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.

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 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.

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.

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.

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.

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 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.

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.