With the rapid advancement of machine learning technology and its growing adoption in research and engineering applications, an increasing number of studies have embraced data-driven approaches for modeling wind turbine wakes. These models leverage the ability to capture complex, high-dimensional characteristics of wind turbine wakes while offering significantly greater efficiency in the prediction process than physics-driven models. As a result, data-driven wind turbine wake models are regarded as powerful and effective tools for predicting wake behavior and turbine power output. This paper aims to provide a concise yet comprehensive review of existing studies on wind turbine wake modeling that employ data-driven approaches. It begins by defining and classifying machine learning methods to facilitate a clearer understanding of the reviewed literature. Subsequently, the related studies are categorized into four key areas: wind turbine power prediction, data-driven analytic wake models, wake field reconstruction, and the incorporation of explicit physical constraints. The accuracy of data-driven models is influenced by two primary factors: the quality of the training data and the performance of the model itself. Accordingly, both data accuracy and model structure are discussed in detail within the review.

Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand, and the blade is the core component in electricity generation from the ocean current. However, the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current, even resulting in blade fatigue and destructively interfering with grid stability. A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio (HDR). However, HDR is difficult to obtain due to the complex fluid–structure interaction (FSI). Therefore, a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures. The experimental and simulation methods used to identify and obtain the HDR quantitatively were described, placing emphasis on the experimental processes and simulation setups. Moreover, the accuracy and efficiency of different simulation methods were compared, and the modal work approach was recommended. The effects of key typical parameters, including flow velocity, angle of attack, gap, rotational speed, and cavitation, on the HDR were then summarized, and the suggestions on operating conditions were presented from the perspective of increasing the HDR. Subsequently, considering multiple flow parameters, several theoretical derivations and semi-empirical prediction formulas for HDR were introduced, and the accuracy and application were discussed. Based on the shortcomings of the existing research, the direction of future research was finally determined. The current work offers a clear understanding of the HDR of blade-like structures, which could improve the evaluation accuracy of flow-induced vibration in the design stage.

Ice-breaking methods have become increasingly significant with the ongoing development of the polar regions. Among many ice-breaking methods, ice-breaking that utilizes a moving load is unique compared with the common collision or impact methods. A moving load can generate flexural-gravity waves (FGWs), under the influence of which the ice sheet undergoes deformation and may even experience structural damage. Moving loads can be divided into above-ice loads and underwater loads. For the above-ice loads, we discuss the characteristics of the FGWs generated by a moving load acting on a complete ice sheet, an ice sheet with a crack, and an ice sheet with a lead of open water. For underwater loads, we discuss the influence on the ice-breaking characteristics of FGWs of the mode of motion, the geometrical features, and the trajectory of motion of the load. In addition to discussing the status of current research and the technical challenges of ice-breaking by moving loads, this paper also looks ahead to future research prospects and presents some preliminary ideas for consideration.

This paper provides an overview of the global wave resource for energy exploration. The most popular metrics and estimators for wave energy resource characterization have been compiled and classified by levels of energy exploration. A review of existing prospective wave energy resource assessments worldwide is also given, and those studies have been collated and classified by continent. Finally, information about forty existing open sea wave energy test sites worldwide and their characteristics is depicted and displayed on a newly created global map. It has been found that wave power density is still the most consensual metric used for wave energy resource assessment purposes among researchers. Nonetheless, to accomplish a comprehensive wave resource assessment for exploitation, the computation of other metrics at the practicable, technical, and socio-economic levels has also been performed at both spatial and temporal domains. Overall, regions in latitudes between 40° and 60° of both hemispheres are those where the highest wave power density is concentrated. Some areas where the most significant wave power density occurs are in offshore regions of southern Australia, New Zealand, South Africa, Chile, the British Isles, Iceland, and Greenland. However, Europe has been the continent where most research efforts have been done targeting wave energy characterisation for exploitation.

This review paper examines the various types of electrical generators used to convert wave energy into electrical energy. The focus is on both linear and rotary generators, including their design principles, operational efficiencies, and technological advancements. Linear generators, such as Induction, permanent magnet synchronous, and switched reluctance types, are highlighted for their direct conversion capability, eliminating the need for mechanical gearboxes. Rotary Induction generators, permanent magnet synchronous generators, and doubly-fed Induction generators are evaluated for their established engineering principles and integration with existing grid infrastructure. The paper discusses the historical development, environmental benefits, and ongoing advancements in wave energy technologies, emphasizing the increasing feasibility and scalability of wave energy as a renewable source. Through a comprehensive analysis, this review provides insights into the current state and future prospects of electrical generators in wave energy conversion, underscoring their potential to significantly reduce reliance on fossil fuels and mitigate environmental impacts.

This paper presents an overview of the recent developments in hybrid wind-wave energy. With the focus on floating concepts, the possible configurations introduced in the literature are categorized and depicted, and the main conclusions obtained from the references are summarized. Moreover, offshore wind and wave resources are discussed in terms of complementarity and supplementarity, offering a new perspective to developing hybrid wind-wave energy systems that look for synergies not limited to maximizing power output. Then, the feasibility of the concepts under development is discussed in detail, with focus on technical feasibility, dynamic feasibility and limitations of the methods employed. The hybrid configurations that surpassed the experimental validation phase are highlighted, and the experimental results are summarized. By compiling more than 40 floating wind turbine concepts, new relations are drawn between power, wind turbine dimensions, platforms’ draft and displacement, which are further related to the payload allowance of the units to accommodate wave devices and onboard power take-off systems. Bearing in mind that it is a challenge to model the exact dynamics of hybrid floating wind-wave platforms, this paper elucidates the current research gaps, limitations and future trends in the field. Lastly, based on the overview and topics discussed, several major conclusions are drawn concerning hybrid synergies, dynamics and hydrodynamics of hybrid platforms, feasibility of concepts, among other regards.

Blades are important parts of rotating machinery such as marine gas turbines and wind turbines, which are exposed to harsh environments during mechanical operations, including centrifugal loads, aerodynamic forces, or high temperatures. These demanding working conditions considerably influence the dynamic performance of blades. Therefore, because of the challenges posed by blades in complex working environments, in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently, thus guaranteeing the reliability and performance of mechanical systems. Focusing on the vibration analysis of blades in rotating machinery, this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions. First, the paper outlines the development of several modeling theories for rotating blades, including one-dimensional beam theory, two-dimensional plate–shell theory, and three-dimensional solid theory. Second, the research progress in the vibrational analysis of blades under aerodynamic loads, thermal environments, and crack factors is separately discussed. Finally, the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives. The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined, aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.

The underwater anechoic coating technology, which considers pressure resistance and low-frequency broadband sound absorption, has become a research hotspot in underwater acoustics and has received wide attention to address the increasingly advanced low-frequency sonar detection technology and adapt to the working environment of underwater vehicles in deep submergence. One the one hand, controlling low-frequency sound waves in water is more challenging than in air. On the other hand, in addition to initiating structural deformation, hydrostatic pressure also changes material parameters, both of which have a major effect on the sound absorption performance of the anechoic coating. Therefore, resolving the pressure resistance and acoustic performance of underwater acoustic coatings is difficult. Particularly, a bottleneck problem that must be addressed in this field is the acoustic structure design with low-frequency broadband sound absorption under high hydrostatic pressure. Based on the influence of hydrostatic pressure on underwater anechoic coatings, the research status of underwater acoustic structures under hydrostatic pressure from the aspects of sound absorption mechanisms, analysis methods, and structural designs is reviewed in this paper. Finally, the challenges and research trends encountered by underwater anechoic coating technology under hydrostatic pressure are summarized, providing a reference for the design and research of low-frequency broadband anechoic coating.

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.

Two asymmetric types of floating breakwaters integrated with a wave energy converter (WEC-FBs), a floating square box with a triangle (trapezoidal type) or a wave baffle (L type) attached to its rear side, have been proposed. In this research, the hydrodynamic performance, including capture width ratio (CWR), wave transmission coefficient, heave motion, and force coefficient, were studied and compared between the two types. A numerical simulation model based on the Navier–Stokes equation was employed. The effects of power take-off (PTO) damping coefficient, wave periods, and draft/displacement on the hydrodynamic performance of the two structure shapes were simulated and investigated. The results reveal that the L type performs better in shorter wave periods, and the trapezoidal type exhibits a higher CWR in intermediate wave periods. This study offers knowledge of the design and protection of the two WEC-FB types.

Ship outfitting is a key process in shipbuilding. Efficient and high-quality ship outfitting is a top priority for modern shipyards. These activities are conducted at different stations of shipyards. The outfitting plan is one of the crucial issues in shipbuilding. In this paper, production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated. The uncertain factors in outfitting equipment production are usually decision-related, which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan. This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model. To address this problem, a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process. A practical case of the shipyard of China Merchants Heavy Industry Co., Ltd. is used to evaluate the performance of the proposed method. Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.

Using natural gas (NG) as the primary fuel helps alleviate the fossil fuel crisis while reducing engine soot and nitrogen oxide (NO_X) emissions. In this paper, the influences of a novel split injection concept on an NG high pressure direct injection (HPDI) engine are examined. Four typical split injection strategies, namely split pre-injection of pilot diesel (PD) and NG, split post-injection of PD and NG, split pre-injection of NG, and split post-injection of PD, were developed to investigate the influences on combustion and emissions. Results revealed that split pre-injection of NG enhanced the atomization of PD, whereas the split post-injection of NG lowered the temperature in the core region of the PD spray, resulting in the deterioration of combustion. The effect of the split injection strategy on indicated thermal efficiency exceeded 7.5%. Split pre-injection was favorable to enhancing thermal efficiency, whereas split post-injection was not. Ignition delay, combustion duration, and premixed combustion time proportion were affected by injection strategies by 3.8%, 50%, and 19.7%, respectively. Split pre-injection increased CH₄ emission in the exhaust. Split post-injection, especially split post-injection of PD and NG, reduced the unburned CH₄ emission by approximately 30%. When the split post-injection ratio was less than 30%, the trade-off between NO_X and soot was interrupted. The distribution range of hydroxyl radicals was expanded by pre-injection, and NO_X was generated in the region where the NG jet hit the wall. This paper provides valuable insights into the optimization of HPDI injection parameters.

The traditional A^* algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles (USVs). In addition, the path planned presents numerous redundant inflection waypoints, and the security is low, which is not conducive to the control of USV and also affects navigation safety. In this paper, these problems were addressed through the following improvements. First, the path search angle and security were comprehensively considered, and a security expansion strategy of nodes based on the 5×5 neighborhood was proposed. The A^* algorithm search neighborhood was expanded from 3×3 to 5×5, and safe nodes were screened out for extension via the node security expansion strategy. This algorithm can also optimize path search angles while improving path security. Second, the distance from the current node to the target node was introduced into the heuristic function. The efficiency of the A^* algorithm was improved, and the path was smoothed using the Floyd algorithm. For the dynamic adjustment of the weight to improve the efficiency of DWA, the distance from the USV to the target point was introduced into the evaluation function of the dynamic-window approach (DWA) algorithm. Finally, combined with the local target point selection strategy, the optimized DWA algorithm was performed for local path planning. The experimental results show the smooth and safe path planned by the fusion algorithm, which can successfully avoid dynamic obstacles and is effective and feasible in path planning for USVs.

An improved version of the sparse A^* algorithm is proposed to address the common issue of excessive expansion of nodes and failure to consider current ship status and parameters in traditional path planning algorithms. This algorithm considers factors such as initial position and orientation of the ship, safety range, and ship draft to determine the optimal obstacle-avoiding route from the current to the destination point for ship planning. A coordinate transformation algorithm is also applied to convert commonly used latitude and longitude coordinates of ship travel paths to easily utilized and analyzed Cartesian coordinates. The algorithm incorporates a hierarchical chart processing algorithm to handle multilayered chart data. Furthermore, the algorithm considers the impact of ship length on grid size and density when implementing chart gridification, adjusting the grid size and density accordingly based on ship length. Simulation results show that compared to traditional path planning algorithms, the sparse A^* algorithm reduces the average number of path points by 25%, decreases the average maximum storage node number by 17%, and raises the average path turning angle by approximately 10°, effectively improving the safety of ship planning paths.