J. Mar. Sci. Eng., Volume 12, Issue 5 (May 2024) – 102 articles

A moored spar platform, equipped with various instruments, serves as a crucial tool in hydrological monitoring. However, conducting dynamic analyses of a single spar that endures wind and current requires significant amount of computational time. To address this challenge, this study proposes an efficient surrogate model to represent fluid loads. A database is established to capture the relationship between fluid loads, spar displacements and uniform currents based on a numerical model of the spar. Subsequently, an artificial neural network method is employed to construct the surrogate model. Finally, the surrogate model is integrated with a numerical model of the cable, developed using the lumped mass method, to create a coupled model of the moored spar. The dynamic responses of this coupled model align closely with those obtained from the purely numerical model, demonstrating the efficacy of the surrogate model in capturing fluid loads on the spar. In addition to the surrogate model generation approach, this research provides an efficient method to couple the surrogate model with the numerical model in dynamic analysis of floating systems in uniform currents. Full article

The expansion of underwater scenarios and missions highlights the crucial need for autonomous underwater vehicles (AUVs) to make informed decisions. Therefore, developing an efficient decision-making framework is vital to enhance productivity in executing complex tasks within tight time constraints. This paper delves into task planning and reconstruction within the AUV control decision system to enable intelligent completion of intricate underwater tasks. Behavior trees (BTs) offer a structured approach to organizing the switching structure of a hybrid dynamical system (HDS), originally introduced in the computer game programming community. In this research, an intelligent search algorithm, MCTS-QPSO (Monte Carlo tree search and quantum particle swarm optimization), is proposed to bolster the AUV’s capacity in planning complex task decision control systems. This algorithm tackles the issue of the time-consuming manual design of control systems by effectively integrating BTs. By assessing a predefined set of subtasks and actions in tandem with the complex task scenario, a reward function is formulated for MCTS to pinpoint the optimal subtree set. The QPSO algorithm is then leveraged for subtree integration, treating it as an optimal path search problem from the root node to the leaf node. This process optimizes the search subtree, thereby enhancing the robustness and security of the control architecture. To expedite search speed and algorithm convergence, this paper recommends reducing the search space by pre-grouping conditions and states within the behavior tree. The efficacy and superiority of the proposed algorithm are validated through security and timeliness evaluations of the BT, along with comparisons with other algorithms for automatic AUV decision control behavior tree design. Ultimately, the effectiveness and superiority of the proposed algorithm are corroborated through simulations on a multi-AUV complex task platform, showcasing its practical applicability and efficiency in real-world underwater scenarios. Full article

Using shallow-water buoy observations, reanalysis data, and numerical models, this study analyzes the variations in sea temperature and significant wave height (SWH) caused by two sequential tropical cyclones (TCs) ‘Lionrock’ and ‘Kompasu’ in October 2021 in the northeast Beibu Gulf, South China Sea. The results show that the sea surface temperature (SST) cooling of the nearshore waters was larger than the offshore water in the basin of the gulf, with the cooling amplitude and rate decreasing and the cooling time lagging behind wind increasing from coast to offshore. The near-surface temperature at the buoy station had a maximum decrease of 2.8 °C after ‘Lionrock’, and the decrease increased slightly to 3 °C after the stronger wind of ‘Kompasu’. The total decrease of 4.6 °C indicates that the sequential TCs had a superimposed effect on the cooling of the Beibu Gulf. The heat budget analysis revealed that the sea surface heat loss and the Ekman pumping rate in the nearshore waters during ‘Kompasu’ (−535 W/m² and 5.8 × 10⁻⁴ m/s, respectively) were significantly higher than that (−418 W/m² and 4 × 10⁻⁴ m/s) during ‘Lionrock’. On the other hand, the SST cooling (−1.2 °C) during the second TC is smaller than (−1.6 °C) the first weaker TC in the gulf basin, probably due to the deepening of the mixed layer. During the observation period, the waves in the Beibu Gulf were predominantly wind-driven. The maximum SWHs reached 1.58 m and 2.3 m at the bouy station near shore during the two TCs, and the SWH variation was highly correlated to the wind variation with a correlation of 0.95. The SWH increases from the nearshore to offshore waters during the TCs. The SAWN and ARCIRC coupled model results suggest that wave variations in the Beibu Gulf are primarily influenced by water depth, bottom friction, and whitecapping. Two days after the TCs, sea surface cooling and high waves appeared again due to a cold air event. Full article

This paper conducted a computational study on the KCS benchmark model at static drift conditions. At the first instance, the roles played by the grid size, turbulence model, and time step are qualitatively and quantitatively analyzed with the orthogonal experimental method (OEM). After the verification of simulated results compared with experimental data in a Static Oblique Towing Test (OTT), hydrodynamic performance is obtained with the employment of the SST κ-ω turbulence model. The grid size is set as 0.07 m while the time step as 0.01 s. The characteristics of the wake field are illustrated in different forms, such as contours of the free surface, distribution of pressure and hydrodynamic forces, variation of turbulent kinetic energy (TKE), and so on. For a deep insight into the physical mechanisms of the asymmetrical flow field, the Detached Eddy Simulation (DES) method is also utilized to capture vortical structures occurring around the hull, in comparison with results obtained through the Reynolds Averaged Navier Stokes (RANS) model. With the aim of a hydrodynamic derivative estimation or detailed flow characteristics analysis, corresponding selections of the computational method are disparate. Full article

In response to the anticipated scarcity of terrestrial land resources in the coming years, the acquisition of marine mineral resources is imperative. This paper mainly summarizes the development of underwater collection and transportation equipment of polymetallic nodules in deep-sea mining. Firstly, the collection equipment is reviewed. The deep-sea mining vehicle (DSMV), as the key equipment of the collection equipment, mainly includes the collecting device and the walking device. The micro and macro properties of sediments have a great influence on the collection efficiency of mining vehicles. For the collecting device, the optimization of the jet head structure and the solid–liquid two-phase flow transport of the hose are discussed. The structure of the walking device restricts mining efficiency. The optimization of the geometric structure is studied, and the geometric passability and lightweight design of the walking device are discussed. Secondly, the core of transportation equipment is the lifting device composed of a riser and lifting pump. In order to explore the key factors affecting mineral transport, the lifting device is summarized, and the design optimization of the lifting pump and the factors affecting the stability of the riser are discussed. Then, the relationship between each device is discussed, and the overall coupling of the device is summarized. Finally, the existing problems and future research focus are summarized. Full article

Industrial farming is one of the main farming systems used for L. vannamei, and it is also the main direction of development in the future. To investigate the role of the bacterial community in nitrogen transformation in industrial L. vannamei farming systems, we studied the concentration of nitrogen compounds, the bacterial community using 16S rRNA sequencing, and nitrogen cycling genes’ abundance using absolute quantitative PCR in aquaculture water (using seawater (WD) and groundwater mixed with seawater (CY)) and analyzed the correlations between them using a person analysis. The results showed that the bacterial α-diversity index (ACE, Shannon, and Sobs) significantly changed during culture in WD but not in CY. Bacterial community species composition analysis and linear discriminant analysis effect size (LEfSe analysis) revealed that Cyanobiaceae and Microbacteriaceae were the dominant bacteria and biomarkers in WD. Vibrionaceae, Ateromonadaceae, Microbacteriaceae, Saprospiraceae, and Cryomorphaceae were the dominant bacteria and biomarkers in CY. A functional annotation of procaryotic taxa (FAPROTAX) analysis revealed that the bacterial community in WD exhibited a greater phototrophic activity at early culture stages, while at the same stage, CY exhibited strong nitrate reduction. A correlation analysis of nitrogen cycling genes and environmental factors revealed that napA, narG, ureC, amoA, and nirK were significantly correlated with the concentrations of total ammonia nitrogen (TAN), nitrite (NO₂⁻-N), nitrate (NO₃⁻-N), and total nitrogen (TN) in WD. In CY, amoA was positively correlated and napA and nirK were negatively correlated with TAN and TN concentrations. A correlation analysis between bacterial abundance and environmental factors revealed that Flavobacteriaceae, Saprospiraceae, Cryomorphaceae, Cyanobiaceae, Halieaceae, and Cyclobacteriaceae were significantly correlated with the concentrations of TAN and NO₂⁻-N. The above results indicated that the bacterial community in industrial shrimp farming systems changed under different conditions, with consequent changes in the abundance of genes being involved in the nitrogen cycle and in this biogeochemical process in the water. Our study facilitates further understanding of microbes and their functions in nitrogen cycling in industrial shrimp farming systems. Full article

Folate, also known as vitamin B9, plays a crucial role in the one-carbon (1C) metabolism, a conserved pathway from microbes to humans. The 1C metabolism, consisting of the folate and methionine cycles, is essential in many biological processes such as nucleotide and protein biosynthesis, cell proliferation, and embryonic development. Despite its functional role, little is known about the 1C metabolism in crustaceans. As part of an ongoing effort to characterize important pathways in Calanus finmarchicus, the biomass-dominant zooplankton in much of the North Atlantic Ocean, we identified transcripts encoding the 1C metabolism enzymes. Using an in silico workflow consisting of a transcriptome mining, reciprocal blasts, and structural analyses of the deduced proteins, we identified the entire set of enzymes in both cycles. The majority encoded for full-length proteins and clustered with homologs from other species. Stage-specific expression was reported, with several transcripts showing high expression in the naupliar stage (e.g., 10-FTHFD, SHMT2) while some methyltransferases (e.g., BHMT, SHMT, DNMT) were more expressed in adults. Overall, this study provides a set of genes which can be used as potential biomarkers of development and reproduction and can be tested in other zooplankters to assess ocean health status monitoring. Full article

Wave-induced seabed liquefaction significantly jeopardizes the stability of marine structures and the safety of human life. Susceptibility assessment is key to enabling spatial predictions and establishing a solid foundation for effective risk analysis and management. However, the current research encounters various challenges, involving an incomplete evaluation system, poor applicability of methods, and insufficient databases. These issues collectively hinder the accuracy of susceptibility assessments, undermining their utility in engineering projects. To address these challenges, a susceptibility assessment method with the safety factor was developed as the key assessment parameter, allowing for a comprehensive susceptibility assessment across the silt-dominated nearshore environment using Empirical Bayesian Kriging (EBK). The safety factor is determined by combining the cyclic stress ratio (CSR) and the cyclic resistance ratio (CRR), which characterize wave loadings and sediment properties in the study area, respectively. This method was applied in the Chengdao region of the Yellow River Estuary, China, a typical silt-dominated nearshore environment where wave-induced liquefaction events have been reported as being responsible for multiple oil platform and pipeline accidents. By collecting the regional wave and seabed sediment data from cores spanning from 1998 to 2017, the safety factors were calculated, and a zonal map depicting the susceptibility assessment of wave-induced seabed liquefaction was created. This study can serve as a valuable reference for the construction and maintenance of marine engineering in liquefaction-prone areas. Full article

Aiming at the problems of large statistical error and the poor real-time performance of catch weight in the ocean fishing tuna industry, an algorithm based on improved YOLOv8-Pose for albacore tuna (Thunnus alalunga) fork length extraction and weight estimation is proposed, with reference to the human body’s pose estimation algorithm. Firstly, a lightweight module constructed using a heavy parameterization technique is used to replace the backbone network, and secondly, a weighted bidirectional feature pyramid network BIFPN is utilized. Finally, the upper and lower jaw and tail feature points of the albacore tuna (Thunnus alalunga) were extracted using the key point detection algorithm, and the weight of the albacore tuna (Thunnus alalunga) was estimated based on the fitted relationship between fork length and weight. The experimental results show that the improved YOLOv8-Pose algorithm reduces the number of model parameters by 13.63% and the number of floating-point operations by 14.03% compared with the baseline model without decreasing the accuracy of the target detection and key point detection and improves the model inference speed by 374%. At the same time, it reduces the drift of the key point detection, and the error of the comparison with the actual albacore tuna (Thunnus alalunga) body weight is not more than 10%. The improved key point detection algorithm has high detection accuracy and inference speed, which provides accurate yield data for pelagic fishing and is expected to solve the existing statistical problems and improve the accuracy and real-time performance of data in the fishing industry. Full article

The k-omega SST turbulence model is extensively employed in Reynolds-averaged Navier–Stokes (RANS)-based Computational Fluid Dynamics (CFD) calculations. However, the accuracy of the estimation of viscous resistance and companion flow distribution for full-sized vessels is not sufficient. This study conducted a computational analysis of the flow around the Ryuko-maru at model-scale and full-scale Reynolds numbers utilizing the Reynolds stress turbulence model (RSM). The obtained Reynolds stress distribution from the model-scale computation was compared against experimental measurements to assess the capability of the RSM. Furthermore, full-scale computations were performed, incorporating the influence of hull surface roughness, with the resulting wake distributions juxtaposed with the actual ship measurements. The full-scale calculation employed the sand-grain roughness function, and an optimal roughness length scale was determined by aligning the computed wake distribution with Ryuko-maru’s measured data. The results of this study will allow for the direct performance estimation of full-scale ships and contribute to the design technology of performance. Full article

In the realm of underwater environment detection, achieving information matching stands as a pivotal step, forming an indispensable component for collaborative detection and research in areas such as distributed mapping. Nevertheless, the progress in studying the matching of underwater side-scan sonar images has been hindered by challenges including low image quality, intricate features, and susceptibility to distortion in commonly used side-scan sonar images. This article presents a comprehensive overview of the advancements in underwater sonar image processing. Building upon the novel SchemaNet image topological structure extraction model, we introduce a feature matching model grounded in side-scan sonar images. The proposed approach employs a semantic segmentation network as a teacher model to distill the DeiT model during training, extracting the attention matrix of intermediate layer outputs. This emulates SchemaNet’s transformation method, enabling the acquisition of high-dimensional topological structure features from the image. Subsequently, utilizing a real side-scan sonar dataset and augmenting data, we formulate a matching dataset and train the model using a graph neural network. The resulting model demonstrates effective performance in side-scan sonar image matching tasks. These research findings bear significance for underwater detection and target recognition and can offer valuable insights and references for image processing in diverse domains. Full article

A large number of research stations have been established to provide members of Antarctic expeditions with logistical support. A previous study confirmed that the wind and solar energy resources of the Chinese Zhongshan Station, a coastal station located in an area of Lassmann Hills in East Antarctica, are highly synergetic and complementary. Considering the demand for a renewable energy power supply in Zhongshan Station, this paper introduces a hybrid energy system with wind–solar–diesel–battery co-generation used as a power supply scheme. Based on the 2015 climate data for Zhongshan Station, the wind–solar resources, conventional energy system, and annual diesel consumption of the station area were analyzed. The annual electrical load demand of each building in the station area was quantitatively expounded. Compared with the original power supply system, and combined with the analysis results of the thermal load and electrical load demands of the station, an objective function based on the requirements of economy, reliability, and environmental protection was presented. According to the constraint conditions of the heat energy and electrical energy load balance in the station area, a multi-objective scheduling strategy for the system was designed. Finally, the effects of this scheduling strategy were analyzed under three different application scenarios. The results indicated that the annual load demand was significantly lower than before the scheduling, and that a 50% reduction in diesel consumption could be achieved, demonstrating that the multi-objective scheduling strategy proposed in this paper could achieve optimal energy scheduling and management of the renewable hybrid energy system. Full article

The resistance performance of amphibious vehicles can be improved by installing underwater tail hydrofoils. The research on the impact of different hydrofoil profiles on the resistance characteristics of amphibious vehicles can provide a reference for the vehicle’s design. For an amphibious vehicle model, five shapes of symmetrical hydrofoils, NACA0012, NACA0015, NACA0016, and asymmetric hydrofoils NACA23012, NACA66-209, were selected as the underwater tail wing of the vehicle body, respectively. Based on the RANS method and overset grid technology, the resistance performance of the vehicle body was numerically calculated, and the resistance variation in the amphibious vehicle equipped with different tail hydrofoils at 0.43 < Fr_∇ < 1.3 speed was obtained. The basic shape of amphibious vehicle tail wings can be determined by comparing the effects of symmetrical hydrofoils and asymmetric hydrofoils on body resistance. The results show that the asymmetric hydrofoils have a better resistance reduction effect on amphibious vehicles than the symmetrical ones. Among them, an amphibious vehicle installing the asymmetric hydrofoil NACA66-209 as an underwater tail wing can reduce resistance by 44.3%. Chord length is an important factor affecting the resistance reduction performance of tail wings. When Fr_∇ = 1.3, the asymmetric hydrofoil optimized based on chord length has a 21.2% higher resistance reduction effect on amphibious vehicles. Full article

Luxury cruise ships are high-end passenger ships with facilities on board for the leisure and entertainment of passengers, so the comfort of luxury cruise ships is a matter of great concern. In this paper, a finite element model of a new polar exploration cruise ship is established, and the wet modes of the whole ship are calculated using the virtual mass method and compared with the principal frequencies of the excitation forces to initially verify the rationality of the design of the structural vibration characteristics of the whole ship. The admittance matrix of the vibration velocity to excitation force was calculated by a frequency response analysis, and the vibration velocities at the stern plate and main engine foundations were tested during sailing. Then, the obtained propeller and main engine excitation forces were loaded into the finite element model; the vibration velocities of each compartment were calculated and compared with the compartment vibration velocity test values. The errors were within the engineering allowable range, verifying the accuracy of the excitation forces. The propeller and main engine excitation forces were loaded separately on the finite element model to calculate the vibration velocity of each cabin, and the contribution of the two excitation sources to the vibration velocity of each cabin was analyzed. It was found that the contribution of the excitation source to the cabin response was related to the relative position between the cabin and the excitation source. When the cabin was located in the cabin adjacent to or directly above a certain excitation source, the contribution of the excitation source to the cabin response was greater. When the cabin was farther away from both excitation sources, the contribution of the propeller excitation was greater. This provides a targeted reference for the preliminary vibration assessment and later vibration control of the new polar expedition cruise ship. Full article

In this study, a set of accurate dispersive nonlinear wave equations is established, using the wave velocity and free surface elevation as variables. These equations improve upon previous equations in which the velocity potential is used as a variable by considering the rotational wave motion and by adding a second-order bottom slope term that applies to general situations, allowing the equations to consider the influence of rapidly changing, horizontal, two-dimensional bottom topographies. The problem of the inaccuracy of the integral calculations used in previous equations in nearshore areas is solved by approximating the integral calculations into differential calculations, and a set of coupled wave equations is established by keeping the free surface elevation and the horizontal velocity constant, thus allowing the calculation of nearshore wave-generated currents. The benefits of the current model are confirmed through comparisons with corresponding laboratory experimental findings and are illustrated through a comparison with the numerical outcomes of other pertinent models. Full article

Sediment erosion damage is one of the main causes of structural failure in reaction turbine units. To study the mechanism through which sediment erosion affects the water-guiding mechanism of a reaction turbine unit, this study obtained the average concentration and particle size of sediment during the flood season based on the statistics of the measured sediment data from the power station. Additionally, the characteristics of the solid–liquid two-phase flow of the diversion components of the reaction hydraulic turbine were numerically calculated. Based on the velocity triangle change in the guide apparatus and the flow similarity principle, a flow-around wear test device for the guide apparatus of the reaction turbine was designed. Furthermore, the similarity of the sand–water flow field between the guide apparatus of the prototype unit and the test device was compared and analyzed. The results demonstrated that the sand–water flow field of the diversion components of the prototype unit was axisymmetric and exhibited a potential flow distribution. Additionally, uniform sand–water flow occurred within the guide apparatus, with a small sand–water velocity gradient near the wall of the stay vanes (SV) and the guide vanes (GV). The maximum volume fraction of sediment particles was observed in the tailing area of the spiral casing, indicating an enrichment phenomenon of sediment particles. The velocity of the sediment particles on the surface of the guide vane in the single-channel sediment wear test device and prototype unit ranged from 6.2 to 7.8 m/s, and the velocity of the sediment particles on the surface of the stay vane ranged from 5.1 to 14.6 m/s, and the difference of the sediment particles’ velocity near the wall was 1 to 3 m/s. The trailing vorticity of the guide vane reached a maximum of 120 s⁻¹. Consequently, the single-channel sediment erosion test device can unveil the sediment erosion mechanism of the guide apparatus of a reaction turbine. Full article

Chlorinated organic compounds, as contaminants in marine fuels, have caused severe damage, affecting both main and auxiliary engines. Contaminated fuels can cause serious damage to an engine and its components, corroding fuel pumps and blocking filters, for example. This affects the operation of the engine, and, in the most severe cases, vessel safety. This study considered fossil diesel containing hydrochloric acid as a possible product formed under certain conditions in fuel contaminated with COCs and its effects on carbon steel, stainless steel, tempering steel, and aluminum. Five fuel samples with different concentrations of hydrochloric acid were prepared, plus one sample of diesel and water. Metal bars were partially immersed in the fuel samples and stored at room temperature for approximately one month. A visual assessment found corrosion across the entire surface of all metal bars when exposed to fuel samples containing hydrochloric acid. Even the smallest acid content (25 ppm) caused corrosion, and the effects were already observable after only two days of exposure. Despite their acid contamination, the measured fuel properties fulfilled the standard for automotive fuels at the beginning of the test. The water in the diesel sample did not cause any visible corrosion. Full article

This study investigates the effects of the gulf stream (GS) on sea-level oscillations across various time scales and assesses the performance of a coastal and estuarine model nested within a global model in simulating these variations. It aims to improve boundary conditions to simulate sea-level oscillations more accurately by considering the influence of GS flow. An inverse correlation is observed between observed sea-level oscillation and GS flow, which becomes more pronounced over longer time scales. Using Delft3D, a high-resolution coastal and estuarine model is developed to simulate circulation dynamics in the central Indian River Lagoon (IRL), FL, and adjacent coastal areas on the Florida east coast. The model is nested into the HYCOM (Hybrid Coordinate Ocean Model), and meteorological forcings are derived from the NARR (North American Regional Reanalysis) model. The model demonstrates satisfactory performance across key parameters, including tide, salinity, water temperature, and currents. However, there remains a noticeable difference between the modeled and observed data. To address this, the model is executed with modified flow boundary conditions at eastern boundary nodes, integrating HYCOM tide, and observing low-frequency sea-level variations. The implementation of the new boundary conditions results in an improved simulation of sea-level oscillations. This study presents the conceptual framework and detailed methodologies employed in the creation of a high-resolution model tailored for estuarine and coastal areas nested into global models capable of satisfactorily simulating sea-level oscillations even when the global model does not represent GS effects. Full article

Oceanic energy sources, notably offshore wind and wave power, present a significant opportunity to generate green hydrogen through water electrolysis. This approach allows for offshore hydrogen production, which can be efficiently transported through existing pipelines and stored in various forms, offering a versatile solution to tackle the intermittency of renewable energy sources and potentially revolutionize the entire electrical grid infrastructure. This research focusses on assessing the technical and economic feasibility of this method in six strategic coastal regions in Morocco: Laayoune, Agadir, Essaouira, Eljadida, Casablanca and Larache. Our proposed system integrates offshore wind turbines, oscillating water column wave energy converters, and PEM electrolyzers, to meet energy demands while aligning with global sustainability objectives. Significant electricity production estimates are observed across these regions, ranging from 14 MW to 20 MW. Additionally, encouraging annual estimates of hydrogen production, varying between 20 and 40 tonnes for specific locations, showcase the potential of this approach. The system’s performance demonstrates promising efficiency rates, ranging from 13% to 18%, while maintaining competitive production costs. These findings underscore the ability of oceanic energy-driven green hydrogen to diversify Morocco’s energy portfolio, bolster water resilience, and foster sustainable development. Ultimately, this research lays the groundwork for comprehensive energy policies and substantial infrastructure investments, positioning Morocco on a trajectory towards a decarbonized future powered by innovative and clean technologies. Full article

Underwater acoustic communication is fraught with challenges, including signal distortion, noise, and interferences unique to aquatic environments. This study aimed to advance the field by developing a novel underwater modem system that utilizes machine learning for signal classification, enhancing the reliability and clarity of underwater transmissions. This research introduced a system architecture incorporating a Lattice Semiconductors FPGA for signal modulation and a half-pipe waveguide to emulate the underwater environment. For signal classification, support vector machines (SVMs) were leveraged with the continuous wavelet transform (CWT) employed for feature extraction from acoustic signals. Comparative analysis with traditional signal processing techniques highlighted the efficacy of the CWT in this context. The experiments and tests carried out with the system demonstrated superior performance in classifying modulated signals under simulated underwater conditions, with the SVM providing a robust classification despite the presence of noise. The use of the CWT for feature extraction significantly enhanced the model’s accuracy, eliminating the need for further dimensionality reduction. Therefore, the integration of machine learning with advanced signal processing techniques presents a promising research line for overcoming the complexities of underwater acoustic communication. The findings underscore the potential of data mining methodologies to improve signal clarity and transmission reliability in aquatic environments. Full article

In this paper, a downlink energy efficiency maximization problem is investigated in an intelligent reflective surface (IRS)-assisted visible light communication system. In order to extend wireless communication coverage of the onshore base station, an IRS mounted on a unmanned aerial vehicle (UAV) is introduced to assist an onshore lighthouse with simultaneously providing remote ship users wireless communication services and illumination. Aiming to maximizing the energy efficiency of the proposed system, a resource allocation problem is formulated as the ratio of the achievable system sum rate to the total power consumption under the constraints of the user’s data requirement and transmit power budget. Due to the non-convexity of the proposed problem, the Dinkelbach method and mean-square error (MSE) method are adopted to turn the non-convex origin problem into two equivalent problems, namely transmit beamforming and reflected phase shifting. The Lagrangian method and semidefinite relaxation technique are used to obtain the closed-form solutions of these two subproblems. Accordingly, an alternative optimization-based resource allocation scheme is proposed to obtain the optimal system energy efficiency. The simulation results show that the proposed scheme performs better in terms of energy efficiency over benchmark schemes. Full article

The coast of São Paulo, Brazil, is exposed to storm surges that can cause damage and floods. These storm surges are produced by slowly traveling cyclone–anticyclone systems. The motivation behind this work was the need to evaluate high-resolution forecasts of the mean sea-level pressure and 10 m winds, which are the major drivers of the wave model. This work is part of the activity in devising an early warning system for São Paulo coastal storm surges. For the evaluation, four case studies that had a major impact on the coast of São Paulo in 2020 were selected. Because storm surges that reach the coast may cause coastal flooding, precipitation forecasts were also evaluated. The mesoscale Eta model produces forecasts with a 5 km resolution for up to an 84 h lead time. The model was set up in a region that covers part of southeast and south Brazil. The ERA5 reanalysis was used to describe the large-scale synoptic conditions and to evaluate the weather forecasts. The cases showed a region in common between 35° S, 40° S and 35° W, 45° W where the low-pressure center deepened rapidly on the day before the highest waves reached the coast of São Paulo, with a mostly eastward, rather than northeastward, displacement of the associated surface cyclone and minimal or no tilt with height. The winds on the coast were the strongest on the day before the surge reached the coast of São Paulo, and then the winds weakened on the day of the maximum wave height. The pattern of the mean sea-level pressure and 10 m wind in the 36 h, 60 h, and 84 h forecasts agreed with the ERA5 reanalysis, but the pressure was slightly underestimated. In contrast, the winds along the coast were slightly overestimated. The 24 h accumulated precipitation pattern was also captured by the forecast, but was overestimated, especially at high precipitation rates. The 36 h forecasts showed the smallest error, but the growth in the error for longer lead times was small, which made the 84 h forecasts useful for driving wave models and other local applications, such as an early warning system. Full article

This work focuses on the modeling of a zero-emissions, high-speed catamaran ferry employing a full-electric propulsion system. It addresses the global emphasis on full-electric vessels to align with IMO regulations regarding ship emissions and energy efficiency improvement. Using the AVL Cruise-M software, this research verified the implementation of an onboard fuel cell power-generating system integrated with a propulsion plant, aiming to assess its dynamic performance under load variations. The catamaran was 30 m long and 10 m wide with a cruise speed of 20 knots. The power system consisted of a proton-exchange membrane fuel cell (PEM) system, with a nominal power of 1600 kWe, a battery pack with a capacity of 2 kWh, two 777 kW electric motors, and their relative balance of the plant (BoP) subsystems. The simulation results show that the battery effectively supported the PEM during the maneuvering phase, enhancing its overall performance and energy economy. Full article

Maritime traffic is increasing more and more, creating more complex navigation environments for ships. Ship trajectory prediction based on historical AIS data is a vital method of reducing navigation risks and enhancing the efficiency of maritime traffic control. At present, employing machine learning or deep learning techniques to construct predictive models based on AIS data has become a focal point in ship trajectory prediction research. This paper systematically evaluates various trajectory prediction methods, spanning classical machine learning approaches and emerging deep learning techniques, to uncover their respective merits and drawbacks. In this work, a variety of studies were investigated that applied different algorithms in ship trajectory prediction, including regression models (RMs), artificial neural networks (ANNs), Kalman filtering (KF), and random forests (RFs) in machine learning, along with deep learning such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), gate recurrent unit (GRU) networks, and sequence-to-sequence (Seq2seq) networks. The performance of predictive models based on different algorithms in trajectory prediction tasks was graded and analyzed. Among the existing studies, deep learning methods exhibit significant performance and considerable potential application value for maritime traffic systems, which can be assessed by future work on ship trajectory prediction research. Full article

Coral reefs are effective natural flood barriers that protect adjacent coastal communities. As the need to adapt to rising sea levels, storms, and environmental changes increases, reef restoration may be one of the best tools available to mitigate coastal flooding along tropical coastlines, now and in the future. Reefs act as a barrier to incoming short-wave energy but can amplify low-frequency infragravity waves that, in turn, drive coastal flooding along low-lying tropical coastlines. Here, we investigate whether the spacing of reef restoration elements can be optimized to maximize infragravity wave energy dissipation while minimizing the number of elements—a key factor in the cost of a restoration project. With this goal, we model the hydrodynamics of infragravity wave dissipation over a coral restoration or artificial reef, represented by a canopy of idealized hemispherical roughness elements, using a three-dimensional Navier–Stokes equations solver (OpenFOAM). The results demonstrate that denser canopies of restoration elements produce greater wave dissipation under larger waves with longer periods. Wave dissipation is also frequency-dependent: dense canopies remove wave energy at the predominant wave frequency, whereas sparse canopies remove energy at higher frequencies, and hence are less efficient. We also identify an inflection point in the canopy density–energy dissipation curve that balances optimal energy losses with a minimum number of canopy elements. Through this work, we show that there are an ideal number of restoration elements per across-shore meter of coral reef flat that can be installed to dissipate infragravity wave energy for given incident heights and periods. These results have implications for designing coral reef restoration projects on reef flats that are effective both from a coastal defense and costing standpoint. Full article

With the increasing warming of the Arctic, the summertime ice-free period in the coastal Arctic becomes longer and the water exchange between arctic lagoons and coastal Beaufort Sea becomes more important for land–ocean interaction. This study examined the dynamics of water exchange between the arctic lagoons and the Arctic Ocean under the influence of weather systems (the transient arctic cyclones and hovering Beaufort High pressure system). We implemented rare observations, numerical modeling with the Finite Volume Community Ocean Model (FVCOM), and a forcing-response Empirical Orthogonal Function (fr-EOF) analysis to determine the weather-driven flow patterns and characteristics in the micro-tidal arctic lagoon (Elson Lagoon) with little freshwater discharge. The results were validated for both tidal and subtidal currents with in situ data. The inlets of the lagoon were significantly impacted by wind associated with the weather systems and the flows through the inlets were highly correlated with each other. The fr-EOF analysis for the 1.5-month FVCOM output indicated three significant modes of wind-driven flow. In the deepest (~16 m) northwestern-most inlet, a counter-wind flow occurred more than 96% of the time due to setup and set down of water level inside the lagoon and the vorticity balance related to the wind stress and water depth. For about 60–80% of the time, the exchange flow was out of the lagoon through the northwestern-most and deepest inlet due to the strong easterly winds dictated by the Beaufort High; this dominant flow is mainly caused by the persistent easterly wind as a limb of the Beaufort High pressure system, modified by the transient arctic cyclones with a westerly wind and inward flows at the westernmost inlet of Elson Lagoon. This study shows that the alternating influence from the cyclone-anticyclone weather systems produces a meteorological tide in the subtidal spectrum which dominates the water exchange in the region through the multiple inlets. With the observed increase in cyclone strength and frequency under the warming trend, this may imply a greater contribution from the westerly wind because of the increased cyclonic activities. If this is the case, the inward flow might increase and have an effect on sediment, larval, and nutrient transports through this system. Full article

As some of the most threatened ecosystems in the world, the declining condition and coverage of coastal habitats results in the loss of the myriad ecosystem services they provide. Due to the variability in physical and biological characteristics across sites, it is imperative to increase location-based information to inform local management projects, which will potentially help to reestablish functions of coastal habitats. Since oysters are often used in restoration projects, this study quantified spatial and temporal patterns in eastern oyster spat settlement in a bar-built estuary in northeast Florida, USA that is host to a robust population of intertidal oyster reefs. Spat settlement was found to occur from April to October with small peaks in the spring and large ones around September. Inter-annual differences in spat settlement were likely influenced by existing environmental conditions and heavily affected by large-scale events such as tropical cyclones. Variations in regional spat settlements are possibly driven by the residence times of the watersheds, the density of adult populations, and the location of the spat collectors. The results of this study illustrate place-based variability in oyster settlement patterns and underscore the importance of local monitoring for oyster resource management, restoration, and research. Full article

When an unmanned surface vehicle (USV) navigates in narrow waterway scenarios, its ability to detect vanishing points accurately and quickly is highly important for safeguarding its navigation safety and realizing automated navigation. We propose a novel approach for detecting vanishing points based on an improved lightweight AlexNet. First, a similarity evaluation calculation method based on image texture features is proposed, by which some scenarios are selected from the filtered Google Street Road Dataset (GSRD). These filtered scenarios, together with the USV Inland Dataset (USVID), compose the training dataset, which is manually labeled according to a non-uniformly distributed grid level. Next, the classical AlexNet was adjusted and optimized by constructing sequential connections of four convolutional layers and four pooling layers and incorporating the Inception A and Inception C structures in the first two convolutional layers. During model training, we formulate vanishing point detection as a classification problem using an output layer with 225 discrete possible vanishing point locations. Finally, we compare and analyze the labeled vanishing point with the detected vanishing point. The experimental results show that the accuracy of our method and the state-of-the-art algorithmic vanishing point detector improves, indicating that our improved lightweight AlexNet can be applied in narrow waterway navigation scenarios and can provide a technical reference for autonomous navigation of USVs. Full article

The motion responses, mooring tensions, and submergence depth are the dominant factors for the arrangement of the Submerged Floating Tunnel (SFT) subjected to waves. Generally, the maximum values of motion responses, mooring tensions, and absolute submergence depth are mainly focused on. In the present study, experiments are implemented to measure the motion responses and mooring tensions of the SFT with different mooring patterns and submergence depths under waves with different characteristic wave heights and periods. In order to evaluate the arrangement of the SFT more effectively and comprehensively, besides the maximum values, several new characteristic parameters are introduced. Such parameters account for the motion responses in the frequency domain, the uniformity of the tension distribution, the length of time during which the cable reaches a relaxed condition during wave action, the KC number, the dimensionless period, the wave height, and the submergence depth. The results from the optimization analysis show the following: according to the characteristic values of motion responses and mooring tensions, the pattern of diagonal cables is better than that of diagonal cables + vertical cables; and within the range of the present experiments, there are optimal dimensionless parameters—the dimensionless submergence depth d₀/L_P ≥ 0.15, the KC number ≤ 0.8, or the dimensionless wave height Hs/d₀ ≤ 0.10—for the condition of which the dynamic responses and mooring tensions vary slightly. Full article

The sandstone-type uranium deposit of the Kelulun Depression is the first industrially valuable uranium deposit discovered in the Hailar Basin. This study performed a systematic examination of 17 sandstone samples from the Yimin Formation in the Kelulun Depression based on various analytical techniques. The findings of the current study were synthesized with previous research to investigate the impact of the redox conditions and the tectonic background of the source area, as well as the paleoclimatic evolution of the Yimin Formation on uranium mineralization. The elemental Mo, U/Th, V/Cr, Ni/Co, and V/(V+Ni) ratios indicate that the paleowater was in an oxygen-rich environment during the deposition of the Yimin Formation. Additionally, the C-value, Sr/Cu, Al₂O₃/MgO, and Rb/Sr ratios indicate that the Yimin Formation was formed in a paleoclimate characterized by arid-to-semi-arid conditions. The geochemical characteristics of the observed elements indicated that the sediment source of the Yimin Formation was mainly felsic rocks from the upper continental crust, the weathering of the rock was weak, and the tectonic background was a passive continental margin. Coffinite is distributed in the form of cementation and stellates within or around pyrite crystals, and uranium-titanium oxide is mostly distributed in an irregular granular distribution in the biotite cleavage fractures of the study area. In summary, the findings of this study reveal that the tectonic settings, provenance, uranium source, paleoclimate, and oxygen-rich paleowater of the Yimin Formation have important geological significance for the large-scale uranium mineralization of the Kelulun Depression. Full article