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.