Scouring around vertical piles in ocean environments, especially under wave action, can significantly affect the stability of structures. Therefore, accurately predicting scour depth is essential for proper pile design. While empirical methods are commonly used, they often lack the accuracy required to model such complex processes, whereas data mining techniques provide more reliable predictions. This study evaluates the predictive performance of a morphological model for caisson breakwaters supported by piles under clear-water conditions, using the Flow-3D HYDRO mathematical modeling tool, addressing a gap in its application. In this study, a series of three-dimensional numerical models were developed to investigate the mechanisms of local scour around semi-immersed caisson breakwaters supported by piles. The investigation focused on key parameters such as the spacing between the piles and the gradual increase in the draft of the caisson barrier, subjected to different wave actions. The Reynolds-averaged Navier-Stokes (RANS) equations, along with the renormalization group (RNG) turbulence model and the Van Rijn sediment transport model, were used to simulate the morphological changes around the caisson breakwater. A numerical contour map was generated to assess the scour topography and sediment deposition beneath the breakwater and around the piles. A three-dimensional numerical model is developed to investigate modifying the caisson’s cross section for different two scenarios on controlling the scour progress around a semi-immersed caisson suspended on piles under wave action. The simulation results were compared to previous experimental data, showing a high level of agreement. The effects of pile spacing on the flow field, bed elevation contours, deposition height, scour length, and scour depth were examined in two different scenarios with varying breakwater drafts. The findings reveal that pile spacing significantly affects the flow dynamics, local scour around the piles, and beneath the breakwater. This influence leads to distinctly different patterns of scour holes and variations in scour depth under the barrier. Detailed discussions are provided on the relationships between these effects and the dimensionless wave number. The attempt to increase the overall width of the breakwater by 0.25 W successfully moved scour away from the breakwater and the piles while maintaining its constant value

To demonstrate the superiority of wake-induced vibration (WIV) in flow-induced vibration piezoelectric energy harvesting, a novel integrated dual-bluff-body piezoelectric energy harvester (PEH) was proposed in this paper. Wind tunnel experiments were conducted to investigate the impact of different cross-sectional shapes on the output performance of the device. The operational mechanism was analyzed using two-way fluid–structure interaction theory. Results show that the integrated structural design not only significantly improved the output performance of the PEH but also facilitated device miniaturization, overcoming the limitations of complex structures and challenges in miniaturization in existing technologies. Compared to vortex-induced vibration, the PEH driven by WIV achieved a 177.2% increase in maximum output voltage and a 66.7% expansion in effective operational range. Among the tested cross-sectional shapes, a circular interference column delivered the best performance under WIV, with maximum output power exceeding that of square and equilateral triangular cross-sections by 60.65% and 44.4%, respectively. Moreover, the second peak in energy conversion efficiency associated with the circular cross-section exhibited a coverage area 2.4 times larger than that of a square cross-section, enabling stable energy output across a broad range of wind speeds. These findings offer important insights into the application of FIV in piezoelectric energy harvesting and provide strong support for the advancement of self-powered technology.

The penetration performance of an underwater shaped charge jet (USCJ) under the influence of an intervening water layer was studied by combining experimental and numerical simulation methods, considering the effects of initiation manners and standoff distance. First, the USCJ formation and its penetration performance tests were carried out, which were used to verify the reliability of the numerical simulation. Then, the formation and penetration processes of the shaped charge jet were analyzed experimentally and numerically. The results showed that during the penetration of the intervening water layer, the high-speed and high-energy jet head was engulfed by the water layer. A 30 mm intervening water layer reduces the kinetic energy of USCJ by approximately 13.6% and its penetration performance by 12.8%. The depth of penetration (DOP) of the USCJ decreases with increasing water layer thickness, and its decreasing trend gradually slows down. The DOPs of USCJ under annular and surface initiation manners are greater than those under central initiation. When the annular initiation radius increases, the accumulation effect of the USCJ weakens, and the overall velocity and kinetic energy increase, resulting in a significant increase in DOP. The DOP of USCJ increases initially and then decreases with an increase in the standoff distance; however, an increase in the water layer thickness reduces the optimal standoff distance. While the water layer reduces DOP, it also has a certain effect on the standoff distance. A certain thickness of the water layer is beneficial for the improvement of the DOP when the standoff distance is small.

This study validates a set of proposed design improvement methods for inland oil tankers and passenger ships in Bangladesh’s inland waterways. Hydrodynamic performance is assessed using computational fluid dynamics (CFD) simulations. Three-dimensional models of three oil tankers and three passenger ships are created after physical investigations and measurements. These are reconfigured according to previously suggested qualitative and quantitative design recommendations. The CFD analysis results indicate very significant reductions in overall resistance for all the redesigned vessels, ranging from 5.56% to 17.27% for oil tankers and up to 16.97% for passenger ships. These reductions validate the effectiveness of the proposed design methods in improving energy efficiency. Although limitations due to operations are present with some of these recommendations, the overall performance improvements provide valuable insights for enhancing the designs of inland ships. However, to validate such computational findings and expand design processes, model testing of new designs is recommended.

A ship’s hull inherently contains initial imperfections that develop pitting corrosion over time, particularly in steel vessels. These factors directly affect and reduce the ultimate strength capacity of the ship. This study investigates the combined effects of these damage factors on the hull girder ultimate strength of double-hull oil tankers. In addition, the study investigates the residual ultimate bending strength of double-hull oil tankers under hogging and sagging conditions through a stress distribution method incorporating several modifications. Using the selected method, different levels of initial imperfections (including slight, average, and severe levels), and corrosion volume losses (ranging from 0% to 30%) are considered to represent the damage scenario. The analysis shows that the effect of initial imperfections on the residual ultimate bending strength under extreme load was negligible (approximately 8.5% at the severe level); however, when interacting with the pitting corrosion, significant reductions of up to 37.17% and 38.50% were observed in the average cases of hogging and sagging conditions, respectively. Further evaluation of the safety factors associated with the ultimate bending moment highlights the necessity of improved structural evaluation and maintenance to ensure operational dependability and safety.

A suitable quasi-zero-stiffness (QZS) vibration isolator system was developed for confined installation spaces. The system achieves close-to-zero stiffness through the parallel combination of magnetic rings and disc springs. First, the Halbach magnetization method was proposed for the positive stiffness mechanism owing to its advantages in the field of non-contact transmission. Furthermore, the negative stiffness mechanism was designed based on the nonlinear stiffness characteristics of disc springs. Next, the proposed QZS vibrator isolator was structurally optimized by focusing on the interaction between the positive and negative stiffness mechanisms. Thereafter, the effects of key structural and operating parameters on its dynamic characteristics (e.g., resonance frequency and force transmissibility (T_e)) were analyzed to validate the accuracy of the theoretical model. Finally, comparative experiments were conducted using a magnetic bearing testing platform to evaluate T_e through the QZS vibration isolator and its equivalent linear isolator under identical excitation. The results demonstrated that the QZS vibration isolator exhibited superior low-frequency vibration isolation performance. This study offered a basis for prototype manufacturing, future experimental validations, and broadening engineering implementation.

Damage to the ship can threaten its overall strength, which in turn affects the structural safety of the hull and its subsequent use. Recognizing ongoing damage immediately and effectively is crucial. This paper examines a method based on curvature modes to identify ship damage. The effectiveness of this method is investigated when the ship experiences simultaneous and successive damage. The ship is simplified as a hull girder with free boundary conditions. Six different damage cases are analyzed through numerical simulations and experiments. Results show that the curvature mode index can effectively identify two separate damages when the ship is damaged in two locations simultaneously. Additionally, when the ship is subjected to continuous attacks, the curvature mode index can accurately detect new damage without being affected by existing damage. The proposed method offers a novel approach to double damage identification in hull girders, providing valuable insights for real-time ship safety assessment.

Studying the damage effects of multi-cabin structures (MCS) subjected to underwater explosions holds immense significance for ship protection. Employing a combined experimental and numerical simulation approach, this paper comprehensively investigates the damage effects of MCS under near-field underwater explosion. Three distinct damage modes are defined. Damage results of MCS caused by a single explosive and simultaneous detonation of two explosives with equivalent total mass are analyzed. A damage factor designated F* is proposed for determining the MCS damage mode under simultaneous dual-explosive detonation. The three different damage modes of MCS are as follows: I) Plastic deformation of the outermost layer; II) Tearing failure of the outermost layer accompanied by significant deformation of the second layer; III) Tearing failure of both the outermost and second layers. Once a breach occurs in the first layer, a water jet penetrates into the cabin and strikes the second layer, causing secondary damage. Additionally, the fragments generated from the first layer colliding with the second layer are the primary factors contributing to the occurrence of Mode III. The study presents criteria for distinguishing these three damage modes based on different shock wave impact locations. When damage factor F* ≥ 1, MCS experiences damage in Mode II; whereas when F* < 1, MCS undergoes damage in Mode I. F* achieves 96.5% accuracy in damage mode prediction for MCS under 250 g-1 080 g TNT charges. When the total mass of explosives remains constant, the simultaneous explosion of two explosives exerts a more pronounced damage effect on MCS than a single explosive.

The demand for enhanced passenger comfort on cruise ships has increased, emphasizing the need to reduce excessive vibrations that affect both onboard livability and environmental noise emissions. Structural vibrations contribute significantly to underwater radiated noise, making vibration control a key challenge. This study develops a method to analyze vibration propagation and identify individual source contributions to ship responses. Proper characterization of transfer mechanisms between sources and receivers is essential for effective vibration control, minimizing negative effects, and improving onboard comfort. The approach helps pinpoint critical sources and optimize their isolation by refining hull interfaces and energy transfer paths. After reviewing existing techniques, a methodology for source contribution analysis is proposed and applied to a cruise ship with dual electric propulsion engines and propellers. The study employs insertion loss functions to experimentally quantify vibration transmission between sources and target locations. The findings support optimized vibration control strategies, leading to improved passenger comfort and reduced underwater noise.

As a multi-body system, the floating offshore wind turbine (FOWT) exhibits significant coupling effect between rotational and translational displacements, and neglecting some rotational angles or applying small-angle assumption in calculations will influence the accuracy of results. In this paper, a 16 degrees of freedom multi-body coupled model including platform, tower, and rotor blades is established. The model fully accounts for coordinate transformations caused by FOWT’s rotation without small-angle assumption, while considering the coupling characteristics between aerodynamic forces, hydrodynamic forces, and structure, and is employed for calculating FOWT responses and investigating the control performance of mass dampers. Taking the Spar-type FOWT as an example, the simulation results comparison between the coupled model and OpenFAST demonstrates its accuracy. Subsequent response analysis indicates that the small-angle assumption underestimates the FOWT response under free vibration and wave loading, while overestimating response under wind loading. Simultaneously, the impact of hydrodynamic computational methods and servo control systems on the calculation results was also analyzed. Finally, using tuned swing mass damper as an example, the modeling method for mass dampers is introduced and the impact of small-angle assumption on computational results is analyzed, providing reference for researchers in the field of FOWT control.

As terrestrial mineral resources continue to diminish, the global focus has significantly shifted toward deep-sea mining, driven by the escalating demand for critical minerals such as lithium, nickel, and cobalt. Among various extraction methods, the pipe lifting technique has gained prominence owing to its substantial commercial viability. Nevertheless, this method faces significant operational challenges, including intricate flow dynamics, pipe wall erosions, and blockages caused by the continuous transport of particulate matter. This study investigates the influence of mineral particle size, the slurry velocity, volume fraction, and shear modulus on pipeline erosion. To enhance the precision of erosion prediction, a solid-liquid coupling optimization model was developed utilizing the Gaussian volume distribution method. Orthogonal experiments and single-factor analyses revealed that the slurry velocity and mineral particle size predominantly influence the erosion rate. The findings of this study elucidate the underlying mechanisms of pipeline erosion in deep-sea mining operations and offer crucial data for the advancement and design of deep-sea transportation systems.

Accurate prediction of the burst pressure of corroded pipes is crucial for preventing their failure. This study integrates finite element method (FEM) simulations with machine learning (ML) models to predict the burst pressure with high accuracy. FEM analyses, employing both solid and shell elements, were performed on offshore API 5L X65 steel pipes with real-world multiple corrosion defects. The burst pressure was estimated by applying a factor of 1.05 to the instability criterion. Shell elements yielded results comparable to those of solid elements, while also significantly reducing computational time from 55.82 h to 25.75 h. Three ML models—multilayer perceptron, Gaussian process, and support vector machine—were developed based on three different input groups. Among them, the support vector machine demonstrated the best performance, achieving the highest coefficient of determination (R² = 0.95). SHapley Additive exPlanations (SHAP) analysis identifies average defect depth as the most influential parameter, contributing 56.21% to predictions and exhibiting an inverse correlation with burst pressure, aligning with real-world behavior.

To enhance the long-distance penetration and combat capabilities of unmanned underwater vehicles (UUVs), this study proposes a high-altitude, long-distance gliding UUV that can be rapidly deployed by a penetration platform. According to the overall scheme, the overall trajectory is partitioned into five distinct stages: the flight stage of the penetration platform, the release stage, the conversion stage, the glide stage, and the water entry stage of the gliding UUV, with trajectory characteristics discussed for each operational segment. UUV conversion, after its release from the penetration platform, is accomplished by designing a piecewise quadratic trajectory inclination angle. The feasibility of the conversion stage trajectory design is validated using a RHC algorithm. The influence of different initial velocities on UUV conversion is also investigated. The glide stage employs a reverse thrust methodology to ensure water entry safety. Trajectory characteristics in the five different stages are studied, with the simulation verifying the rationality of the overall trajectory. Accordingly, the UUV achieves a total flight range of 410 km within 633.5 s, with the designed trajectory enabling smooth conversion and high-altitude glide performance. The water entry velocity of the UUV is 33.3 m/s, and the water entry angle is -72°, meeting the requirements of load shedding on UUVs. The reasonably designed trajectory of the high-altitude, long-distance gliding UUV establishes a foundation for subsequent engineering validation.

This study numerically determines hydrodynamic coefficients of a torpedo-shaped autonomous underwater vehicle (AUV) using the shear stress transport k-ω turbulence model in COMSOL Multiphysics. Linear and nonlinear coefficients are extracted via steady-state simulations (uniform linear motion, uniformly accelerated motion, and horizontal/vertical oblique cruising) and transient simulations replicating planar motion mechanism (PMM) tests with small and large amplitudes. The sliding mesh and rotating domain techniques resolve unsteady flow characteristics during dynamic maneuvers. The methodology formalizes six-degree-of-freedom motion equations, with hydrodynamic coefficients identified through regression analysis of simulated force/moment data. Experimental validation via towing-tank testing demonstrates agreement between numerical predictions and empirical measurements, particularly in capturing nonlinear hydrodynamic effects during large-amplitude PMM maneuvers. The framework maintains geometric generality for application to diverse AUV configurations. Resultant hydrodynamic databases improve the motion prediction accuracy in dynamic environments, enhance attitude control algorithm robustness, and support hull optimization through parametric drag analysis. The hydrodynamic database established significantly improves the maneuverability prediction accuracy under turbulent marine conditions.

Cooperative control technology has propelled the development of unmanned surface vessel and unmanned aerial vehicle (USV–UAV) systems. To extend their application potential in complex environments, it is essential to improve the flexibility and robustness of time-varying formation tracking (TFT) control for USV–UAV systems. This article proposes a distributed adaptive TFT control scheme with the output regulation theory, such that all vehicles can realize the expected time-varying formation while tracking multiple leaders. First, a distributed observer is constructed to estimate the global states of all leaders. Subsequently, an adaptive TFT controller is presented for each vehicle based on the output regulation framework and the estimated states of the leaders. Given the external disturbances and unknown nonlinearities, system robustness is effectively enhanced by introducing adaptive parameters and compensation inputs. Additionally, extra formation compensation terms are incorporated into the controller to ensure system adaptability to time-varying formation changes. Finally, theoretical analysis and numerical simulations are presented to demonstrate the effectiveness of the proposed scheme.

This study solves the problem of distributed prescribed-time containment control of underactuated unmanned surface vehicles (USVs) in the presence of parametric uncertainties, unmodeled dynamics, and external environmental disturbances. Under the leader-follower approach, considering that only a subset of followers has access to the trajectory information of the virtual leaders, a novel distributed adaptive prescribed-time observer is presented. Given the general uncertainties in the USV model, an improved prescribed-time extended state observer (PTESO) is established for estimation and compensation. Then, a prescribed-time command filter and a filter compensation system are introduced to estimate the virtual control signal and address the differential explosion problem. Furthermore, a prescribed-time anti-saturation auxiliary system is proposed to address the actuator input saturation. Moreover, a prescribed-time distributed guidance protocol and a distributed control protocol are developed for each USV by employing the backstepping method and the variable transformation strategy. The use of graph theory, prescribed-time theory, and Lyapunov analysis ensures that the follower converges to the convex hull spanned by the multiple virtual leaders within a prescribed time. This approach involves dynamically adjusting the distance among USVs according to the channel width. The errors associated with the distributed adaptive observer and PTESO exhibit bounded convergence within a prescribed time. In addition, the full-state constraints have been confirmed, which implies that the containment errors, including position, velocity, and acceleration errors of the followers, can converge and remain bounded within a prescribed time. The originality of this study lies in overcoming key challenges, including general model uncertainties, actuator saturation, limited information available to follower USVs, and ensuring prescribed-time convergence. Future research can explore an event-based communication protocol to realize intermittent communication among USVs.

Unmanned surface vehicles (USVs) play a vital role in marine construction, such as maritime patrol and search–rescue operations. However, USVs face complex challenges when performing tasks in path planning. An adaptive chaotic-enhanced particle swarm optimization (ACA-PSO) algorithm is presented in this paper to increase the efficiency of static path planning for USVs in intricate maritime environments. The proposed ACA-PSO algorithm addresses the dual challenges of path optimality and navigational safety while considering path length, smoothness, safety, and convergence speed. First, a sine chaotic sequence for initialization is introduced, which enhances global search capabilities and effectively escapes local optima. Second, an adaptive inertia weight decay strategy is proposed to adjust the weight dynamically to enhance convergence efficiency and solution quality. Third, sinusoidal acceleration learning factors are considered to alleviate the limitations of static cognitive and social learning factors. Fourth, a historical velocity weighting strategy is developed to improve trajectory smoothness and convergence robustness. Finally, extensive simulation results confirm that the proposed ACA-PSO algorithm significantly outperforms conventional PSO and other optimization algorithms in path planning effectiveness, convergence efficiency, and operational stability. Specifically, in optimal path distance, the proposed ACA-PSO algorithm achieves 2.4% and 4.9% improvements compared with traditional PSO and simulated annealing (SA) algorithms, respectively. The proposed ACA-PSO algorithm also demonstrates a 29.8% better grayscale value in path smoothness compared with the SA algorithm. Moreover, with a much lower standard deviation of 0.201 × 10^-2, the ACA-PSO algorithm is superior in stability.

With the growing demand for cross-domain operations in fields such as environmental monitoring, emergency response, and scientific exploration, hybrid aerial-aquatic vehicles (HAAVs) have emerged as a cutting-edge research direction integrating bio-inspired principles and multi-domain robotic technologies. This paper systematically reviews the technological trajectories of HAAVs: bio-inspired designs achieve efficient air-water transitions through flapping-wing (e.g., flying fish/insect-inspired) and water-jet (e.g., cephalopod-inspired) propulsion systems, enhanced by morphing structures (e.g., bistable airfoils, foldable wings). Meanwhile, drone-UUV integrated systems employ unimodal (multirotor/fixed-wing) and multimodal architectures, optimizing multi-domain adaptability through hybrid thrust mapping and active buoyancy control. Key challenges remain in cross-medium dynamic coupling, energy efficiency, and communication reliability. This paper provides theoretical foundations and technical roadmaps for the bio-inspired design and system integration of next-generation intelligent cross-domain platforms.

Path planning is essential for an autonomous underwater vehicle (AUV) to efficiently perform underwater missions. To address the challenges of energy-efficient three-dimensional path planning under multiple constraints, this study proposes a synergistic differential evolution (SDE) algorithm. First, a comprehensive underwater environment model is developed, including a path encoding model and a deterministic path-evaluation method. Second, a synergistic evolution mechanism is introduced to improve global exploration by adaptively sharing the evolutionary information of two synergistic populations. Third, evolutionary guidance is proposed to refine the search direction by integrating successful population movements based on fitness improvements and positional correlations. Finally, a cosine-based strategy is employed to adjust the population size by eliminating low-quality solutions. Compared to state-of-the-art methods, the proposed algorithm achieves average improvements of 2.37% in best fitness, 15.99% in mean fitness, 13.42% in median fitness, 80.69% in standard deviation, 66.65% in convergence quality, and 39.91% in runtime. In addition, AUV field tests further validate the feasibility and reliability of the SDE-based path-planning approach.

In recent years, deep-sea acoustic sensor networks (DSASNs) have gained considerable attention in areas such as deep-sea resource exploration, environmental monitoring, and underwater construction. However, due to the combined effects of adverse DSA channel conditions, a hostile deep-sea environment, long propagation delays, and limited energy supply, DSASNs often experience random performance fluctuations and low resilience. These issues are typically caused by unstable connectivity and abnormal node failures. Given the critical role of network topology in influencing network behavior, this paper proposes a hybrid topology optimization algorithm for DSASNs. The algorithm integrates the virtual force algorithm (VFA) and particle swarm optimization (PSO), leveraging the global search capability of PSO and the local optimization strength of VFA to provide a highly robust solution for improving the DSASN resilience (DSR–VFPSO). Specifically, a comprehensive objective function is formulated to transform the high-resilience topology optimization problem into a dual-objective function of maximizing coverage and optimizing betweenness centrality. This objective is addressed iteratively through the combined use of VFA and PSO to reach an optimal solution. Simulation results reveal that the proposed algorithm effectively improves the resilience of DSASNs under artificial stress conditions caused by random node failures.

Recently, the underwater digital terrain model (UDTM) has been extensively used for seafloor terrain measurement. Identifying terrain and nonterrain points from an underwater bathymetric point cloud has been a fundamental problem in UDTM modeling. Hence, we propose a new ground filtering method derived from smoothed particle hydrodynamics to distinguish bathymetric points. The proposed method is called smoothed particle simulation filtering (SPSF), which embodies filtering as a matching of a smoothed particle grid to the point-set surface. First, four seafloor terrain features, namely curvature-based shape factor, slope, roughness, and concave–convex coefficient, are extracted from the moving least-square fitting surface of the original point-set surface, and the terrain complexity of each point is computed. Then, an enhanced particle motion model appropriate for ground filtering is introduced. To improve filtering performance, we divide the point-set surface into several subregions and set adaptive parameters for diverse subregions according to the terrain complexity. Finally, subregional point cloud filtering is performed, and each bathymetric point is marked as "terrain" or "nonterrain". To assess the filtering performance, SPSF is applied to process the multibeam bathymetric point cloud data collected around Chi Island in Qingdao, China. Results indicate that compared with the same type of filtering methods, SPSF improves the filtering accuracy by more than 50% and the filtering efficiency by more than 40%. Furthermore, compared with other types of filtering methods, SPSF displays great potential in alleviating over- and under-filtering in seafloor terrains.