Underwater wireless communication technology plays an important role in marine environment monitoring and ecological protection. Underwater optical wireless communications (UWOCs) can currently achieve a transmission distance of hundreds of meters, and the rate can reach hundreds of Mbps or even Gbps, with low power consumption and high-speed features. In addition, UWOC also has the advantages of a small transceiver size and strong anti-electromagnetic interference ability, which is especially suitable for scenarios where underwater volume and power consumption are relatively limited. However, UWOC systems face problems such as unstable transceiver ends, ocean turbulence, and so on, resulting in reduced communication reliability and limited transmission distance. Establishing a stable and reliable communication link is critical to extending the communication distance of the UWOC system. In this paper, a model of ocean turbulence channels is established based on the power spectrum inversion method. The transmission characteristics of orbital angular momentum (OAM) light in an ocean turbulence channel are studied, then the mode selection of OAM light is determined. At the same time, the polarization coding technique is applied to the underwater OAM communication system for the first time. The simulation results show that this scheme can effectively extend the communication distance and reduce the system bit error rate. Full article

Oceanographic parameters, such as sea surface temperature, surface chlorophyll-a concentration, sea surface ice concentration, sea surface height, etc., are listed as Essential Climate Variables. Therefore, there is a crucial need for persistent and accurate measurements on a global scale. While in situ methods tend to be accurate and continuous, these qualities are difficult to scale spatially, leaving a significant portion of Earth’s oceans and seas unmonitored. To tackle this, various remote sensing techniques have been developed. One of the more prominent ways to measure the aforementioned parameters is via satellite spacecraft-mounted remote sensors. This way, spatial coverage is considerably increased while retaining significant accuracy and resolution. Unfortunately, due to the nature of electromagnetic signals, the atmosphere itself and its content (such as clouds, rain, etc.) frequently obstruct the signals, preventing the satellite-mounted sensors from measuring, resulting in gaps—missing data—in satellite recordings. One way to deal with these gaps is via various reconstruction methods developed through the past two decades. However, there seems to be a lack of review papers on reconstruction methods for satellite-derived oceanographic variables. To rectify the lack, this paper surveyed more than 130 articles dealing with the issue of data reconstruction. Articles were chosen according to two criteria: (a) the article has to feature satellite-derived oceanographic data (b) gaps in satellite data have to be reconstructed. As an additional result of the survey, a novel categorising system based on the type of input data and the usage of time series in reconstruction efforts is proposed. Full article

On account of current algorithm and parameter design difficulties and low detection accuracy in feature extractions of small target detections in sea clutter environment, this paper proposes a correspondingly improved four feature extraction method by FAST. After the short-time Fourier transform is applied, a time–frequency distribution spectrogram of original data is generated. Candidate feature points (CFP) are first extracted by FAST algorithm, and then a four-feature extraction is implemented with FAST and DBSCAN combined. The feature distinction is enhanced through a feature optimization. Upon the construction of the four-dimensional feature vectors, XGBoost classifier algorithm classifies and detects these feature vectors. The genetic algorithm optimizes the hyperparameters in XGBoost and updates the decision threshold in real time to control the detection method’s false alarm rate. The IPIX dataset is employed for experimental verification. Verification results confirm that this proposed detection method has better performance than several other currently used detection methods. The detection performance is improved by 7% and 13.8% when observation time is set at 0.512 s and 1.024 s, respectively. Full article

The Mesozoic strata in the northern South China Sea have good potential for oil and gas exploration. The Dongsha Waters, where the study area is located, have complex seismic and geological characteristics; in particular, turbulence is very prominent in this area, so it is difficult to implement 3D seismic data collection. The “single-source and single-cable quasi-3D seismic survey” method integrates some key technologies in acquisition and processing, thus improving the quality of seismic imaging. Based on the interpretation of the existing research results and new data, structure B-1 has good source–reservoir–cap combination conditions. The oil–gas accumulation mode is predicted, and the drilling well B-1-1 is given. In addition, the large-scale distribution of bottom-simulating reflectors (BSRs) and the discovery of gas seepage areas in the study area suggest the presence of gas hydrate. We suggest that deep thermogenic gas from the Mesozoic strata has migrated into the overlying strata along the fault system and mixed with microbial gas to form hydrate. Full article

Path planning is a key issue for safe navigation of inland ferries. With the development of ship intelligence, how to enhance the decision–support system of a ferry in a complex navigation environment is one of the key issues. The inland ferries need to cross the channel frequently and, thus, risky encounters with target ships in the waterway are more frequent, so they need an intelligent decision–support system that can deal with complex situations. In this study, a reinforced deep learning method is proposed for path planning of inland ferries during crossing of the waterways. In the study, the state space, action space and reward function of the Deep Q-network (DQN) model are designed and improved to establish an autonomous navigation method for ferries considering both economy and safety. The DQN model also takes into account the crossing behavior, navigation economy and safety. Finally, the model is applied to case studies to verify its effectiveness. Full article

Pipe bend is a critical integral component, widely used in slurry pipeline systems involving various engineering applications, including natural gas hydrate production. The aim of this study is to assess the capability of RANS-based CFD models to capture the main features of the turbulent single-phase flow in pipe bends, in view of the future investigation of the hydrate slurry flow in the same geometry. This is different from the available literature in which only a few accounted for the effects of a combination of computational mesh, turbulence model, and near-wall treatment approach. In this study, three types of mesh configuration were adopted to carry out the computations, namely unstructured mesh and two structured meshes with a uniform and nonuniform inflation layer, respectively. To explore the influence of the turbulence model, standard k-ε, low-Reynolds k-ε, and nonlinear eddy viscosity turbulence model were selected to close RANS equations. Pressure coefficient, mean axial velocity, turbulence intensity, secondary flow velocity, and magnitude of secondary flow were regarded as the critical variables to make a comprehensive sensitivity analysis. Predicted results suggest that turbulent kinetic energy is the most sensitive variable to the computational mesh while others tend to stabilize. The largest difference of turbulence kinetic energy was around 26% between unstructured mesh and structured mesh with a nonuniform inflation layer. Additionally, a fully resolved boundary layer can reduce the sensitivity of mesh on turbulent kinetic energy, especially for a nonlinear turbulence model. However, the large gradient and peak value of turbulence intensity near the inner wall of the bend was not captured by the case with a fully resolved boundary layer, compared with that of the wall function used. Furthermore, it has been confirmed that the same rule was detected also for different curvature ratios, Reynolds numbers, and dimensionless wall distance y+. Full article

The present paper proposes the implementation of a new algorithm for the control of the speed regulators of Pelton wheel turbines, used in many of the pumped hydroelectric energy storage systems that operate in isolated electrical systems with high renewable energy participation. This algorithm differs substantially from the standard developments which use PID or PI governors in that, in addition to acting on the nozzle needles and deflectors, it incorporates a new inner-loop pressure stabilization circuit to improve frequency regulation and dampen the effects of the pressure waves that are generated when regulating needle position. The proposed algorithm has been implemented in the Gorona del Viento wind–hydro power plant, an installation which supplies the primary energy needs of the island of El Hierro (Canary Islands, Spain). Although, as well as its wind and hydro generation systems, the plant also has a diesel engine based generation system, the validation of the results of the study presented here focuses on situations in which frequency control is provided exclusively by the hydroelectric plant. It is shown that implementation of the proposed algorithm, which replaces the previous control system based on a classical PI governor, is able to damp the pressure wave that originates in the long penstock of the plant in the face of variations in non-dispatchable renewable generation, a situation which occurred with a high degree of relative frequency in the case study. The damper has enabled a substantial reduction in the cumulative time and the number of times that frequency exceeded different safety margins. Damper incorporation also reduced the number of under-frequency pump unit load shedding events by 93%. Full article

The present study makes a consistent attempt to evaluate promising additive manufacturing (AM) processes and materials for marine structural applications, paving the way for the development of additively manufactured light-weight composites. The main objective is to analyse the structural performances of fibre-reinforced plastics (FRP) produced by AM for marine applications. In particular, the tensile response of chopped and continuous carbon-fibre-reinforced thermoplastics have been investigated through destructive and non-destructive testing, considering the influence of AM process settings and thermal post-manufacturing treatments. The results demonstrate that continuous fibre-reinforced thermoplastics produced by AM are potentially suited to marine structural applications, since their tensile capacity is superior to the minimum imposed by the Classification Society Rules. However, the mechanical properties of additively manufactured FRP are currently lower than conventional composites. The continuous carbon fibre reinforcement is far more effective than the chopped one, and the additive manufacturing deposition pattern significantly influences the structural capacity. The annealing post-manufacturing treatment enhances the mechanical properties by approximately 10%, decreasing material ductility and manufacturing defects. Full article

In order to proceed with shipbuilding scheduling involving hundreds of hull blocks of ships, it is important to mark the locations of the hull blocks with the correct block identification number. Incorrect information about the locations and the identification numbers of hull blocks causes disruption in the shipbuilding scheduling process of the shipyard. Therefore, it is necessary to have a system for tracking the locations and identification numbers of hull blocks in order to avoid time loss due to incorrectly identified blocks. This paper proposes a method to mark the identification numbers, which are necessary for the tracking system of hull blocks. In order to do this, 3 CNN (convolutional neural network) models, VGG-19, Resnet-152V2, and Densenet-201, are used to classify the hull blocks. A set of multi-view images acquired from 3D CAD data are used as training data to obtain a trained CNN model, and images from 3D printer-printed hull block models are used for the test of the trained CNN model. The datasets used for training and prediction are Non-Thr and Thr datasets, that each included both binarized and non-binarized datasets. As a result of end-to-end classification experiments with Non-Thr datasets, the highest prediction accuracy was 0.68 with Densenet-201. A total of 4050 experimental conditions were constructed by combining the threadhold of the Thr training and testing dataset. As a result of experiments with Thr datasets, the highest prediction accuracy of 0.96 was acquired with Resnet-152V2, which was trained with a threshold of 72 and predicted with a threshold of 50. In conclusion, the classification of ship hull blocks using a CNN model with binarized datasets of 3D CAD data is more effective than that using a CNN model with non-binarized datasets. Full article

Seaports play a crucial role in the transportation and logistics chain, and their development and optimization require significant investments in infrastructure, superstructure, human resources, and management. To ensure the efficiency and effectiveness of these investments, it is essential to implement a well-designed port management model. This model should be based on the criteria used to guide the selection process and ensure that the chosen model aligns with the needs and objectives of the port, stakeholders, and community. This study aims to determine the optimal criteria and management model for the regional seaports in the Republic of Croatia. Port management experts’ opinions were obtained through a questionnaire, and data were analyzed using the AHP and fuzzy AHP methods. The results showed that the criterion of functionality is optimal for choosing the appropriate management model, while the most favorable management model is the coordinated decentralized model. The results obtained by both methods were the same. Different criteria and management models, with similarities and differences between the obtained results and the provisions of the National Development Plan of Ports Open to Public Transport of Regional and Local Significance, are discussed and highlighted. Full article

Long-term consequences of radionuclide contamination of the Arabian Gulf as a result of hypothetical accidents at the Bushehr and Barakah nuclear power plants (NPPs) were studied using a chain of models including the atmospheric dispersion model RIMPUFF, the marine compartment model POSEIDON-R, and the dose model. The compartment model POSEIDON-R is complemented by a dynamic model of the biota food chain that includes both pelagic and benthic organisms. The source terms for the hypothetical releases of the selected radionuclides (¹³⁴Cs, ¹³⁷Cs, ¹⁰⁶Ru, and ⁹⁰Sr) in the atmosphere were defined as a fraction of respective reactor inventories available in the literature. Conservative meteorological scenarios for the calculation of the initial depositions of radionuclides were selected. Because the Gulf is shallow, a significant portion of the reactive radionuclides (¹³⁴Cs, ¹³⁷Cs, ¹⁰⁶Ru) remain in the bottom sediments and continue to contaminate water and benthic organisms for a long period of time. The annual dose due to the consumption of marine products can exceed 1 mSv, whereas the annual dose due to drinking the water from desalination plants is expected to be an order less. The contribution of elements to the dose depends on the type of reactor. This is manifested in differences between the contributions of different marine organisms to the dose. Full article

Ship exhaust gas has become an essential source of air pollution in recent years. To assess the impact of ship exhaust gas on the atmospheric environment and human health, this paper studies the problem of ship exhaust gas diffusion in the port area. According to automatic identification system (AIS) data, ship exhaust gas is estimated based on the bottom-up method, and the result of emission calculation is entered into a Gaussian puff model to calculate the superposition of the diffusion of gaseous pollutants from multiple ships. In addition, the results of a case study of the diffusion of ship exhaust gas in the western area of Shenzhen Port in China show that the distribution of the NO₂ concentration in the studied area is not stable, the diffusion of exhaust gas from multiple ships mainly affects some areas near large ship berths at night, and there is a small impact on the whole study area. This lays a foundation for monitoring and treating the atmospheric environment in the port area. Full article

The Ganges–Brahmaputra–Meghna Delta (GBMD) located in the head of the Bay of Bengal is regularly affected by severe tropical cyclones frequently. The GBMD covers the Bangladesh coast, which is one of the most vulnerable areas in the world due to cyclone-induced storm surges. More than 30% of the total country’s population lives on the Bangladesh coast. Hence, it is crucial to understand the underlying processes that modulate the storm surge height in the GBMD. A barotropic numerical 3D model setup is established by using Delft3D and SWAN to investigate a cyclone-induced storm surge event. The model is calibrated and validated for Cyclone Sidr in 2007 and applied to six idealized cyclonic scenarios. Numerical experiments with different coupling configurations are performed to distinguish the contribution of wind, tides, waves, and wave–current interactions (WCI) on the storm surge height. Results show that the wind-driven setup is the dominant contributor to the storm surge height during cyclonic events. Based on the tidal phase and wind direction, the interaction between tide and wind can increase or decrease the magnitude of the storm surge height. Finally, considering the wind-driven wave may increase the surge height up to 0.3 m along the coastline through a strong wave setup. Full article

Safe navigation for maritime autonomous surface ships (MASS) is a challenging task, and generally highly dependent on effective collaboration between multiple sub-systems in environments with various levels of uncertainty. This paper presents a novel methodology combining risk-based optimal control and path following with autonomous machinery management (AMM) for MASS navigation and supervisory risk control. Specifically, a risk-aware particle swarm optimization (PSO) scheme utilizes “time-to-grounding” predictions based on weather data and electronic navigational charts (ENC) to simultaneously control both the ship’s motion as well as the machinery system operation (MSO) mode during transit. The proposed autonomous navigation system (ANS) is comprised of an online receding horizon control that uses a PSO approach from previous works, which produces a dynamic risk-aware path with respect to grounding obstacles from a pre-planned MASS path, subsequently given as the input to a line-of-sight guidance controller for path following. Moreover, the MSO mode of the AMM system is simultaneously selected and assigned to explicit segments along the risk-aware path throughout the receding horizon, which effectively introduces into the optimization scheme an additional safety layer as well as another dimension for risk or resource minimization. The performance of the resulting ANS is demonstrated and verified through simulations of a challenging scenario and human assessment of the generated paths. The results show that the optimized paths are more efficient and in line with how human navigators would maneuver a ship close to nearby grounding obstacles, compared to the optimized paths of selected previous works. Full article