi-rigid-body dynamic model of the wave glider in the longitudinal profile. Incorporating calculation methods for wave force, fluid resistance, and hydrofoil external forces, a simulation program was developed on the MATLAB/Simulink platform to solve the model. The model's validity was verified by comparing its results with those of existing studies. Finally, a sensitivity analysis was conducted to examine the influence of environmental and umbilical cable parameters on the system response.

The results indicate that the longitudinal motion response increases with wave height; specifically, when the wave height rises from 0.2 m to 0.4 m, the longitudinal response increases by 78.20%. Under a current disturbance of 0.07 m/s, the longitudinal displacement within 60 s in the downstream condition increases from 1.53 m to 9.11 m compared with the upstream condition. Shorter umbilical cables amplify the longitudinal motion response; when the umbilical cable length decreases from 5 m to 2 m, the longitudinal response increases by 31.97%. Conversely, excessively small wave periods reduce the longitudinal response due to rigid impacts between the multi-segment hinged rigid rods. Changes in umbilical cable density, however, exert only a minor influence on the longitudinal motion response.

The findings of this study provide theoretical support for the structural optimization and motion control strategies of wave gliders.

Deep-sea pressure hulls are at risk of implosion when subjected to extreme hydrostatic pressures that exceed their ultimate bearing capacities. Therefore, it is essential to investigate the failure mechanisms and shock response characteristics of titanium alloy cylindrical shells under implosion conditions.

First, an independent deep-sea implosion experimental platform was developed, and underwater experiments were conducted on the titanium alloy cylindrical shell in a deep-sea high-pressure environment. A compressible multiphase flow module was then developed to simulate the high-speed motion of the flow field during the underwater implosion. The explicit nonlinear finite element method was employed to analyze the dynamic response associated with the collapse and failure of the titanium alloy cylindrical shell. Finally, the characteristics of the titanium alloy cylindrical shell implosion were investigated, focusing on the fluid-structure interaction mechanism, the evolution of asymmetric shock waves in the multiphase medium, the nonlinear dynamic response of the structure, and the energy balance relationships.

The results showed that the titanium alloy cylindrical shell, with a length-to-diameter ratio of 2, collapsed in the first-order instability mode, and the implosion center formed twice successively. As hydrostatic pressure increased, a pronounced migration effect of the first implosion center was observed. Meanwhile, the failure mechanism of the shell transitioned progressively from inward extrusion to inward curling, and the rupture morphology evolved from an arcuate shape to an M-shaped configuration.

This study reveals the failure mechanism and shock response characteristics of the titanium alloy cylindrical shell implosion, providing valuable insights for the implosion assessment and protection of deep-sea pressure hulls.

To address frequent actuator failures caused by complex underwater environments and the inherent characteristics of unmanned underwater vehicles (UUVs), this study investigates a prescribed performance path-following fault-tolerant control scheme for an underactuated UUV subject to ocean current disturbances, model uncertainties, and actuator faults. To ensure safe UUV navigation, a path-following fault-tolerant controller is designed by integrating an improved prescribed performance function with a barrier Lyapunov function, enabling full-state-constrained fault-tolerant control.

A novel predefined-time disturbance observer is developed to estimate the lumped disturbances arising in UUV path-following, including ocean currents, parameter perturbations, unmodeled dynamics, and thrust loss caused by actuator faults. The lumped uncertainties with actuator faults are incorporated into the prescribed performance fault-tolerant controller for compensation, ensuring that all path-following state errors remain within predefined bounds.

Simulation results demonstrate that the position error, attitude angle error, and angular velocity error converge rapidly while strictly satisfying the prescribed safety constraints, achieving a steady-state position error bound of 1 meter and an attitude angle error bound of 0.05 radians. When the actuators suffer up to 80% thrust loss, the disturbance observer rapidly estimates the lumped disturbances, and the controller compensates for the faults within 1 second without significant path-following deviation. The maximum transient error does not exceed 20% of the prescribed limit. These findings validate the strong robustness of the proposed method against actuator faults. By unifying disturbance observation with prescribed performance constraints, the fault-tolerant control structure is simplified, achieving both fast fault response and full-state safety guarantees.

This work provides a universal solution for high-performance UUV navigation in complex underwater environments.

The underwater dynamic navigation based on the sectional observation system generates multi-source and heterogeneous data, creating crossed or forked tracks due to asynchronous time delay and unknown system errors. This makes it difficult to represent continuous navigation processes and identify local characteristic points. To address this issue, a functional reconstruction algorithm for underwater data fusion is proposed.

The polynomial constraint fusion (PCF) method and the spline function fusion (SFF) method are employed to process track data collected via sectional observations. These methods effectively integrate the full underwater track and address issues such as discontinuous dynamic parameter sequences and ambiguous data in overlapping section.

Numerical simulations show that both PCF and SFF methods can capture the main characteristics of underwater dynamic motion and produce accurate and continuous tracks. Compared with the general data fusion (GDF) method, the PCF and SFF yield smoother and more continuous data series, enabling a more precise representation of motion in overlapping regions. Compared with the moving average filter algorithm, the fusion processing results based on the functional reconstruction algorithm and the filter algorithm both show an optimizing performance in accuracy and smoothness. In terms of velocity and acceleration consistency, the functional reconstruction algorithm is better than the filter algorithm. Verified by sea trials, the SFF and the PCF were used to obtain the re-analysis track in the observed section with velocity estimation errors within 5% at the characteristic points, and also obtain the predicted track in subsequent sections with errors within 15%.

The proposed method shows application values for processing multi-source and heterogeneous data in complex underwater motion scenarios, and is also effective for the short-term underwater navigation estimation.

To address the challenges posed by high-intensity noise and the structural characteristics of large obstacle targets in underwater sonar imaging, as well as the stringent requirements for lightweight deployment and high inference efficiency of perception algorithms in real-time underwater obstacle avoidance tasks, a semantic segmentation algorithm for sonar images with low computational cost and short inference time is proposed. The method aims to resolve the trade-off between the computational complexity of perception algorithms and the real-time response requirements in obstacle avoidance applications.

Based on an encoder-decoder network architecture, lightweight convolution operations were introduced to significantly reduce computational complexity. In addition, a large-kernel separable attention mechanism was incorporated into the skip connections to enhance feature fusion for obstacle avoidance scenarios. A dataset of 6936 sonar images collected and manually annotated from real environments was used for training and comparative experiments. Furthermore, the obstacle avoidance strategy based on the proposed perception algorithm was validated on the Gazebo simulation platform.

The improved algorithm specifically enhances the segmentation accuracy of large targets. Compared with the baseline model, the FLOP and the number of parameters are reduced by 69.2% and 83%, respectively. At the same time, the inference time is shortened by 22.6%, while perception accuracy improves by 10.8%. In addition, simulation experiments verify the effectiveness of the perception algorithm during the obstacle avoidance process, demonstrating that it fully satisfies the requirements of real-time perception tasks in underwater obstacle avoidance scenarios based on forward-looking sonar.

The proposed sonar-image-based perception algorithm can effectively meet the obstacle avoidance requirements of unmanned underwater vehicles in onboard operating scenarios and shows promising potential for engineering applications.

This paper investigates the high-precision control challenges associated with the autonomous recovery of an autonomous underwater vehicle (AUV) by a dynamically moving docking base. During the docking process, the recovery performance is significantly affected by complex underwater environments, including time-varying external ocean currents and inherent model uncertainties. To address these challenges, this study aims to propose a robust double-loop control strategy designed to achieve rapid, stable, and precise pose alignment between the AUV and the moving docking base under constrained conditions.

Using the "White Dolphi 100" docking system as the primary research platform, a 5-DOF motion model is established to formulate the dynamic docking problem. The proposed control architecture consists of an outer kinematic loop for pose error regulation and an inner dynamic loop for velocity tracking, utilizing an adaptive fast nonsingular integral terminal sliding mode control (AFNITSMC) strategy. Specifically, a fast nonsingular integral terminal sliding mode surface is designed to ensure finite-time convergence of the system states while effectively eliminating the singularity issues inherent in conventional terminal sliding mode control methods. To enhance robustness, an adaptive lumped disturbance estimation law is incorporated to online estimate and compensate for uncertainties—such as model parameter mismatches and time-varying ocean currents—without requiring any prior knowledge of the disturbance upper bounds. Furthermore, a boundary layer technique is introduced into the switching term of the control law to mitigate the chattering phenomenon, thereby protecting the mechanical actuators. The stability and finite-time convergence of the overall closed-loop system are rigorously established using the Lyapunov stability theory.

Extensive simulation studies were conducted using the hydrodynamic parameters of the "White Dolphin 100" docking system to validate the effectiveness of the proposed control method. The simulation scenarios accounted for 20% thrust saturation limits, time-varying ocean current disturbances, and 20% perturbations in model parameters. The results indicate that the AFNITSMC method achieves rapid pose convergence within 10 seconds, with specific convergence times of 4.6, 7.0 and 9.39 s in the longitudinal, lateral, and vertical directions, respectively. This performance significantly surpasses that of the baseline nonsingular integral terminal sliding mode control (NITSMC), which required much longer intervals to stabilize. Regarding steady-state accuracy, the mean absolute errors (MAE) for position were measured at 0.142, 0.103, and 0.0397 cm, while the attitude errors were 0.012° and 0.054°. Compared to the NITSMC method, the proposed method reduced position errors by 75.7%, 87.6%, and 95.3%, and attitude errors by 96.5% and 62.2%, demonstrating its superior tracking precision and robustness.

The proposed AFNITSMC exhibits excellent control performance and promising engineering application prospects in addressing the dynamic base docking problem under external disturbances and model uncertainties.

This study investigates the motion characteristics of deep-sea vehicles during deep vertical transit under vectored propulsion.

First, the motion equations were established to obtain preliminary solutions for the parameters of helical diving. Subsequently, a series of lake trials were conducted using a vectored-propulsion deep-sea vehicle prototype, including steady-state turning diameter tests, heeling angle measurements, and powered helical diving experiments under multiple control parameters, in order to analyze the diving motion characteristics. Finally, a 3 650 m powered diving test was performed under real operating conditions at a depth of 3 700 m in the South China Sea.

The lake trial results show that the steady turning diameter of the vector-propelled deep-sea vehicle is only 4 times the overall length of the platform, while the turning heel angle remains within 2.5°. The sea trial results indicate that, under the selected control parameters, the average deep-sea diving speed reaches 0.6 m/s, the standard deviation of the pitch angle is only 0.42°, and the horizontal offset during the 3 650 m diving process is 442 m. These results demonstrate stable and controllable motion characteristics, verifying the feasibility of the powered diving technology for deep-sea vehicles based on vectored propulsion.

The results provide a reference for the research on diving technologies for deep-sea vehicles.

With the increasing diversification of application requirements for unmanned underwater vehicles (UUVs), traditional design methods centered on text-based documentation have revealed numerous limitations in practice, such as scattered design documents, difficulty in maintenance, and low iteration efficiency among systems. Therefore, it is necessary to introduce a novel overall design methodology.

In this study, the model-based systems engineering (MBSE) methodology was incorporated into the design process of UUVs and integrated with traditional design approaches to establish a model-driven design and verification framework. Using the M-Design collaborative research platform, graphical system modeling language (SysML) was employed to construct a comprehensive system model, including the requirements model, logical architecture model, and physical architecture model, thereby forming an integrated design framework. To further validate the feasibility of the framework, multi-system co-simulation technology was adopted, and a distributed simulation platform was developed to perform performance simulation and verification for typical mission scenarios of UUVs. Based on these efforts, a conceptual scheme for an agile design and verification prototype system has been proposed to support agile development requirements.

The results demonstrate that the model-based design methodology can significantly improve the design efficiency and verification capability of UUVs, enabling a closed-loop development process from requirements definition to design implementation.

The proposed design methodology provides effective guidance for the design and specification verification of various manned and unmanned underwater platforms.

To improve the overall operational capability of autonomous underwater vehicles (AUVs) and address the critical issue of collision risks during the dynamic docking process with towed recovery docks (TRDs), this study conducts a systematic investigation into the collision mechanisms and control strategies of the docking system. Reliable docking and recovery technology is essential for extending AUV operational endurance, enhancing data transmission efficiency, and enabling long-term underwater deployment. However, in real marine environments, limitations in sensor accuracy, external disturbances, and the dynamic response of the docking system often lead to unavoidable contact or collision between AUVs and TRDs, which may result in mission failure or structural damage to the equipment. Therefore, this study aims to clarify the influence of key initial operating conditions on docking-induced collisions and to propose an effective control strategy for optimizing the dynamic docking process, thereby providing theoretical and technical support for the engineering application of AUV towed recovery systems.

Based on dynamic analysis, a simulation model incorporating contact and collision dynamics was developed using the ADAMS-MATLAB co-simulation platform. First, rigid body dynamic models of AUV and TRD were constructed. The AUV model accounts for gravity, buoyancy, viscous hydrodynamic drag, inertial hydrodynamic drag, thrust, and environmental disturbances. The TRD model adopts a frame-cage structure with a bell-mouth guiding cover, and a discrete flexible body method is used to model the towing cable. Subsequently, a nonlinear contact model based on Hertz theory was employed to calculate the collision forces between AUV and TRD, which more accurately captures the transient impact characteristics of the collision process compared with the linear contact model. On this basis, the effects of initial operating conditions including eccentric angle, eccentric distance, relative initial velocity, and mother vessel acceleration on docking collisions were systematically analyzed using the control variable method. To mitigate attitude disturbances induced by collisions, a multi-stage coordinated control strategy based on PID control was proposed, which realizes active attitude adjustment of AUV by switching control modes across different docking phases.

The simulation results indicate that increases in eccentric angle and eccentric distance primarily prolong the docking time while exerting only a limited influence on the peak collision force, which remains within the range of 1 000–2 000 N under most working conditions. In contrast, increasing the relative initial velocity can shorten the docking time but significantly amplifies the peak collision force, showing a positive correlation between them. Further analysis of mother vessel acceleration reveals the complex, non-monotonic relationship between collision force and docking efficiency. As the mother vessel's acceleration increases, the amplitude of the TRD attitude variations intensifies, leading to greater uncertainty in the collision position, and the peak collision force reaches its maximum value when the acceleration is 0.2 m/s². Moreover, the proposed multi-stage coordinated control strategy enables effective post-collision attitude adjustment of the AUV. In the case of uniform motion of the mother vessel, the strategy reduces the peak collision force by up to 74.5% and shortens the docking time from 7.56 s to 5.93 s. Even under the complex working condition of uniform acceleration of the mother vessel, the peak collision force is reduced by 19.6%, and the docking time is shortened by 16.7%, effectively optimizing the dynamic docking process and ensuring both docking safety and efficiency.

This study systematically clarifies the effects of key initial operating conditions on the docking collision between AUV and TRD. The research findings indicate that controlling the initial eccentric angle and eccentric distance can improve docking efficiency, whereas adjustments to the relative initial velocity and mother vessel acceleration require a careful balance between collision risk and docking speed. The proposed multi-stage coordinated control strategy can significantly reduce the peak collision force while maintaining docking efficiency, achieving reductions of 14%–74.5% under different working conditions. This strategy exhibits superior robustness and stability compared with the traditional position tracking control strategy, effectively addressing the limitations of passive control methods that rely solely on the dock structure. Overall, this study provides a reliable simulation basis and design reference for the design and stability control of AUV towed recovery systems. In addition, the research framework and methods provide guidance for the collision analysis and control in similar underwater docking systems.

To suppress hydrodynamic noise at the source, a noise reduction method for pump-jet propulsors based on porous media is proposed.

By replacing the metallic leading edges of the stator blades of the pump-jet propulsor with porous materials, the interaction between the blade wake and the inner wall of the duct can be effectively modulated, thereby reducing wall pressure fluctuations. Large eddy simulation (LES), combined with acoustic analogy analysis, was employed to investigate the flow characteristics and noise control performance of the stator blades with porous leading edges. The mechanisms by which the porous media modulates the flow field and suppresses noise were analyzed, and the effects of key parameters, such as porosity and advance coefficient, on hydrodynamic noise control were examined.

Comparative results indicate that the porous leading edges of the stator significantly reduce the low-frequency sound pressure level components on the duct wall and the far-field radiation noise. The maximum reduction in the sound pressure level (SPL) reaches 5.52 dB in the direction perpendicular to the rotation axis of the pump-jet propulsor.

The findings of this study provide useful guidance for flow control and hydrodynamic noise reduction in pump-jet propulsors.

This study aims to systematically quantify the effects of fin-hull geometric configuration on the propulsion performance of bionic undulating-fin vehicles employing media and/or paired fin propulsion (MPF). It addresses the lack of a unified analysis of geometric parameters across different bionic underwater vehicles in existing research.

To this end, a universal parametric geometric model incorporating the hull and a pair of undulating fins was developed. The model innovatively introduces the ratio of fin width to hull width β as the core dimensionless geometric parameter. Based on this model, high-fidelity CFD numerical simulations were conducted to analyze the propulsion performance and flow field structure of the vehicle under different β values.

The results indicate that β has a nonlinear and significant influence on propulsion performance, and that an optimal range of β values exists for maximizing propulsion efficiency. Excessively small β values lead to insufficient thrust generation, whereas excessively large β values increase drag due to intensified fin-hull interactions that induce flow separation. Furthermore, β significantly modulates the magnitude of the pitching moment, imposing a critical constraint on the vehicle's attitude stability.

This study clarifies the design trade-off between efficiency and stability governed by the β parameter. The established parametric model and the identified underlying mechanisms provide a quantitative theoretical basis for the shape design of bionic underwater vehicles and lay a solid foundation for future research on multi-parameter coupling optimization and self-propulsion performance.

To overcome the limitations of conventional wave-absorbing structures, a novel broadband, low-profile multilayer composite absorber was designed.

The proposed design integrates square loop resistive film units to significantly broaden the operational bandwidth and incorporates miniaturized conductor units based on lumped inductance loading. Structural parameters were further optimized to achieve broadband, low-profile wave-absorption, effectively lowering the minimum operational frequency.

Simulation results show that the developed composite absorber achieves over 90% electromagnetic wave absorption across the frequency range of 3.22 to 14.63 GHz, with a relative bandwidth of 127.8% and a low profile height of just 0.068λ_L.

The operational mechanism of the absorber is analyzed using an equivalent circuit model, and potential improvements are discussed. This design offers valuable insights and a solid reference for the development of broadband, low-profile absorbers. Future work will focus on replacing lumped inductors with metal meander-line structures to reduce processing complexity and costs.

To accurately evaluate the impact of blanking on pulse interception, this study examines the loss probabilities of pulses caused by the blanking.

The influence of blanking on pulse sorting was analyzed. Based on the pulse sorting method used by reconnaissance equipment, the criteria for identifying the loss pulses were established. The output waveform of a pulse erased by the blanking gate was then examined under various time-sequence relationships between the pulse and the blanking gate, allowing the varying law of the residual pulse to be obtained. The expressions were derived for the average loss probabilities of the pulses and the loss probabilities of the periodic pulses both caused by the periodic blanking gates, as well as for the average loss probabilities of the pulses under blanking gates with time-varying duty cycles. Finally, each pulse loss probability was validated by comparing the calculation results with numerical simulation. The maximum absolute deviation between the two was approximately 5.8×10⁻⁴, which is negligible.

The mathematical models for the pulse loss probabilities and the average loss probabilities are obtained, and their accuracy has been verified.

The research provides a quantitative evaluation of the influence of the blanking on the loss of the intercepted pulse. It provides the input for accurately analyzing the missed alarm probability in pulse interception with the blanking gate and supports decision-making regarding the use of blanking measures.

To address the defect that the empirical formula of sea-spray flux depends on observation data from specific ships, this study proposes a correction method for the empirical formula of sea-spray flux on polar ship decks.

By analyzing the parameter characteristics of the empirical formula, it is proposed to modify the empirical formula of sea spray flux using numerical solutions of sea-spray flux for different ship types and corresponding environmental conditions as inputs. The reliability of the numerical method is verified through numerical wave profile and MFV fishing vessel spray flux calculations. Based on the proposed method, the empirical formulas of sea spray flux for four different ship types, such as bulbous bow, ice-resistant bow, clipper bow and raked bow, are modified.

The theoretical and numerical solutions of the empirical formula for fishing vessel spray flux are in good agreement. The spray duration coefficients for the other four ship types are similar to each other, and the liquid water content coefficient is similar to the coefficient in the existing empirical formula.

The results show that the proposed method has the ability to correct the empirical formula of sea-spray flux for different ship types.

To explore the effect of structural elasticity on the ice-structure interaction process, model tests on the interaction between frozen ice and elastic plates were conducted in a low-temperature laboratory. This study aims to provide a theoretical basis for understanding the ice-structure interaction mechanism and predicting ice loads on ships operating in ice-covered areas.

In the experiments, the stiffness of the elastic plates was adjusted by varying their thickness. Two loading rates within the strain-rate range associated with brittle ice failure were selected. A universal testing machine was used to record load-time history data, and a CCD camera was employed to capture the ice failure modes under different test conditions.

The interaction process consists of two typical phases: the loose contact phase and the tight contact phase. Loose contact results from the uneven contact between the plate and the top of the ice specimen, with maximum displacements generally ranging from 0 to 1.5 mm. In the tight contact phase, about 43.3% of the load-displacement curves show a saw-tooth shape, representing multi-stage failure modes. Stiffer plates are more likely to cause single-stage ice failure, while more flexible plates tend to result in multi-stage failures. Multi-stage failures are associated with ice flaking at a 45° angle due to shear failure. During multi-stage failure, the slope of the load-displacement curve remains nearly constant, suggesting constant stiffness of the ice-elastic plate coupling system in the tight contact phase.

Although the structure in this study is simplified as a plate, the experimental results provide valuable insights for designers of ice-going ships into the complex interaction mechanics between ice and ship structures. This research also provides a foundation for further studies on more complex structures and accurate ice load predictions.

As global warming accelerates the melting of sea ice, the Arctic region witnesses an increase in ship navigation. The brash ice area, composed of brash ice of various sizes and shapes, is a common operational scenario for polar ships. Understanding the ice load characteristics of polar ships during oblique navigation in brash ice regions is crucial. This can enhance ship navigation safety in the complex polar marine environment, provide a reference for polar navigation route planning, and fill the gap in the current research that mainly focuses on straight-sailing conditions.

This study selects a specific type of polar ship as the research object and utilizes the discrete element method (DEM) to predict the ice loads on the ship during oblique navigation through brash ice regions. First, a numerical model of the target ship is established. The model parameters include a ship model with a scale ratio of 60, a total length of 2.04 m, a beam of 0.37 m, and a design draft of 0.13 m. The ice particles have a density of 917.0 kg/m³, a Poisson's ratio of 0.3, and other specific properties. The accuracy of the model is verified by comparing it with the experimental results from the literature under the straight-sailing condition. Then, different oblique-sailing angles (0° −15°), speeds (0.6, 0.7 m/s), and ice thicknesses (0.011 67, 0.014 97 m) are set. The ice-load calculation is carried out based on the momentum conservation equation, angular momentum conservation equation, and the linear spring contact force model in the DEM.

The results show that as the drift angle increases, the ice-breaking resistance and lateral force on the ship increase non-linearly. For example, at a speed of 0.6 m/s, an ice concentration of 70%, and an ice thickness of 0.014 97 m, when the drift angle is 15°, the ice-breaking resistance and lateral force increase by 4.25 times and 6.04 times respectively, compared to the straight-sailing condition. In terms of speed, when the drift angle is between 0° and 10°, the ice-breaking resistance increases slowly, but when it exceeds 10°, it increases significantly. The lateral force also increases non-linearly, and the influence of speed on the lateral force is more significant than whether the ship is on the ice-facing side. Regarding the influence of ice thickness, when the drift angle is greater than 10°, the ice-breaking resistance and lateral force increase significantly as the ice thickness increases.

In conclusion, this research provides reliable data support for the safety assessment of ships during oblique navigation in polar brash ice regions. It offers a valuable reference for predicting and studying ice loads on polar ships under such conditions. Ship operators should be cautious when increasing speed or entering thicker ice areas, especially when the drift angle is greater than 10°. This is to avoid potential risks caused by sudden changes in ice-breaking resistance and lateral force, ensuring the safe and stable navigation of polar ships in complex ice-covered waters.

To address the challenge of low fault diagnosis accuracy in traditional neural networks with few labeled samples, a method based on contrastive learning and convolution transformer network is proposed.

First, raw monitoring data are transformed into similar sample pairs by data augmentation. These similar sample pairs are then mapped to a deep feature space by a feature extractor. A transformer network is utilized to design cross-prediction tasks for both local and global comparisons, facilitating the clustering of data with the same fault type by comparing the intrinsic similarity between the same batches of data. Finally, the downstream classification network is trained with few labeled samples to improve the diagnostic performance of the proposed model.

The effectiveness of the proposed method is validated using a self-built reducer test rig. The results show that accuracy of the proposed method reaches 98.38% with few labeled samples, showing significant advantages over existing methods.

The research results can provide the key technology for fault diagnosis of industrial equipment with few labeled samples, contributing to the advancement of intelligent manufacturing.

This paper addresses the path tracking control problem for underactuated unmanned surface vehicles (USVs) under the conditions of lumped disturbances, input saturation, and limited onboard energy. These factors complicate the path tracking process and reduce the effectiveness of traditional control methods. The aim of this study is to propose an event-triggered fixed-time path tracking control strategy that improves robustness, energy efficiency, and tracking precision in complex environments.

The proposed control strategy integrates several key components to address the challenges mentioned. First, a longitudinal speed guidance law and a fixed-time line-of-sight (SGFTLOS) guidance law are designed to provide the desired longitudinal speed and heading angle for the USV, ensuring it follows the trajectory with optimal speed and heading. Next, to handle model uncertainties and external disturbances (such as wind and current), a Fixed-Time Extended State Observer (FESO) is introduced. The FESO estimates and compensates for lumped disturbances, improving the system's robustness in uncertain environments. To address input saturation, an auxiliary dynamic system is designed to smooth inputs and maintain stable path tracking, even when saturation occurs. Finally, to overcome onboard energy limitations, a periodic event-triggered mechanism based on relative threshold is proposed. This mechanism adjusts control signal update frequency based on system states, minimizing unnecessary actuator activity and energy consumption.

The stability of the system is proven to be fixed-time stable using Lyapunov's fixed-time stability theory, which also eliminates Zeno behavior (infinite triggering in finite time) that could otherwise cause instability. SimuNPS simulation results demonstrate that the tracking error converges within a fixed time, verifying the effectiveness of the proposed method. Compared to existing methods, the proposed strategy exhibits faster transient response, smaller steady-state errors, and superior robustness in the presence of lumped disturbances. Furthermore, the introduction of the FESO provides accurate real-time disturbance estimation, allowing the controller to compensate for disturbances and maintain precise path tracking. Additionally, the event-triggered mechanism significantly reduces the number of control signal updates and actuator actions, improving the system's energy efficiency.

The proposed event-triggered fixed-time path tracking control strategy effectively addresses the challenges of lumped disturbances, input saturation, and limited onboard energy in underactuated USVs. By integrating event-triggered mechanisms, innovative guidance laws, and robust disturbance compensation, the strategy provides a reliable solution for path tracking in complex and uncertain environments. The fixed-time convergence property ensures that the USV achieves desired performance within a fixed time, making the strategy suitable for real-time applications requiring stability, precision, and energy efficiency. This method offers a robust, efficient, and reliable solution for USV path tracking control under difficult operational conditions.

To address the problem of inadequate path-following accuracy and stability in unmanned surface vehicles (USVs) operating in complex environments (characterized by uncertainties such as fluctuating wind speeds and initial position deviations), a guidance method called time-varying sideslip compensated adaptive line-of-sight (TSC-ALOS) is proposed.

First, a time-varying sideslip compensation mechanism is introduced based on real-time measurements of wind speed and direction, which forms the foundation of the improved TSC-ALOS algorithm. This mechanism dynamically compensates for sideslip angle variations induced by environmental disturbances, thereby optimizing the desired heading output of the USV. Subsequently, a proportional-derivative (PD)-based heading controller is designed. This controller translates the desired heading generated by the TSC-ALOS algorithm into actual rudder angle commands, enabling the USV to rapidly and stably track the target heading. This also establishes an effective connection between high-level navigation strategies and low-level control execution. Finally, numerical simulations emulating real marine environments are conducted. The performance of TSC-ALOS algorithm is compared with that of adaptive LOS (ALOS) and traditional LOS algorithms under three operational conditions: no wind, steady wind, and variable wind. Key metrics such as cross-track error and heading stability are specifically analyzed.

Simulation results demonstrate that under no-wind conditions, both TSC-ALOS and ALOS algorithms achieve higher path-following accuracy than traditional LOS algorithm, particularly in handling turning segments. Under steady wind (wind speed: 8.37 m/s) and variable wind (wind speed: 16.73 m/s) conditions, TSC-ALOS significantly reduces the cross-track error, showcasing stronger resilience to environmental disturbances. In scenarios with initial position deviations, the average cross-track error of TSC-ALOS is reduced by 24.6% and 36.8% compared to ALOS and LOS algorithms, respectively.

The TSC-ALOS algorithm demonstrates superior guidance performance across various complex environments, with particularly notable advantages in addressing environmental disturbances and initial position deviations. It offers essential technical support for the development of autonomous navigation systems for USVs and provides insights into future research directions for algorithm optimization.

To address the challenges of preventing non-random multiple concurrent faults caused by cable aging in shipboard power grids through preventive reconfiguration, and to resolve the issue of unreasonable weight coefficient settings in multi-objective reconfiguration models, thereby enhancing the safety and reconfiguration efficiency of shipboard power grids, a predictive fault reconfiguration method for shipboard power grids based on a double-level optimization strategy is proposed.

A cable aging fault prediction model for shipboard grids was constructed based on Markov chains and thermo-electro-mechanical multi physics analysis. This model was integrated as a constraint into the reconfiguration framework to avoid high-risk branches. A dual-layer optimization strategy was proposed: the upper layer dynamically solves multi-objective weight coefficients using the whale migration algorithm (WMA), while the lower layer determines the optimal switch configuration for grid reconfiguration using a multi-strategy-improved dung beetle optimizer (MSDBO).

After integrating the fault prediction model, the reconfiguration strategy achieved 100% avoidance of high-risk branches (fault probability ≥0.5) proactively. Compared to the conventional two-step passive reconfiguration strategy, convergence speed improved by 47.06%. The dual-layer optimization framework enabled adaptive dynamic adjustment of weight coefficients and increased reconfiguration convergence speed by 56.25%.

The integration of the cable aging fault prediction model and the dual-layer optimization framework effectively enables predictive reconfiguration of shipboard power grids. This approach proactively mitigates non-random faults while significantly improving reconfiguration efficiency and rationality. It offers a novel solution for addressing predictive reconfiguration challenges in non-random multiple-fault scenarios.

This paper introduces a novel data-driven approach for generating realistic and hazardous overtaking scenarios. These scenarios are crucial for rigorously evaluating the autonomous collision avoidance capabilities of autonomous ships. Existing methods often struggle to balance scenario diversity, realism, and the representation of hazardous situations. To overcome this limitation, our method leverages the rich information embedded in automatic identification system (AIS) data to generate diverse and realistic overtaking encounters.

Specifically, we propose a hybrid model that integrates a sequence generative adversarial network (SeqGAN) with a self-attention mechanism (SAM). The SeqGAN captures the complex patterns and dynamics in AIS-based ship trajectories, enabling the generation of novel, yet plausible, overtaking maneuvers. The incorporation of a SAM further enhances the model's ability to capture long-range dependencies in ship trajectories, resulting in more realistic and nuanced simulations. To ensure that the generated scenarios accurately reflect hazardous situations, we have developed a constraint model based on longitudinal and lateral safety distances between vessels to define realistic initial conditions. This model dynamically adjusts the initial positions and velocities of both the target vessel and the autonomous ship under test, ensuring that each generated scenario presents a genuine collision risk.

The results show that the effectiveness of our approach is validated through extensive simulations. A total of 500 hazardous overtaking scenarios were generated, significantly improving the coverage of test scenarios. Notably, 97.3% of these generated trajectories fall within a predefined buffer zone that encompasses real-world trajectories, demonstrating the high fidelity of our model. Furthermore, the speed distributions of the generated target vessels closely match those observed in real-world AIS data, further validating the realism of our approach.

The enhanced realism and diversity of scenarios generated by this method significantly improve the efficiency of autonomous collision avoidance testing. This allows for a more precise definition of safety performance boundaries and accelerates the development and optimization of autonomous collision avoidance algorithms. Ultimately, this work contributes to the development of safer and more reliable autonomous maritime systems capable of navigating the complexities of modern maritime environments.

This research focuses on the energy characteristics of false targets generated by time-modulated adaptive jamming technology, aiming to investigate the significant variations in these characteristics caused by different modulation schemes and parameter settings. It aims to provide a comprehensive understanding of how modulation parameters influence the energy distribution of false targets, thereby offering practical insights for electronic warfare applications.

First, theoretical interference models were established for different modulation schemes against linear frequency modulation (LFM) pulse radar. These models elucidate the mapping relationship between modulation timing and the amplitude of false targets. Second, a Ku-band jamming system was designed and built to experimentally validate the theoretical findings. The system incorporates 1-bit modulation and control modules to generate time-modulated signals. Numerical simulations were conducted to evaluate the energy characteristics of false targets under various duty cycles and modulation schemes. Additionally, experimental measurements were performed in a controlled environment to compare the performance of various modulation modules and to verify the accuracy of the simulation results.

The results demonstrate that 1-bit modulation effectively conceals the target's energy at the fundamental frequency, making it difficult for radar systems to detect the true target. Under a fixed modulation scheme, it was observed that decreasing the duty cycle of the modulation signal reduces the amplitude difference between each harmonic and the fundamental frequency. When the harmonics approach the fundamental frequency in amplitude, the radar's ability to distinguish between true and false targets is significantly compromised. This finding highlights the importance of optimizing the duty cycle to enhance the effectiveness of time-modulated adaptive jamming. The experimental results closely matched the numerical simulations, validating both the theoretical models and the effectiveness of the proposed jamming system.

By employing 1-bit modulation and carefully adjusting the duty cycle of the modulation signal, it is possible to effectively shape the energy profile of the real target, thus improving the jamming effectiveness against modern radar systems. This research provides both qualitative and quantitative analysis of the energy characteristics of false targets, and offers practical guidance for the development and implementation of time-modulated adaptive jamming systems. Future work may focus on extending this study to multi-target jamming scenarios, and on incorporating artificial intelligence algorithms to optimize jamming strategies in real time, as well as exploring countermeasures against emerging radar technologies.

Complex backgrounds, significant target size variations, and severe sea clutter in maritime infrared imagery often result in missed or false detections. To address this challenge, an improved method based on YOLOv8n, termed maritime infrared target detection-YOLO (MITD-YOLO), is proposed to enhance target detection accuracy in maritime infrared images.

MITD-YOLO incorporates a diverse branch module (DBB) and enhanced multi-scale convolution (EMSConv) to leverage multi-scale convolutions, enabling the model to more effectively capture complex features. A triple attention mechanism is employed to facilitate spatial and channel-wise feature interaction, thereby improving key feature extraction. Additionally, the powerful-IoUv2 (PIoUv2) loss function is introduced to address the anchor box expansion problem, leading to improved detection accuracy and enhanced model robustness.

Experimental results show that the improved model significantly enhances the efficiency of maritime infrared target detection, with a 2.3% increase in precision and a 1.7% increase in recall. The model achieves an average precision of 88.9%, and 132.8 FPS, outperforming the original model.

MITD-YOLO enhances maritime infrared target detection performance and provides a more reliable target detection technology for applications such as maritime surveillance and ship navigation, contributing to the advancement of intelligent maritime systems.

The information obtained through forced detection is often inaccurate, and targets frequently change course unpredictably. This degrades the performance of target maneuver detection and hampers the analysis of the target motion pattern. Therefore, this paper proposes a detection method for maneuvering maritime targets based on prior knowledge.

The method incorporates two types of prior knowledge derived from expert experience. The first is that significant differences in target heading occur before and after maneuvering, whereas the target heading remains relatively stable during non-maneuvering periods. The second is that the heading difference before and after maneuvering reaches a local extremum. The maneuvering point in the trajectory tends to maximize the heading difference between adjacent sub-trajectories. Based on the definition of trajectory smoothness metric, a calculation method is proposed to calculate the course maneuver evaluation factor based on principal component analysis (PCA). This factor enables preliminary screening of potential maneuvering points. In order to find trajectory points that satisfy the second prior knowledge, a maximum filtering-based maneuvering point screening method is proposed.

Simulation results show that, compared with the mainstream interactive multiple model (IMM) algorithm and information entropy-based algorithm, the target maneuver inflection points detected by the proposed method are closer to the actual inflection points, with the lowest false detection rate and missed detection rate. Moreover, when track compression is performed using the maneuver positions extracted by this method, the distance error relative to the original track is minimized.

The findings confirm the superiority of the proposed algorithm, which can effectively improve the accuracy and robustness of target maneuver detection and provide strong support for target behavior analysis and operational decision-making at sea.