Races using kitefoil and windfoil surfboards have been in the Olympic Games for the first time in Paris 2024, signalling their relevance in sailing sports. However, the dynamics of these devices is yet not well understood, in particular the influence on the hydrodynamic forces and moments of the distance of the foil to the free surface. Considering this, the present paper documents an experimental investigation in which forces and torque produced, under uniform flow, by a full-scale state-of-the-art hydrofoil (suitable both for kitesurf and windsurf) were measured. A range of velocities, angles of attack, and submergences were tested, leading to Froude numbers based on submergence with maximum values around five, a typical range in actual sailing conditions. From these tests, formulae for the hydrodynamic coefficients have been proposed. They can be used for developing Velocity Prediction Programs (VPP) for this kind of craft, a necessary tool to plan racing configurations and to analyze their racing performance. With the aim of making the experimental data useful for benchmarking numerical models and for future research on related topics such as foil ventilation and transition to turbulence, the specimen’s 3D file is provided as supplementary material to this paper.

In this investigation, a hybrid approach integrating the IDDES turbulence model and FW-H is employed to forecast the hydroacoustic of the rim-driven thruster (RDT) under non-cavitation and uniform flow conditions at varying loading conditions (J = 0.3 and J = 0.6). It is revealed that the quadrupole term contribution in the P-FWH method significantly affects the monopole term in the low-frequency region, while it mainly affects the dipole term in the high-frequency region. Specifically, the overall sound pressure levels (SPL) of the RDT using the P-FWH method are 2.27 dB, 10.03 dB, and 16.73 dB at the receiving points from R1 to R3 under the heavy-loaded condition, while they increase by 0.67 dB at R1, and decrease by 14.93 dB at R2, and 22.20 dB at R3, for the light-loaded condition. The study also utilizes the pressure-time derivatives to visualize the numerical noise and to pinpoint the dynamics of the vortex cores, and the optimization of the grid design can significantly reduce the numerical noise. The computational accuracy of the P-FWH method can meet the noise requirements for the preliminary design of rim-driven thrusters.

In this study, the dynamic characteristics of microscale floating bubbles near the vertical wall are studied. This occurrence is common in industrial and natural phenomena. Although many studies have been conducted on microscale bubbles, few studies investigate floating bubbles with very small Reynolds number (Re) near the wall, which is the main research goal of this study. Therefore, this study establishes a model for the ascent of small-scale bubbles near a vertical wall using the interFoam solver in OpenFOAM. This study investigates the influences of diverse viscosity parameters, varying distances from the wall, and different gas flow rates on the terminal velocity, deformation, and motion trajectory of bubbles. The results reveal that as liquid viscosity increases, the Re of bubbles gradually decreases and reaches a minimum of 0.012, which is similar to the Re of micrometer-sized bubbles in water. The characteristics of the wall-induced force in the longitudinal direction are closely related to the changes in liquid viscosity. Under low-viscosity conditions, the induced lift is the principal form of action, whereas under high-viscosity conditions, it is primarily manifested as induced drag.

The issue of resistance reduction through hull ventilation is of particular interest in contemporary research. This paper presents multiphase computational fluid dynamics (CFD) simulations with 2-DOF motion of a planing hull. The original hull was modified by introducing a step to allow air ventilation. Following an assessment of the hull performance, a simulation campaign in calm water was conducted to characterize the hull at various forward speeds and air insufflation rates for a defined single step geometry. Geometric analysis of the air layer thickness beneath the hull for each simulated condition was performed using a novel method for visualizing local air thickness. Additionally, two new parameters were introduced to understand the influence of spray rails on the air volume beneath the hull and to indicate the primary direction of ventilated air escape. A validation campaign and an assessment of uncertainty of the simulation has been conducted. The features offered by the CFD methodology include the evaluation of the air layer thickness as a function of hull velocity and injection flow rate and the air volume distribution beneath the hull. The air injection velocity can be adjusted across various operating conditions, thereby preventing performance or efficiency loss during navigation. Based on these findings, the study highlights the benefits of air insufflation in reducing hull resistance for high-speed planing vessels. This work lays a robust foundation for future research and new promising topics, as the exploration of air insufflation continues to be a topic of contemporary interest within naval architecture and hydrodynamics.

Vortex-induced vibration (VIV) of an underwater manipulator in pulsating flow presents a notable engineering problem in precise control due to the velocity variation in the flow. This study investigates the VIV response of an underwater manipulator subjected to pulsating flow, focusing on how different postures affect the behavior of the system. The effects of pulsating parameters and manipulator arrangement on the hydrodynamic coefficient, vibration response, motion trajectory, and vortex shedding behaviors were analyzed. Results indicated that the cross-flow vibration displacement in pulsating flow increased by 32.14% compared to uniform flow, inducing a shift in the motion trajectory from a crescent shape to a sideward vase shape. In the absence of interference between the upper and lower arms, the lift coefficient of the manipulator substantially increased with rising pulsating frequency, reaching a maximum increment of 67.0%. This increase in the lift coefficient led to a 67.05% rise in the vibration frequency of the manipulator in the in-line direction. As the pulsating amplitude increased, the drag coefficient of the underwater manipulator rose by 36.79%, but the vibration frequency in the cross-flow direction decreased by 56.26%. Additionally, when the upper and lower arms remained in a state of mutual interference, the cross-flow vibration amplitudes of the upper and lower arms were approximately 1.84 and 4.82 times higher in a circular-elliptical arrangement compared to an elliptical-circular arrangement, respectively. Consequently, the flow field shifted from a P+S pattern to a disordered pattern, disrupting the regularity of the motion trajectory.

Studies of wave–current interactions are vital for the safe design of structures. Regular waves in the presence of uniform, linear shear, and quadratic shear currents are explored by the High-Level Green–Naghdi model in this paper. The five-point central difference method is used for spatial discretization, and the fourth-order Adams predictor–corrector scheme is employed for marching in time. The domain-decomposition method is applied for the wave–current generation and absorption. The effects of currents on the wave profile and velocity field are examined under two conditions: the same velocity of currents at the still-water level and the constant flow volume of currents. Wave profiles and velocity fields demonstrate substantial differences in three types of currents owing to the diverse vertical distribution of current velocity and vorticity. Then, loads on small-scale vertical cylinders subjected to regular waves and three types of background currents with the same flow volume are investigated. The maximum load intensity and load fluctuation amplitude in uniform, linear shear, and quadratic shear currents increase sequentially. The stretched superposition method overestimates the maximum load intensity and load fluctuation amplitude in opposing currents and underestimates these values in following currents. The stretched superposition method obtains a poor approximation for strong nonlinear waves, particularly in the case of the opposing quadratic shear current.

Installing internal bulkheads in a composite bucket foundation alters the rotational symmetry characteristic of a single-compartment bucket foundation, consequently influencing the stress distribution within the bucket and surrounding soil. During the seabed penetration of a spudcan from a jack-up wind turbine installation vessel, an angle may form between the spudcan’s axis and the axis of symmetry of the adjacent composite bucket foundation in the horizontal plane. Such a misalignment may affect load distribution and the non-uniform interaction between the foundation, soil, and spudcan, ultimately influencing the foundation’s stability. This study employs physical model tests to ascertain the trends in end resistance during spudcan penetration in sand, the extent of soil disturbance, and the backflow condition. The finite element coupled Eulerian–Lagrangian method is validated and utilized to determine the range of penetration angles that induce alterations in the maximum vertical displacement and tilt rate of the composite bucket foundation in sand. The differential contact stress distribution at the base of the bucket is analyzed, with qualitative criteria for sand backflow provided. Findings demonstrate that the maximum vertical displacement and tilt rate of the composite bucket foundation display a “wave-like” variation with the increasing spudcan penetration angle, peaking when the angle between the spudcan and bulkhead is the smallest. Stress distribution is predominantly concentrated at the base and apex of the bucket, becoming increasingly uneven as the penetration angle deviates from the foundation’s symmetry axis. The maximum stress gradually shifts to the junction of the bulkhead and bucket bottom on the side with the shortest net distance from the spudcan. Considering the in-place stability and stress state of the composite bucket foundation is therefore imperative, and particular attention should be paid to the foundation’s state when the angle between the spudcan and bulkhead is small.

An analytical model of a floating heaving box integrated with a vertical flexible porous membrane placed right next to the box applications to wave energy extraction and breakwater systems is developed under the reduced wave equation. The theoretical solutions for the heave radiating potential to the assigned physical model in the corresponding zones are attained by using the separation of variables approach along with the Fourier expansion. Applying the matching eigenfunction expansion technique and orthogonal conditions, the unknown coefficients that are involved in the radiated potentials are determined. The attained radiation potential allows the computation of hydrodynamic coefficients of the heaving buoy, Power Take-Off damping, and wave quantities. The accuracy of the analytical solution for the hydrodynamic coefficients is demonstrated for different oblique angles with varying numbers of terms in the series solution. The current analytical analysis findings are confirmed by existing published numerical boundary element method simulations. Several numerical results of the hydrodynamic coefficients, power capture, power take-off optimal damping, and transmission coefficients for numerous structural and physical aspects are conducted. It has been noted that the ideal power take-off damping increases as the angle of incidence rises, and the analysis suggests that the ability to capture waves is more effective in shallower waters compared to deeper ones.

Marine thin plates are susceptible to welding deformation owing to their low structural stiffness. Therefore, the efficient and accurate prediction of welding deformation is essential for improving welding quality. The traditional thermal elastic-plastic finite element method (TEP-FEM) can accurately predict welding deformation. However, its efficiency is low because of the complex nonlinear transient computation, making it difficult to meet the needs of rapid engineering evaluation. To address this challenge, this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds. This method is based on the coupled temperature gradient-thermal strain method (TG-TSM) that integrates inherent strain theory with a shell element finite element model. The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis. This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation. The proposed method—particularly, the gradual temperature gradient-thermal strain method (GTG-TSM)—achieved improved computational efficiency and consistent precision. Furthermore, the proposed method required much less computation time than the traditional TEP-FEM. Thus, this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.

This study examines the methods to plan the development of offshore oilfields over the years, which are used to support the decision-making on the development of offshore oilfields. About 100 papers are analysed and categorised into different groups of main early-stage decisions. The present study stands in contrast to the contributions of the operations research and system engineering review articles, on the one hand, and the petroleum engineering review articles, on the other. This is because it does not focus on one methodological approach, nor does it limit the literature analysis by offshore oilfield characteristics. Consequently, the present analysis may offer valuable insights, for instance, by identifying environmental planning decisions as a recent yet highly significant concern that is currently being imposed on decision-making process. Thus, it is evident that the incorporation of safety criteria within the technical-economic decision-making process for the design of production systems would be a crucial requirement at development phase.

Monocolumn composite bucket foundation is a new type of offshore wind energy foundation. Its bearing characteristics under shallow bedrock conditions and complex geological conditions have not been extensively studied. Therefore, to analyze its bearing characteristics under complex conditions—such as silty soil, chalky soil, and shallow bedrock—this paper employs finite element software to establish various soil combination scenarios. The load – displacement curves of the foundations under these scenarios are calculated to subsequently evaluate the horizontal ultimate bearing capacity. This study investigates the effects of shallow bedrock depth, the type of soil above the bedrock, the thickness of layered soil, and the quality of layered soil on the bearing characteristics of the monocolumn composite bucket foundation. Based on the principle of single-variable control, the ultimate bearing capacity characteristics of the foundation under different conditions are compared. The distribution of soil pressure inside and outside the bucket wall on the compressed side of the foundation, along with the plastic strain of the soil at the base of the foundation, is also analyzed. In conclusion, shallow bedrock somewhat reduces foundation bearing capacity. Under shallow bedrock conditions, the degree of influence on foundation bearing capacity characteristics can considerably vary on different upper soils. The thickness of each soil layer and the depth to bedrock in stratified soils also affect the bearing capacity of the foundation. The findings of this paper provide a theoretical reference for related foundation design and construction. In practice, the bearing performance of the foundation can be enhanced by improvingthe soil quality in the bucket, adjusting the penetration depth, adjusting the percentage of different types of soil layers in the bucket, and applying other technical construction methods.

Environmental pollution, energy consumption, and greenhouse gas emissions are critical global issues. To address these challenges, optimizing skimmer coatings is a major step in commercializing cleaning oil stains. This research presents a novel approach to creating and refining oil-absorbent coatings, introducing a unique oil spill removal skimmer enhanced with a super hydrophobic polyaniline (PANI) nanofiber coating. The goal of this study was to improve oil absorption performance, increase the contact angle, lower drag, reduce energy consumption, achieve high desirability, and lower production costs. PANI treated with hydrochloric acid was a key focus as it resulted in higher porosity and smaller pore diameters, providing a larger surface area, which are crucial factors for boosting oil absorption and minimizing drag. To optimize optimal nanofiber morphology, PANI synthesized with methanesulfonic acid was first dedoped and then redoped with hydrochloric acid. After optimization, the most effective skimmer coating was achieved using a formulation consisting of 0.1% PANI, an ammonium persulfate/aniline ratio of 0.4, and an acid/aniline ratio of 9.689, along with redoped PANI nanofibers. The optimized skimmer exhibited a remarkable contact angle of 177.477°. The coating achieved drag reduction of 32%, oil absorption of 88.725%, a cost of $1.710, and a desirability rating of 78.5%. In this study, an optimized skimmer coat containing super hydrophobic coat–PANI nanofibers was fabricated. By enhancing contact angle and reducing drag, these coatings increased the skimmer performance by improving oil absorption and reducing fuel consumption.

Underwater pipeline inspection plays a vital role in the proactive maintenance and management of critical marine infrastructure and subaquatic systems. However, the inspection of underwater pipelines presents a challenge due to factors such as light scattering, absorption, restricted visibility, and ambient noise. The advancement of deep learning has introduced powerful techniques for processing large amounts of unstructured and imperfect data collected from underwater environments. This study evaluated the efficacy of the You Only Look Once (YOLO) algorithm, a real-time object detection and localization model based on convolutional neural networks, in identifying and classifying various types of pipeline defects in underwater settings. YOLOv8, the latest evolution in the YOLO family, integrates advanced capabilities, such as anchor-free detection, a cross-stage partial network backbone for efficient feature extraction, and a feature pyramid network+ path aggregation network neck for robust multi-scale object detection, which make it particularly well-suited for complex underwater environments. Due to the lack of suitable open-access datasets for underwater pipeline defects, a custom dataset was captured using a remotely operated vehicle in a controlled environment. This application has the following assets available for use. Extensive experimentation demonstrated that YOLOv8 X-Large consistently outperformed other models in terms of pipe defect detection and classification and achieved a strong balance between precision and recall in identifying pipeline cracks, rust, corners, defective welds, flanges, tapes, and holes. This research establishes the baseline performance of YOLOv8 for underwater defect detection and showcases its potential to enhance the reliability and efficiency of pipeline inspection tasks in challenging underwater environments.

During the use of robotics in applications such as antiterrorism or combat, a motion-constrained pursuer vehicle, such as a Dubins unmanned surface vehicle (USV), must get close enough (within a prescribed zero or positive distance) to a moving target as quickly as possible, resulting in the extended minimum-time intercept problem (EMTIP). Existing research has primarily focused on the zero-distance intercept problem, MTIP, establishing the necessary or sufficient conditions for MTIP optimality, and utilizing analytic algorithms, such as root-finding algorithms, to calculate the optimal solutions. However, these approaches depend heavily on the properties of the analytic algorithm, making them inapplicable when problem settings change, such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion. In this study, an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program (QG-PWL) is proposed for the EMTIP. This program can accommodate different effective interception ranges and complicated target motions (variable velocity or complicated trajectories). The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies. The approximate error in the intercept path length is proved to be bounded to

Amphibious vehicles are more prone to attitude instability compared to ships, making it crucial to develop effective methods for monitoring instability risks. However, large inclination events, which can lead to instability, occur frequently in both experimental and operational data. This infrequency causes events to be overlooked by existing prediction models, which lack the precision to accurately predict inclination attitudes in amphibious vehicles. To address this gap in predicting attitudes near extreme inclination points, this study introduces a novel loss function, termed generalized extreme value loss. Subsequently, a deep learning model for improved waterborne attitude prediction, termed iInformer, was developed using a Transformer-based approach. During the embedding phase, a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment. Data segmentation techniques are used to highlight local data variation features. Furthermore, to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function, a teacher forcing mechanism is integrated into the model, enhancing its convergence capabilities. Experimental results validate the effectiveness of the proposed method, demonstrating its ability to handle data imbalance challenges. Specifically, the model achieves over a 60% improvement in root mean square error under extreme value conditions, with significant improvements observed across additional metrics.

This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis (FTA) and Bayesian Networks (BN). FTA provides a structured, top-down method for identifying critical failure modes and their root causes, while BN introduces flexibility in probabilistic reasoning, enabling dynamic updates based on new evidence. This dual methodology overcomes the limitations of static FTA models, offering a comprehensive framework for system reliability analysis. Critical failures, including External Leakage (ELU), Failure to Start (FTS), and Overheating (OHE), were identified as key risks. By incorporating redundancy into high-risk components such as pumps and batteries, the likelihood of these failures was significantly reduced. For instance, redundant pumps reduced the probability of ELU by 31.88%, while additional batteries decreased the occurrence of FTS by 36.45%. The results underscore the practical benefits of combining FTA and BN for enhancing system reliability, particularly in maritime applications where operational safety and efficiency are critical. This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems, especially as the industry transitions toward more autonomous vessels.

Analysis of the environmental and economic performance of fishing vessels has received limited attention compared with other ship types despite their notable contribution to global greenhouse gas (GHG) emissions. This study evaluates the carbon footprint (CF) and economic viability of a liquefied natural gas (LNG)-fueled fishing vessel, using real engine operation simulations to provide precise and dynamic evaluation of fuel consumption and GHG emissions. Operational profiles are obtained through the utilization of onboard monitoring systems, whereas engine performance is simulated using the 1D/0D AVL Boost ™ model. Life cycle assessment (LCA) is conducted to quantify the environmental impact, whereas life cycle cost assessment (LCCA) is performed to analyze the profitability of LNG as an alternative fuel. The potential impact of the future fuel price uncertainties is addressed using Monte Carlo simulations. The LCA findings indicate that LNG has the potential to reduce the CF of the vessel by 14% to 16%, in comparison to a diesel power system configuration that serves as the baseline scenario. The LCCA results further indicate that the total cost of an LNG-powered ship is lower by 9.5%–13.8%, depending on the share of LNG and pilot fuels. This finding highlights the potential of LNG to produce considerable environmental benefits while addressing economic challenges under diverse operational and fuel price conditions.

Pre-chamber ignition technology can address the issue of uneven in-cylinder mixture combustion in large-bore marine engines. The impact of various pre-chamber structures on the formation of the mixture and jet flames within the pre-chamber is explored. This study performed numerical simulations on a large-bore marine ammonia/hydrogen pre-chamber engine prototype, considering pre-chamber volume, throat diameter, the distance between the hydrogen injector and the spark plug, and the hydrogen injector angle. Compared with the original engine, when the pre-chamber volume is 73.4 ml, the throat diameter is 14 mm, the distance ratio is 0.92, and the hydrogen injector angle is 80°. Moreover, the peak pressure in the pre-chamber increased by 23.1%, and that in the main chamber increased by 46.3%. The results indicate that the performance of the original engine is greatly enhanced by altering its fuel and pre-chamber structure.

While reinforcement learning-based underwater acoustic adaptive modulation shows promise for enabling environment-adaptive communication as supported by extensive simulation-based research, its practical performance remains underexplored in field investigations. To evaluate the practical applicability of this emerging technique in adverse shallow sea channels, a field experiment was conducted using three communication modes: orthogonal frequency division multiplexing (OFDM), M-ary frequency-shift keying (MFSK), and direct sequence spread spectrum (DSSS) for reinforcement learning-driven adaptive modulation. Specifically, a Q-learning method is used to select the optimal modulation mode according to the channel quality quantified by signal-to-noise ratio, multipath spread length, and Doppler frequency offset. Experimental results demonstrate that the reinforcement learning-based adaptive modulation scheme outperformed fixed threshold detection in terms of total throughput and average bit error rate, surpassing conventional adaptive modulation strategies.

In this study, a fifth-degree cubature particle filter (5CPF) is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking (BOT). This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling, which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter. However, the 5CPF algorithm exhibits high computational complexity, particularly in scenarios with a large number of particles. Therefore, we propose the extended Kalman filter (EKF)-5CPF algorithm, which employs an EKF to replace the time update step for each particle in the 5CPF. This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm. In addition, we construct bearing-only dual-station and single-motion station target tracking systems, and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed. The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments. Furthermore, both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed, tracking accuracy, and overall stability.

Accurate time delay estimation of target echo signals is a critical component of underwater target localization. In active sonar systems, echo signal processing is vulnerable to the effects of reverberation and noise in the maritime environment. This paper proposes a novel method for estimating target time delay using multi-bright spot echoes, assuming the target’s size and depth are known. Aiming to effectively enhance the extraction of geometric features from the target echoes and mitigate the impact of reverberation and noise, the proposed approach employs the fractional order Fourier transform-frequency sliced wavelet transform to extract multi-bright spot echoes. Using the highlighting model theory and the target size information, an observation matrix is constructed to represent multi-angle incident signals and obtain the theoretical scattered echo signals from different angles. Aiming to accurately estimate the target’s time delay, waveform similarity coefficients and mean square error values between the theoretical return signals and received signals are computed across various incident angles and time delays. Simulation results show that, compared to the conventional matched filter, the proposed algorithm reduces the relative error by 65.9%–91.5% at a signal-tonoise ratio of -25 dB, and by 66.7%–88.9% at a signal-to-reverberation ratio of -10 dB. This algorithm provides a new approach for the precise localization of submerged targets in shallow water environments.