Through active manipulation of wavelengths, a structure exposed to a water-wave field can achieve a target hydrodynamic performance. Based on the form invariance of the governing equation for shallow water waves, wavelength modulators have been proposed using the space transformation method, which enables wavelength manipulation by distributing an anisotropic medium that incorporates water depth and gravitational acceleration within the modulation space. First, annular wavelength modulators were designed using the space transformation method to reduce or amplify the wavelength of shallow water waves. The control method of wavelength scaling ratios was investigated. In addition to plane waves, the wavelength modulator was applied to manipulate the wavelength of cylindrical waves. Furthermore, the interactions between a vertical cylinder and modulated water waves were studied. Results indicate that the wavelength can be arbitrarily reduced or amplified by adjusting the dimensional parameters of the modulator. Additionally, the modulator is effective for plane waves and cylindrical waves. This wavelength modulator can enable the structure to achieve the desired scattering characteristics at the target wavelength.

This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry, emphasizing their role in improving material utilization, minimizing waste, and enhancing production efficiency. The shipbuilding process involves the complex cutting and arrangement of steel plates, making the optimization of these operations vital for cost-effectiveness and sustainability. Nesting algorithms are broadly classified into four categories: exact, heuristic, metaheuristic, and hybrid. Exact algorithms ensure optimal solutions but are computationally demanding. In contrast, heuristic algorithms deliver quicker results using practical rules, although they may not consistently achieve optimal outcomes. Metaheuristic algorithms combine multiple heuristics to effectively explore solution spaces, striking a balance between solution quality and computational efficiency. Hybrid algorithms integrate the strengths of different approaches to further enhance performance. This review systematically assesses these algorithms using criteria such as material dimensions, part geometry, component layout, and computational efficiency. The findings highlight the significant potential of advanced nesting techniques to improve material utilization, reduce production costs, and promote sustainable practices in shipbuilding. By adopting suitable nesting solutions, shipbuilders can achieve greater efficiency, optimized resource management, and superior overall performance. Future research directions should focus on integrating machine learning and real-time adaptability to further enhance nesting algorithms, paving the way for smarter, more sustainable manufacturing practices in the shipbuilding industry.

Captive model tests are one of the most common methods to calculate the maneuvering hydrodynamic coefficients and characteristics of surface and underwater vehicles. Considerable attention must be paid to selecting and designing the most suitable laboratory equipment for towing tanks. A computational fluid dynamics (CFD) -based method is implemented to determine the loads acting on the towing facility of the submarine model. A reversed topology is also used to ensure the appropriateness of the load cells in the developed method. In this study, the numerical simulations were evaluated using the experimental results of the SUBOFF benchmark submarine model of the Defence Advanced Research Projects Agency. The maximum and minimum loads acting on the 2.5-meter submarine model were measured by determining the body’s lightest and heaviest maneuvering test scenarios. In addition to having sufficient endurance against high loads, the precision in measuring the light load was also investigated. The horizontal planar motion mechanism (HPMM) facilities in the National Iranian Marine Laboratory were developed by locating the load cells inside the submarine model. The results were presented as a case study. A numerical-based method was developed to obtain the appropriate load measurement facilities. Load cells of HPMM test basins can be selected by following the two-way procedure presented in this study.

This study investigates the effect of nacelle motions on the rotor performance and drivetrain dynamics of floating offshore wind turbines (FOWTs) through fully coupled aero–hydro–elastic–servo–mooring simulations. Using the National Renewable Energy Laboratory 5 MW monopile-supported offshore wind turbine and the OC4 DeepCwind semisubmersible wind turbine as case studies, the research addresses the complex dynamic responses resulting from the interaction among wind, waves, and turbine structures. Detailed multi-body dynamics models of wind turbines, including drivetrain components, are created within the SIMPACK framework. Meanwhile, the mooring system is modeled using a lumped-mass method. Various operational conditions are simulated through five wind–wave load cases. Results demonstrate that nacelle motions significantly influence rotor speed, thrust, torque, and power output, as well as the dynamic loads on drivetrain components. These findings highlight the need for advanced simulation techniques for the design and optimization of FOWTs to ensure reliable performance and longevity.

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.

The rudder mechanism of the X-rudder autonomous underwater cehicle (AUV) is relatively complex, and fault diagnosis capability is an important guarantee for its task execution in complex underwater environments. However, traditional fault diagnosis methods currently rely on prior knowledge and expert experience, and lack accuracy. In order to improve the autonomy and accuracy of fault diagnosis methods, and overcome the shortcomings of traditional algorithms, this paper proposes an X-steering AUV fault diagnosis model based on the deep reinforcement learning deep Q network (DQN) algorithm, which can learn the relationship between state data and fault types, map raw residual data to corresponding fault patterns, and achieve end-to-end mapping. In addition, to solve the problem of few X-steering fault sample data, Dropout technology is introduced during the model training phase to improve the performance of the DQN algorithm. Experimental results show that the proposed model has improved the convergence speed and comprehensive performance indicators compared to the unimproved DQN algorithm, with precision, recall, F _1−score, and accuracy reaching up to 100%, 98.07%, 99.02%, and 98.50% respectively, and the model’s accuracy is higher than other machine learning algorithms like back propagation, support vector machine.

As intelligent sensors for marine applications rapidly advance, there is a growing emphasis on developing efficient, low-cost, and sustainable power sources to enhance their performance. With the continuous development of triboelectric nanogenerators (TENGs), known for their simple structure and versatile operational modes, these devices exhibit promising technological potential and have garnered extensive attention from a broad spectrum of researchers. The single-electrode mode of TENGs presents an effective means to harness eco-friendly energy sourced from flowing water. In this study, the factors affecting the output performance were investigated using different structures of single-electrode solidliquid TENGs placed in a circulating water tank. In addition, the solid–liquid contact process was numerically simulated using the COMSOL Multiphysics software, and significant potential energy changes were obtained for the solid–liquid contact and liquid flow processes. Finally, the energy generated is collected and converted to power several light-emitting diodes, demonstrating that solid–liquid TENGs can generate effective electrical power in a flowing water environment. Through several experimental investigations, we finally determined that the flow rate of the liquid, the thickness of the friction electrode material, and the contact area have the most significant effect on the output efficiency of TENGs in the form of flowing water, which provides a guide for improving their performance in the future.

The need to transport goods across countries and islands has resulted in a high demand for commercial vessels. Owing to such trends, shipyards must efficiently produce ships to reduce production costs. Layout and material flow are among the crucial aspects determining the efficiency of the production at a shipyard. This paper presents the initial design optimization of a shipyard layout using Nondominated Sorting Algorithm-II (NSGA-II) to find the optimal configuration of workstations in a shipyard layout. The proposed method focuses on simultaneously minimizing two material handling costs, namely work-based material handling and duration-based material handling. NSGA-II determines the order of workstations in the shipyard layout. The semiflexible bay structure is then used in the workstation placement process from the sequence formed in NSGA-II into a complete design. Considering that this study is a case of multiobjective optimization, the performance for both objectives at each iteration is presented in a 3D graph. Results indicate that after 500 iterations, the optimal configuration yields a work-based MHC of 163 670.0 WBM-units and a duration-based MHC of 34 750 DBM-units. Starting from a random solution, the efficiency of NSGA-II demonstrates significant improvements, achieving a 50.19% reduction in work-based MHC and a 48.58% reduction in duration-based MHC.

Demand for faster vessels continues to grow, various high speed vessels have been designed and constructed for military, recreational, and passenger use. Planing vessels, specifically engineered for high-speed travel, require optimization to improve their hydrodynamic performance and stability during design. Reducing resistance and improving longitudinal stability are key challenges in the design of high-speed vessels. Various methods are employed to overcome these challenges, with the use of a transverse step being one of the most common approaches. This study explores the effect of changing the angle of the aft-wise step and incorporates these changes into existing analytical formulas, resulting in new formulas specifically for high-speed vessels equipped with aft-wise steps. This research investigates how the angle of the transverse step affects the hydrodynamic performance and longitudinal stability of high-speed vessels. Based on the results, analytical formulas have been developed to calculate the wetted surface parameters of vessels equipped with an aft-wise transverse step. The study used experimental methods to analyze the vessel’s behavior with six different aft-wise transverse step angles of 0°, 9°, 11°, 13°, 15°, and 17° at three speeds of 8, 10, and 12 m/s. In the experimental tests, the hydrodynamic components of resistance, trim angle, and wetted surface of the vessel were measured. Results indicate that creating an angle in the transverse step substantially improves the hydrodynamic components and longitudinal stability of the vessel. At the optimal angle, the resistance and trim angle of the vessel were reduced by 7.8% and 12.8%, respectively, compared to the base vessel. Additionally, the existing analytical methods for calculating the wetted surface area are more accurate than similar methods

The position deviation of the underwater manipulator generated by vortex-induced vibration (VIV) in the shear flow increases relative to that in the uniform flow. Thus, this study established an experimental platform to investigate the vibration characteristics of the underwater manipulator under shear flow. The vibration response along the manipulator was obtained and compared with that in the uniform flow. Results indicated that the velocity, test height, and flow field were the main factors affecting the VIV of the underwater manipulator. With the increase in the reduced velocity (U _r), the dimensionless amplitudes increased rapidly in the in-line (IL) direction with a maximum of 0.13D. The vibration responses in the cross-flow (CF) and IL directions were concentrated at positions 2, 3 and positions 1, 2, with peak values of 0.46 and 0.54 mm under U _r = 1.54, respectively. In addition, the vibration frequency increased with the reduction of velocity. The dimensionless dominant frequency in the CF and IL directions varied from 0.39–0.80 and 0.35–0.64, respectively. Moreover, the ratio of the CF and IL directions was close to 1 at a lower U _r. The standard deviation of displacement initially increased and then decreased as the height of the test location increased. The single peak value of the standard deviation showed that VIV presented a single mode. Compared with the uniform flow, the maximum and average values of VIV displacement increased by 104% and 110% under the shear flow, respectively.