Editor’s Choice Articles

This review paper focuses on the use of ensemble neural networks (ENN) in the development of storm surge flood models. Storm surges are a major concern in coastal regions, and accurate flood modeling is essential for effective disaster management. Neural network (NN) ensembles have shown great potential in improving the accuracy and reliability of such models. This paper presents an overview of the latest research on the application of NNs in storm surge flood modeling and covers the principles and concepts of ENNs, various ensemble architectures, the main challenges associated with NN ensemble algorithms, and their potential benefits in improving flood forecasting accuracy. The main part of this paper pertains to the techniques used to combine a mixed set of predictions from multiple NN models. The combination of these models can lead to improved accuracy, robustness, and generalization performance compared to using a single model. However, generating neural network ensembles also requires careful consideration of the trade-offs between model diversity, model complexity, and computational resources. The ensemble must balance these factors to achieve the best performance. The insights presented in this review paper are particularly relevant for researchers and practitioners working in coastal regions where accurate storm surge flood modeling is critical. Full article

Here we show the SAVEMEDCOASTS-2 web-based geographic information system (webGIS) that supports land planners and decision makers in considering the ongoing impacts of Relative Sea Level Rise (RSLR) when formulating and prioritizing climate-resilient adaptive pathways for the Mediterranean coasts. The webGIS was developed within the framework of the SAVEMEDCOASTS and SAVEMEDCOASTS-2 projects, funded by the European Union, which respond to the need to protect people and assets from natural disasters along the Mediterranean coasts that are vulnerable to the combined effects of Sea Level Rise (SLR) and Vertical Land Movements (VLM). The geospatial data include available or new high-resolution Digital Terrain Models (DTM), bathymetric data, rates of VLM, and multi-temporal coastal flooding scenarios for 2030, 2050, and 2100 with respect to 2021, as a consequence of RSLR. The scenarios are derived from the 5th Assessment Report (AR5) provided by the Intergovernmental Panel on Climate Change (IPCC) and encompass different Representative Concentration Pathways (RCP2.6 and RCP8.5) for climate projections. The webGIS reports RSLR scenarios that incorporate the temporary contribution of both the highest astronomical tides (HAT) and storm surges (SS), which intensify risks to the coastal infrastructure, local community, and environment. Full article

The International Maritime Organization strives to improve the atmospheric environment in oceans and ports by regulating ship emissions of air pollutants and promoting energy efficiency. This study deals with the prediction of eco-friendly combustion in boilers to reduce air pollution emissions. Accurately measuring air pollutants from ship boilers in real-time is crucial for optimizing boiler combustion. However, using data obtained through an exhaust gas analyzer for real-time control is challenging due to combustion process delays. Therefore, a real-time predictive modeling approach is proposed to enhance the accuracy of prediction models for ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$, ${\mathrm{S}\mathrm{O}}_2$, ${\mathrm{C}\mathrm{O}}_2$, and ${\mathrm{O}}_2$ by analyzing the color spectrum of flame images in a quasi-instantaneous combustion state. Experimental investigations were carried out on an oil-fired boiler installed on an actual ship, where the air damper was adjusted to create various combustion conditions. This algorithm is a saturation-based feature extraction filter (SEF) through color spectrum analysis using RGB (red, green, and blue) and HSV (hue, saturation, and value). The prediction model applying the proposed method was verified against exhaust gas analyzer data using a new data set, and real-time prediction performance and generalization were confirmed. Full article

This study considers assessing the wave energy potential in the French façade. The objective is to investigate the validity of satellite altimetry-based estimates of wave renewable energy potential using the homogenized multi-mission altimeter data made available by the European Space Agency Sea State Climate Change Initiative (Sea_State_cci). The empirical model of Gommenginger et al. (2003) is adopted to calculate the wave period, which is required to estimate the wave power density from both the radar altimeter’s significant wave height and backscatter coefficient. The study comprises 26 years of data, from January 1992 to December 2018. In the winter season, the wave resource is abundant and higher than in other seasons. On average, the highest value is about 99,000 W/m offshore. In the coastal zone, the wave power density is also relatively high, with values of about 60,000 W/m in the North and South regions of the French Atlantic coast. The seasonal spatial distribution of the wave power density is presented to identify potential sites of interest for the development of the marine renewable energy sector and to make renewable energy supply more resilient. The analysis reveals large inter-annual and interseasonal variability in the wave resource in the French façade in the past 26 years. The study shows the feasibility of satellite altimetry-based assessments of wave renewable energy potential as a promising and powerful tool. Full article

Sea turtles gracefully navigate their marine environments by flapping their pectoral flippers in an elegant routine to produce the required hydrodynamic forces required for locomotion. The propulsion of sea turtles has been shown to occur for approximately 30% of the limb beat, with the remaining 70% employing a drag-reducing glide. However, it is unknown how the sea turtle manipulates the flow during the propulsive stage. Answering this research question is a complicated process, especially when conducting laboratory tests on endangered animals, and the animal may not even swim with its regular routine while in a captive state. In this work, we take advantage of our robotic sea turtle, internally known as Cornelia, to offer the first insights into the flow features during the sea turtle’s propulsion cycle consisting of the downstroke and the sweep stroke. Comparing the flow features to the animal’s swim speed, flipper angle of attack, power consumption, thrust and lift production, we hypothesise how each of the flow features influences the animal’s propulsive efforts and cost of transport (COT). Our findings show that the sea turtle can produce extremely low COT values that point to the effectiveness of the sea turtle propulsive technique. Based on our findings, we extract valuable data that can potentially lead to turtle-inspired elements for high-efficiency underwater drones for long-term underwater missions. Full article

The Ocean Cleanup introduces a Digital Twin (DT) describing the cleanup systems made of netting to extract marine litter from our oceans. It consists of two wings forming a “U-shape” and a retention zone. During operation, the system is towed and drag-driven with a span-to-length ratio of 0.6 $\le S{R}^{*}\le$ 0.8. The twine Reynolds number is ${\mathcal{R}e}_t^{*}\in [800:1600]$, making it experience various local drag coefficients. The DT was built with OrcaFlex (OF) aiming at: (i) avoiding over- or under-designing the system; (ii) supporting the scale-up of the system; and (iii) estimating the costs and/or the impact of our offshore operations. Therefore, we present an attempt to build an accurate DT using data from the Great Pacific Garbage Patch (GPGP). We developed a three-cycle validation: (i) initial guess applying Naumov’s semi-empirical drag coefficient to define the OF drag coefficients without the influence of the angles of attack $\theta$ of the wings; (ii) adjustment of the OF drag coefficients using AquaSim (AS) with its twine-by-twine drag correlation for various $\theta$; (iii) re-adjustment of the OF drag coefficients from two-dimensional CFD simulations using Direct Numerical Simulation (DNS) for a twine-by-twine establishment of a drag correlation on a 1 m plane net, highlighting the shielding effects for $\theta <{24}^{°}$. Consequently, an initial underestimation of −3% in the combined towline tension, for a nominal span ($S{R}^{*}=0.6$), was corrected to a slight overestimation of +7% compared to the GPGP data. For a wide span ($S{R}^{*}=0.8$), the deviation remained between +1% and +15% throughout the validation process. For a narrow span ($S{R}^{*}\sim$ 0.02), mostly exhibiting low $\theta$, the first cycle showed a +276% deviation, whereas at the end of the third cycle, it showed a +43% deviation. Full article

To lessen the environmental impact of the maritime industry, ports must decarbonize in conformity with various standards such as the European Green Deal and the Sustainable Development Goals (SDGs). In this regard, they must demonstrate integrated low-emission energy production, distribution, and supply, as well as sustainable alternative infrastructure for refueling ships, cargo handling equipment, and other vehicles inside port boundaries. To address this issue, ports must progress toward smartening their operations. This requires intelligent infrastructure and components, with smart energy infrastructure being one of the most crucial ones. It is a part of port energy management systems (EMSs) and works based on modern technology to balance energy demand, distributions, and supply while transitioning to renewable energies. This study investigates the “scoping review” of “smart energy infrastructure” deployment and its efficiency in seaport EMSs to reduce the port’s carbon footprint (C.F). The “Introduction” section discusses the subject’s significance. The “Materials and Methods” section explains the process of selecting and revising references and relevant material. The “Findings” section then examines the several aspects and sections of a smart port and smart energy infrastructure, as well as how they function. The “Discussion” section explains the interpretation based on the present situation. Finally, the “Conclusion” part gives scientific thoughts and comments on the work-study debate and ideas for future research in the same field to help port authorities achieve sustainability. Full article

This work represents a modification of the Context Conditional Generative Adversarial Network as a novel implementation of a non-linear gap reconstruction approach of missing satellite-derived chlorophyll a concentration data. By adjusting the loss functions of the network to focus on the structural credibility of the reconstruction, high numerical and structural reconstruction accuracies have been achieved in comparison to the original network architecture. The network also draws information from proxy data, sea surface temperature, and bathymetry, in this case, to improve the reconstruction quality. The implementation of this novel concept has been tested on the Adriatic Sea. The most accurate model reports an average error of $0.06\mathrm{mg}{\mathrm{m}}^{-3}$ and a relative error of $3.87\%$. A non-deterministic method for the gap-free training dataset creation is also devised, further expanding the possibility of combining other various oceanographic data to possibly improve the reconstruction efforts. This method, the first of its kind, has satisfied the accuracy requirements set by scientific communities and standards, thus proving its validity in the initial stages of conceptual utilisation. Full article

Earth observation can provide managers with valuable information on ongoing coastal processes and major trends in coastline evolution, especially in data-poor regions. This paper examines the use of optical satellite images in the mapping of the changes in shoreline position before, during, and after the implementation of a protection scheme. The aim of this paper is twofold: (i) to demonstrate the potential of satellite imagery as an effective, robust, and low-cost tool to remotely monitor the effectiveness of protective structures based on a large-scale case study in West Africa; and (ii) to compile lessons learned from this case study that can be used in the design of future interventions. The analysis shows that before the implementation of the protection scheme, the coastal sector was retreating at a rate of −1.6 m/year, which is in line with the average retreat rates reported in other studies for the region. After project implementation, this trend reversed into shoreline accretion at a rate of +1.0 m/year, locally experiencing positive and negative oscillations in the short term. Furthermore, the shoreline-extracted positions proved useful in assessing the impact of differences in the groynes’ permeability with respect to temporary leeside erosion. Finally, it is recommended to continue this monitoring to assess long-term trends. Full article

The importance of accurate ship performance estimation is increasing for efficient ship operation. Ship performance has been evaluated through model tests in the past, but there are limitations in terms of facilities and costs. With the spread of high-performance computers, the method of evaluating the performance of a ship by numerical analysis, especially computational fluid dynamics (CFD), has become common. There have been many numerical studies on added resistance under various wave conditions for many years, showing a high reliability. Meanwhile, most of the studies were conducted under conditions where the degree of freedom (DOF) of the ship was limited due to computational complexity. In this study, we tried to compare the added resistance performance and fluid dynamics of S-VLCC with 6 DOFs in the regular wave conditions. One of the methods for utilizing the 6 DOFs is the soft-mooring system, which allows springs to be attached to the bow and stern to recover the non-restoring force of the hull. The second method considers the free-running condition. The virtual disk is used for the self-propulsion of the ship, and the rudder can be rotated to maintain its course. The propeller rotation speed and rudder angle are controlled through PID control. The bow wave (ψ = 180°) and oblique wave (ψ = 150°, 120°) conditions were considered, and various regular wave conditions from short to long wavelengths were regarded. The effects of restraint conditions on the added resistance and motion response amplitude operator (RAO), according to each wave condition, were compared. As a result, there was a difference in the roll motion for each restraint condition, and the y-direction force and yaw moment generated on the hull were compared to analyze the cause. In addition, we observed the change in flow characteristics by comparing the streamlines around the hull and the nominal wake on the propeller plane. Full article

Nowadays, the exponential expansion in human population has resulted in the massification of intensive agricultural practices, with crop yield and sustainability being one of the most pressing challenges. Therefore, there was a need for new and natural fertilizers and pesticides, which has become a popular agricultural trend nowadays. Therefore, there was an increased interest to apply seaweed and bacterial extracts in agriculture to promote new means of sustainability and soil usage. This work aims to test seaweed inclusion in the agricultural field, as a simple or complex foliar biofertilizer solution applied together with a nitrifying bacteria, to verify if there is a potential synergistic effect of these two different types of biofertilizers on economically important vegetables. As a result, experiments were conducted in a greenhouse using an aqueous extract of the brown seaweed Saccharina latissima (1.2% v/v) and a biofertilizer based on BlueN bacteria (0.03% m/v), both simple or in combination, on lettuce (Lactuca sativa L. var. crispa) plants. The seaweed extract (simple or in combination), presented favorable effect on lettuce growth and nutritional properties. The aqueous algal extract, and it in combination with BlueN, produced heavier lettuce leaves (74.25 ± 6.86 and 74.13 ± 3.07 g, respectively) than the controls and enriched leaf micronutrient contents (zinc and manganese). Also, this study demonstrated that a combined seaweed-bacteria fertilizer did not show synergistic behavior, being a non-profitable solution when compared to a simple seaweed extract. In summary, this study demonstrated that simple (crude) seaweed extracts can be considered as an important key for natural plant biofertilizers and growth stimulators concerned with the blue circular economy. Full article

Thousands of tonnes of litter enter the ocean every day, posing a significant threat to marine life and ecosystems. While floating and beach litter are often in the spotlight, about 70% of marine litter eventually sinks to the seafloor, making underwater litter the largest accumulation of marine litter that often goes undetected. Plastic debris makes up the majority of ocean litter and is a known source of microplastics in the ocean. This paper focuses on the detection of ocean plastic using neural network models. Two neural network models will be trained, i.e., YOLACT and the Mask R-CNN, for the instance segmentation of underwater litter in images. The models are trained on the TrashCAN dataset, using pre-trained model weights trained using COCO. The trained neural network could achieve a mean average precision ($mAP$) of 0.377 and 0.365 for the Mask R-CNN and YOLACT, respectively. The lightweight nature of YOLACT allows it to detect images at up to six times the speed of the Mask R-CNN, while only making a comparatively smaller trade-off in terms of performance. This allows for two separate applications: YOLACT for the collection of litter using autonomous underwater vehicles (AUVs) and the Mask R-CNN for surveying litter distribution. Full article

Accurate estimation of offshore wind turbine (OWT) modal parameters has a prominent effect on the design loads, lifetime prediction, and dynamic response of the system. Modal parameters can vary during the operation of OWTs. This paper studies the variation and sensitivity analysis of an OWT’s modal parameters with respect to operational and environmental conditions. Three finite element models of a jacket-supported OWT at the Block Island Wind Farm are created within the OpenSees, SAP2000, and OpenFAST platforms and validated using experimental measurements. The OpenFAST model is used to simulate the modal parameters of the turbine under various wind speed, rotor speed, power, yaw angle, mean sea level, blade pitch angle, and soil spring values. The model-predicted modal parameters of the first fore–aft (FA) and side–side (SS) modes are compared to those identified from experimental measurements. Results from the simulations show that the first FA natural frequency and damping ratio mostly depend on the rotor speed and wind speed, respectively, while yaw angle and mean sea level do not have a visible effect. It is observed that there is about 8% stiffening in the first FA frequency and an aerodynamic damping of 7.5% during the operation of the OWT. Full article

There has been a growing interest in research on how to define and build indicators of resilience to address challenges associated with sea-level rise. Most of the proposed methods rely on lagging indicators constructed based on the historical performance of an infrastructure sub-system. These indicators are traditionally utilized to build curves that describe the past response of the sub-system to stressors; these curves are then used to predict the future resilience of the sub-system to hypothesized events. However, there is now a growing concern that this approach cannot provide the best insights for adaptive decision-making across the broader context of multiple sub-systems and stakeholders. As an alternative, leading indicators that are built on the structural characteristics that embody system resilience have been gaining in popularity. This structure-based approach can reveal problems and gaps in resilience planning and shed light on the effectiveness of potential adaptation activities. Here, we survey the relevant literature for these leading indicators within the context of sea-level rise and then synthesize the gained insights into a broader examination of the current research challenges. We propose research directions on leveraging leading indicators as effective instruments for incorporating resilience into integrated decision-making on the adaptation of infrastructure systems. Full article

The use of floating offshore wind farms for electrical energy supply is expected to rise significantly over the coming years. Suspended inter-array power cables are a new design to connect floating offshore wind turbines (FOWTs) with shorter cable lengths than conventional setups. The present study investigates the fatigue life of a suspended power cable with attached buoys connecting two spar-type FOWTs. Typical environmental conditions for the North Sea are applied. The nonlinear bending behavior of the power cable is considered in the analysis. Fatigue assessment is performed using the numerical software OrcaFlex based on stress factors obtained from cross-section analysis. An effective method for obtaining the stress factors is proposed for early engineering design stages and compared with the finite element software UFLEX simulation results. The simplified method delivers similar results for axial tension loads and conservative results for bending loads compared with results obtained from the finite element software. Stress components resulting from curvature variation are identified as the main contributors to fatigue damage. The most critical locations along the power cable for fatigue life are close to the hang-off points. Full article

Marine emission policies are becoming more demanding; thus, ship propulsion and power generation technologies need to be adapted to current scenarios. LNG is already considered to be a transition fuel, and new alternative marine fuels are emerging. The aim of this study was to develop an innovative methodology to optimize and adapt the combustion system of an LNG internal combustion marine engine to burn alternative marine fuels. The present study was based on LBG, but the methodology could be replicated with other fuels. A total of six tests were carried out, with three prechamber designs and three spark plug designs. Each test was carried out in a single-cylinder engine with two types of high-methane-number fuel. The influence on thermal efficiency parameters such as the prechamber volume, the orientation of the flame holes, and the existence of a central hole was studied. In the case of the spark plug, the influence of the amount of precious metal in the electrode, its shape and its insertion into the prechamber were analysed. Experiments showed that by modifying both the prechamber and the spark plug, maximum improvements in thermal efficiency of 1.9% can be achieved. Those improvements allowed the LBG engine to suffer only a 4.3% thermal efficiency reduction, as opposed to its LNG counterpart. By applying the proposed methodology, the thermal efficiency of commercially available internal combustion gas engines could be improved. Full article

A Vessel Traffic Service (VTS) plays a central role in maritime traffic safety. Regulations are given by the International Maritime Organization (IMO) and Guidelines by the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA). Accordingly, VTS facilities utilize communication and sensor technologies such as an Automatic Identification System (AIS), radar, radio communication and others. Furthermore, VTS operators are motivated to apply Decision Support Tools (DST), since these can reduce workloads and increase safety. A promising type of DST is anomaly detection. This survey presents an overview of state-of-the-art approaches of anomaly detection for the surveillance of maritime traffic. The approaches are characterized in the context of VTS and, thus, most notably, sorted according to utilized communication and sensor technologies, addressed anomaly types and underlying detection techniques. On this basis, current trends as well as open research questions are deduced. Full article

Semidiurnal tidal currents can exceed 5 ms${}^{-1}$ in Minas Passage, Bay of Fundy, where a tidal energy demonstration area has been designated to generate electricity using marine hydrokinetic turbines. The risk of harmful fish–turbine interaction cannot be dismissed for either migratory or local fish populations. Individuals belonging to several fish populations were acoustically tagged and monitored by using acoustic receivers moored within the Minas Passage. Detection efficiency $\rho$ is required as the first step to estimate the probability of fish–turbine encounter. Moored Innovasea HR2 receivers and high-residency (HR) tags were used to obtain detection efficiency $\rho$ as a function of range and current speed, for near-seafloor signal paths within the tidal energy development area. Strong tidal currents moved moorings, so HR tag signals and their reflections from the sea surface were used to measure ranges from tags to receivers. HR2 self-signals that reflected off the sea surface showed which moorings were displaced to lower and higher levels on the seafloor. Some of the range testing paths had anomalously low $\rho$, which might be attributed to variable bathymetry blocking the line-of-sight signal path. Clear and blocked signal paths accord with mooring levels. The application of $\rho$ is demonstrated for the calculation of abundance, effective detection range, and detection-positive intervals. High-residency signals were better detected than pulse position modulation (PPM) signals. Providing that the presently obtained $\rho$ applies to tagged fish that swim higher in the water column, there is a reasonable prospect that probability of fish–turbine encounter can be estimated by monitoring fish that carry HR tags. Full article

Oil spills may have devastating effects on marine ecosystems, public health, the economy, and coastal communities. As a consequence, scientific literature contains various up-to-date, advanced oil spill predictive models, capable of simulating the trajectory and evolution of an oil slick generated by the accidental release from ships, hydrocarbon production, or other activities. To predict in near real time oil spill transport and fate with increased reliability, these models are usually coupled operationally to synoptic meteorological, hydrodynamic, and wave models. The present study reviews the available different met-ocean forcings that have been used in oil-spill modeling, simulating hypothetical or real oil spill scenarios, worldwide. Seven state-of-the-art oil-spill models are critically examined in terms of the met-ocean data used as forcing inputs in the simulation of twenty-three case studies. The results illustrate that most oil spill models are coupled to different resolution, forecasting meteorological and hydrodynamic models, posing, however, limited consideration in the forecasted wave field (expressed as the significant wave height, the wave period, and the Stokes drift) that may affect oil transport, especially at the coastal areas. Moreover, the majority of oil spill models lack any linkage to the background biogeochemical conditions; hence, limited consideration is given to processes such as oil biodegradation, photo-oxidation, and sedimentation. Future advancements in oil-spill modeling should be directed towards the full operational coupling with high-resolution atmospheric, hydrodynamic, wave, and biogeochemical models, improving our understanding of the relative impact of each physical and oil weathering process. Full article

Costa da Caparica beach, in Portugal, has suffered from chronic erosion for the last 50 years, a phenomenon that has been countered by various management interventions. This study aims at comparing sixteen possible interventions, thus identifying the most effective one(s) in terms of reducing beach erosion or even promoting beach accretion. This exercise is achieved using a one-line shoreline evolution model, calibrated with in situ field data, forced by local wave conditions. The target management period is 25 years. In the calibration phase, it is found that the annual mean alongshore net sediment transport along the 24 km sandy coast is variable in direction and magnitude, but it is mostly smaller than ±50 × 10³ m³/year. This net transport results from the imbalance of northward/southward-directed bulk transports of circa tenfold-larger magnitudes. This affects the overall sediment balance at the urban beaches, as well as the effectiveness of the intervention strategies. The results show that the present management strategy is effective in holding the shoreline position, although deploying the same nourishment volume but over a shorter area could lead to better results. The best solutions, which are capable of promoting beach accretion, implicate the lengthening of the terminal groin at the northern extremity of the beach. The results from this study can support decision makers in identifying the most appropriate management action, not just locally but also at other coastal regions where similar problems persist and the same methodology could be applied. Full article

Despite recent advancements in ocean–wave observations, how a tropical cyclone’s (TC’s) track, intensity, and translation speed affect the directional wave spectra evolution is poorly understood. Given the scarcity of available wave spectral observations during TCs, there are few studies about the performance of spectral wave models, such as Simulating Waves Nearshore (SWAN), under various TC scenarios. We combined the National Data Buoy Center observations and numerical model hindcasts to determine the linkages between wave spectrum evolution and TC characteristics during hurricanes Matthew 2016, Dorian 2019, and Isaias 2020. Five phases were identified in the wave spectrogram based on the normalized distance to the TC, the sea–swell separation frequency, and the peak wave frequency, indicating how the wave evolution relates to TC characteristics. The wave spectral structure and SWAN model’s performance for wave energy distribution within different phases were identified. The TC intensity and its normalized distance to a buoy were the dominant factors in the energy levels and peak wave frequencies. The TC heading direction and translation speed were more likely to impact the durations of the phases. TC translation speeds also influenced the model’s performance on swell energy. The knowledge gained in this work paves the way for improving model’s performance during severe weather events. Full article

The harvesting of wind energy and its transformation into a thrust force for ship propulsion are gaining in popularity due to the expected benefit in fuel consumption and emission reductions. To exploit these benefits, a proper matching between the conventional diesel engine-screw propeller propulsion plant and the wind-assisted plant is key. This paper aims to present a method and a code for the preliminary sizing of a ship propulsion plant based on a diesel engine, a controllable pitch propeller, and one or more Flettner rotors. A mathematical model describing the behaviour of the rotor in terms of propulsive thrust and power is proposed. The rotor model has been integrated into an existing diesel propulsion model in order to evaluate the ship’s fuel consumption. The ship’s propulsion model is written in a parametric form with respect to the following design parameters: ship dimensions and resistance-speed curve, propeller diameter, engine power, rotor geometry, and true wind conditions. The methodology helps in evaluating the engine–propeller working points and eventually the total ship propulsive power, including the power required to spin the rotor. It provides a way to compare wind-assisted propulsive solutions in terms of fuel consumption and CO₂ emissions. A 3000-ton Ro-Ro/Pax ferry has been selected as a case study. Results on the parametric analysis of rotor dimensions and propeller pitch optimization are presented. Full article

This paper highlights the development of Digital Twin (DT) technology and its admittance to a variety of applications within the maritime domain in general and surface ships in particular. The conceptual theory behind the evolution of DT is highlighted along with the development of the technology and current progress in practical applications with an exploration of the key milestones in the extension from the electrification of the shipping sector towards the realization of a definitive DT-based system. Existing DT-based applications within the maritime sector are surveyed along with the comprehension of ongoing research work. The development strategy for a formidable DT architecture is discussed, culminating in a proposal of a four-layered DT framework. Considering the importance of DT, an extensive and methodical literature survey has also been carried out, along with a comprehensive scientometric analysis to unveil the methodical footprint of DT in the marine sector, thus leading the way for future work on the design, development and operation of surface vessels using DT applications. Full article

Antarctica is an untapped reservoir of bacterial communities, which are able to adapt to a huge variety of strategies to cope with extreme conditions and, therefore, are capable of producing potentially valuable compounds for biotechnological applications. In this study, 31 UV-resistant bacteria collected from different Antarctic aquatic environments (surface sea waters/ice and shallow lake sediments) were isolated by UV-C assay and subsequently identified. A phylogenetic analysis based on 16S rRNA gene sequence similarities showed that the isolates were affiliated with Proteobacteria, Actinobacteria and Firmicutes phyla, and they were clustered into 15 bacterial genera, 5 of which were Gram negative (Brevundimonas, Qipengyuania, Sphingorhabdus, Sphingobium, and Psychrobacter) and 10 of which were Gram positive (Staphylococcus, Bacillus, Mesobacillus, Kocuria, Gordonia, Rhodococcus, Micrococcus, Arthrobacter, Agrococcus, and Salinibacterium). Strains belonging to Proteobacteria and Actinobacteria phyla were the most abundant species in all environments. The genus Psychrobacter was dominant in all collection sites, whereas bacteria belonging to Actinobacteria appeared to be the most diverse and rich in terms of species among the investigated sites. Many of these isolates (20 of 31 isolates) were pigmented. Bacterial pigments, which are generally carotenoid-type compounds, are often involved in the protection of cells against the negative effects of UV radiation. For this reason, these pigments may help bacteria to successfully tolerate Antarctic extreme conditions of low temperature and harmful levels of UV radiation. Full article

Coral reefs are three-dimensional biogenic structures that provide habitat for plenty of marine organisms; yet, coral reefs are deteriorating worldwide. Hence, it is essential to identify suitable substitutes for such coral services. This study examines reef fishes’ behavior and reactions to three-dimensional-printed (3DP) corals based on scanned Stylophora pistillata, as well as modified 3DP models. In particular, fishes’ unresponsiveness to the color, shape, morphology, and material of 3DP models both in vitro and in situ experiments was investigated. Coral reef fishes responded to the 3DP corals and demonstrated their usage in a range of services. Moreover, a greater number of fish species interacted more with 3DP models than they did with live corals. Furthermore, specific reef fish species, such as Sea Goldies (Pseudanthias squamipinnis), showed a preference for specific 3DP coral color, and other species demonstrated preferences for specific 3DP model shapes. The current study results show that three-dimensional-printed coral models can substitute for live corals for certain types of reef fish services. Full article

The size of container vessels is continuously growing, always exceeding expectations. Port authorities and terminals need to constantly adapt and face challenges related to maritime infrastructure, equipment, and operations, as these are the principal areas affected by the future Ultra Large Container Vessels (ULCVs). Maneuvring areas are at their limits, and mooring equipment is at an increased risk of being overloaded. This study aims to analyze the limitations that present mooring systems may face when ULCVs are subjected to wind and passing-ship forces exerted by a future ULCV and wind forces through Dynamic Mooring Analysis (DMA). A hypothetical and massive future ULCV with a capacity of 40,000 TEU is compared to the Emma Maersk, which is a present vessel that regularly calls at container terminals. The Emma Maersk, with its current mooring arrangement, experiences higher motion than future ULCVs, which experience higher forces but are also moored with more and stronger lines. This translates into considerably higher loads in the mooring system, potentially compromising safe mooring conditions at the terminal. Mitigating measures are proposed in the study to face these limitations. In addition, the study explores the potential of new and innovative mooring technologies, such as high-strength synthetic ropes and smart mooring systems, to address the challenges posed by ULCVs. A container terminal at the Port of Rotterdam, Europe’s largest sea port, has been analyzed as a case study. The terminal is located next to a busy fairway that leads to other container terminals, justifying the need to analyze both wind and passing-ship effects on moored ships. Full article

Underwater radiated noise is part of the anthropogenic emissions into the environment and as such a pressing problem for the preservation of the marine ecosystem. In order to direct attention to the most relevant noise sources associated with ships it is crucial to precisely determine the local origins of the acoustic emissions. As acoustics are by nature perceived through a very subjective auditory perception, visual post-processing support is required in engineering applications to assess the impact on structures and to create an understanding of the overall noise field geometrically, topologically, and directionally. In the context of CFD simulations, this may be achieved by considering the pressure pulses on domain boundary surfaces or passive surfaces, or by evaluating various volumetric information, such as Proudman acoustic sources or the Lighthill stress tensor, which is the fundamental input for many acoustic analogies including the Ffowcs-Williams-Hawkings method. For a propeller-hull configuration, the acoustic emissions from modeled and scale-resolved turbulence two-phase CFD analyses are evaluated in detail with different visualization methods. It is shown that the spatial distribution information of frequency domain pressure pulses, and the corresponding complex phase angles on specific passive geometries, as well as the Lighthill stress tensor may be utilized to create a better understanding of underwater acoustics. This allows the identification of source types and their respective excitation of the hull and emission characteristics of the hydrodynamic sources into the fluid domain, as well as the effect of the CFD simulation domain geometry extent. Full article

The Central Red Sea Rift is a natural laboratory to study the transition from rifting to spreading. Based on new reflection seismic profiles and gravity modeling, we examined the crustal structure, tectonic evolution, breakup mechanism, and future evolution of the Central Red Sea Rift. Along this rift axis, the breakup of continental lithosphere is discontinuous and the oceanic crust is limited to the axial deeps. The punctiform breakup and formation of deeps is assisted by mantle upwelling and topographic uplift, but the nucleation is directly controlled by the normal-fault system. The discontinuities spaced between axial deeps within the relatively continuous central troughs are presently axial domes or highs and will evolve into new deeps with tectonic subsidence. Isolated deeps will grow and connect with each other to become a continuous central trough, before transitioning into a unified spreading center. Full article

In this study, nondominated sorting genetic algorithm II (NSGA-II) was used to minimize the cost and carbon emissions of a liquefied natural gas (LNG) dual-fuel ship for a given route. This study considered the regulations of emission control areas (ECA) and the European Union (EU) Emissions Trading System (ETS) to determine the optimal speed and LNG/oil ratio for the ship. NSGA-II used the arrival time at each port and the LNG usage ratio for each voyage leg as its genes. The time window for arrival, the fuel cost, and potential EU carbon emission regulations were used to estimate the cost of the considered voyage. Moreover, fuel consumption was determined using historical data that were divided by period, machinery, and voyage leg. The results indicated that the optimal speed and fuel ratio could be determined under any given fuel and carbon price profile by using NSGA-II. Finally, the effects of regulations and carbon price differences on the optimal speed and fuel ratio were investigated. The cost minimization solution was susceptible to being affected by the regulations of ECAs and the EU ETS. The speed profile of the cost minimization solution was found to have a tendency to travel at faster-than-average speeds outside ECAs and non-EU regions, and travel slower in ECAs and EU regions. Meanwhile, the selection of fuel type showed that 100% traditional fuel oil in all regions, but with sufficiently high EU carbon permit cost, tends to use 100% LNG in EU regions. Full article

GNSS (Global Navigation Satellite System) positioning is not available underwater due to the very short range of electromagnetic waves in the sea water medium. In this article a LBL (Long Base Line) acoustic repeater system of the GNSS positioning is presented. The system is hyperbolic, i.e., based on time differences and it does not need very accurate atomic clocks to synchronize repeaters. The system architecture and system calculations that demonstrate the feasibility of the solution are presented. The system uses four buoys that sequentially transmit their position and the time of the instant of transmission, for which they are equipped with GNSS receivers and acoustic modems. The buoys can be fixed or even drifting, but they are inexpensive devices, which pose no hazard to navigation and can be easily and quickly deployed for a specific underwater mission. The multilateration algorithm used in the receiver is presented. To simplify the algorithm, the depth of the receiver, measured by a depth sensor, is used. Results are presented for the position error of an underwater vehicle due to its displacement during the transmission frame of the four buoys. Full article

Underwater target detection is a crucial aspect of ocean exploration. However, conventional underwater target detection methods face several challenges such as inaccurate feature extraction, slow detection speed, and lack of robustness in complex underwater environments. To address these limitations, this study proposes an improved YOLOv7 network (YOLOv7-AC) for underwater target detection. The proposed network utilizes an ACmixBlock module to replace the 3 × 3 convolution block in the E-ELAN structure, and incorporates jump connections and 1 × 1 convolution architecture between ACmixBlock modules to improve feature extraction and network reasoning speed. Additionally, a ResNet-ACmix module is designed to avoid feature information loss and reduce computation, while a Global Attention Mechanism (GAM) is inserted in the backbone and head parts of the model to improve feature extraction. Furthermore, the K-means++ algorithm is used instead of K-means to obtain anchor boxes and enhance model accuracy. Experimental results show that the improved YOLOv7 network outperforms the original YOLOv7 model and other popular underwater target detection methods. The proposed network achieved a mean average precision (mAP) value of 89.6% and 97.4% on the URPC dataset and Brackish dataset, respectively, and demonstrated a higher frame per second (FPS) compared to the original YOLOv7 model. In conclusion, the improved YOLOv7 network proposed in this study represents a promising solution for underwater target detection and holds great potential for practical applications in various underwater tasks. Full article

Here we present a machine-learning-based method for utilizing traditional ocean-viewing satellites to perform automated atmospheric correction of nanosatellite data. These sensor convolution techniques are required because nanosatellites do not usually possess the wavelength combinations required to atmospherically correct upwelling radiance data for oceanographic applications; however, nanosatellites do provide superior ground-viewing spatial resolution (~3 m). Coincident multispectral data from the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (Suomi NPP VIIRS; referred to herein as “VIIRS”) were used to remove atmospheric contamination at each of the nanosatellite’s visible wavelengths to yield an estimate of spectral water-leaving radiance [L_w(l)], which is the basis for surface ocean optical products. Machine learning (ML) algorithms (KNN, decision tree regressors) were applied to determine relationships between L_w and top-of-atmosphere (L_t)/Rayleigh (L_r) radiances within VIIRS training data, and then applied to test cases for (1) the Marine Optical Buoy (MOBY) in Hawaii and (2) the AErosol RObotic Network Ocean Color (AERONET-OC), Venice, Italy. For the test cases examined, ML-based methods appeared to improve statistical results when compared to alternative dark spectrum fitting (DSF) methods. The results suggest that ML-based sensor convolution techniques offer a viable path forward for the oceanographic application of nanosatellite data streams. Full article

SOLAS (Safety of Life at Sea), which was first enacted in 1914 as a result of the Titanic disaster, presents mandatory requirements for ship safety, such as the adoption of watertight bulkheads. However, ship accidents continue to occur despite the development and application of numerous safety technologies. In the case of a marine accident, the risk of sinking or capsizing due to flooding can be reduced by subdividing the watertight area, but shipbuilding costs, the weight increase for light ships, and the intact stability of the vessel must be considered together. For this reason, in this study, a BSS (buoyancy support system) was designed in accordance with ISO 23121-1 and ISO 23121-2. The characteristics of watertight and non-watertight spaces were reviewed and the BSS was implemented for a small car ferry. By applying additional safety technologies while securing economic feasibility in terms of ship construction and operation, an alternative to reduce the loss of human lives, environmental damage, and property losses in the case of a ship accident was proposed. Full article

The primary objective of this research is to demonstrate advanced surveying methods and techniques for coastal erosion identification and monitoring in a densely human-populated coastline, the southern coastline of the Gulf of Patras (Greece), which diachronically suffers erosion problems expected to become worse in the forthcoming years due to climate change and human intervention. Its importance lies in the fact that it presents a robust methodology on how all modern scientific knowledge and techniques should be used in coastal erosion problems. The presented methods include the use of satellite and aerial photo imaging, shallow seabed bathymetry and morphology, sediment sampling, geotechnical investigations, as well as hydrodynamic modelling. The results are extensively analyzed in terms of their importance in coastal erosion studies and are cross-validated to define those areas most vulnerable to erosion. Towards this scope, the seabed erosion rate produced by hydrodynamic modelling is compared with the coastal vulnerability index (CVI) calculations performed in the examined area to identify which coastal zones are under a regime of intensive erosion. The results between the CVI and the seabed erosion rate appear to coincide in terms of the erosion potential, especially in zones where the vulnerability regime has been calculated as being high or very high, with the P. oceanica meadows playing an important role in reducing erosion. Full article

Weld quality and life extension methods of welded details in ship structures made of high-strength and ultra-high-strength steels are of high importance to overcome the issues related to the fatigue characteristics of welded high-strength steels. The current work experimentally and numerically investigated the fatigue strength of a longitudinal stiffener detail, typically present in the bulkhead connections of ship hull. Two high-strength steel grades, namely EQ47TM and EQ70QT steels, were studied in welded plate connections using gas metal arc welding with rutile-cored wires. Fatigue tests were carried out on both small-scale specimens under axial and large-scale beam specimens under four-point bending loading. In addition to the joints tested in the as-welded condition, the high-frequency mechanical impact (HFMI) treatment was considered as a post-weld treatment technique in the fatigue test series. Furthermore, the large-scale beam specimens were pre-fatigued until substantial fatigue cracks were observed, after which they were re-tested after weld repairing and post-weld treatments to investigate the potential to rehabilitate fatigue-cracked ship details. The joints in the as-welded condition were performed in accordance with the current design recommendations. Due to the severe transition from the base material to the weld reinforcement in the joints welded with the rutile-cored wire, a successful HFMI treatment required geometrical modification of weld toe using a rotary burr to avoid any detrimental sub-cracks at the HFMI-treated region. Alternatively, the use of solid filler wires could potentially overcome these issues related to the welding quality. Repaired and post-weld-treated welds performed well in the re-tests, and the fatigue strength was almost twice higher than that of tests in the as-welded condition. Full article

With the increasing use of electric propulsion ships, the emergence of the shaftless rim-driven thruster (RDT) as a revolutionary integrated motor thruster is gradually becoming an important development direction for green ships. The shaftless structure of RDTs leads to their dependence on position sensorless control techniques. In this study, a novel control algorithm using a composite sliding mode observer (SMO) with a modified feed-forward phase-locked loop (PLL) is presented for achieving high accuracy position and speed control of shaftless RDT motors. The deviation between the observed and actual currents is exploited to develop a current SMO to extract back electromotive force (back-EMF) errors. On this basis, a back-EMF observer is established to achieve accurate estimation of the back-EMF. The basic structure of the PLL was modified and incorporates a speed feedforward mechanism, which enhances the performance of rotor position estimation and facilitates bidirectional rotation. The stability of the algorithm has been verified in Matlab/Simulink for a range of steady-state, dynamic, and ship propeller loading conditions. Remarkably, the control algorithm boasts an impressive adjustment time of approximately 0.006 s and its position estimation error may be as low as 0.03 rad. Simulation results highlight the performance of the algorithm to achieve bidirectional rotation, while exhibiting fast convergence, minimal vibration, exceptional control accuracy, and robustness. Full article

Coastal environments are dynamic ecosystems, constantly subject to erosion/accretion processes. Erosional trends have unfortunately been intensifying for decades due to anthropic factors and an accelerated sea level rise might exacerbate the problem. It is crucial to preserve these areas for safeguarding not only coastal ecosystems and cultural heritage, but also the population living there. In this context, monitoring coastal areas is essential and geomatics techniques, especially satellite remote sensing imagery, might prove very advantageous. In this paper, a semi-automatic methodology to extract shorelines from SAR (Synthetic Aperture Radar) Sentinel-1 and optical Sentinel-2 satellite images was developed. An experimental algorithm, called J-Net Dynamic, was tested in two pilot sites. The semi-automatic methodology was validated with GNSS (Global Navigation Satellite System) reference shorelines and demonstrated to be a powerful tool for a robust extraction of the shoreline both from optical and SAR images. The experimental algorithm was able to extract the shoreline closer to the reference with SAR images on the natural beach of Castelldefels and it was demonstrated to be less sensitive to speckle effects than the commonly used Canny Edge Detector. Using the SAR images of the urban beach of Somorrostro, the Canny detector was not able to extract the shoreline, while the new algorithm could do it but with low accuracy because of the noise induced by man-made structures. For further investigation, the Sentinel-2-extracted shorelines were also compared to the ones extracted by a state-of-the-art tool, CoastSat, in the two beaches using both automatic and manual thresholds. The mean errors obtained with J-Net Dynamic were generally higher than the ones from CoastSat using the manual threshold but lower if using the automatic one. The proposed methodology including the J-Net Dynamic algorithm proves to extract the shorelines closer to the reference in most of the cases and offers the great advantage of being able to work with both optical and SAR images. This feature could allow to reduce the time lag between satellite derived shorelines paving the way to an enhanced monitoring and management of coastal areas. Full article

Automated surveillance systems based on machine learning and computer vision constantly evolve to improve shipping and assist port authorities. The data obtained can be used for port and port property surveillance, traffic density analysis, maritime safety, pollution assessment, etc. However, due to the lack of datasets for video surveillance and ship classification in real maritime zones, there is a need for a reference dataset to compare the obtained results. This paper presents a new dataset for estimating detection and classification performance which provides versatile ship annotations and classifications for passenger ports with a large number of small- to medium-sized ships that were not monitored by the automatic identification system (AIS) and/or the vessel traffic system (VTS). The dataset is considered general for the Mediterranean region since many ports have a similar maritime traffic configuration as the Port of Split, Croatia. The dataset consists of 19,337 high-resolution images with 27,849 manually labeled ship instances classified into 12 categories. The vast majority of the images contain the port and starboard sides of the ships. In addition, the images were acquired in a real maritime zone at different times of the year, day, weather conditions, and sea state conditions. Full article

Human-induced carbon emissions are altering the modern climate, with severe repercussions on ecosystems. Among others, anthropogenic pressure is causing deoxygenation of the bottom water, with the widespread establishment of hypoxic zones in several Mediterranean areas. The geological archives allow investigating past deoxygenation dynamics (sapropel events) and their impact on marine ecosystems. Here, we compare the causes and the evolution of deoxygenation dynamics which occurred during two different time periods (Messinian and Holocene) in different paleoceanographic settings based on their micropaleontological content. The Messinian sapropel events are the result of increased export productivity during a relatively cold and arid context, triggering bottom anoxic conditions. The Holocene sapropel formed in response to weakening/stopping of the thermohaline circulation due to increasing temperature and freshwater input. Our results suggest that the deoxygenation dynamics in the Mediterranean in the near future will not follow the trend characteristic of the Holocene deep-sea sapropel because of the predicted drying trend. Differently, the paleoceanographic setting triggering the Messinian shallow-sea sapropels is comparable with the modern situation in different Mediterranean areas, where human-induced eutrophication is promoting deoxygenation. Based on these results, we suggest that the patchy deoxygenation trend in the Mediterranean Sea caused by climate warming may lead to a drastic change in the ecosystem services which would likely impact human activities. Full article

This study presents the results of economic and environmental analysis for two types of zero-emission ships (ZESs) that are receiving more attention to meet strengthened environmental regulations. One of the two types of ZES is the ZES using only the energy storage system (All-ESS), and the other is the ZES with fuel cell and ESS hybrid system (FC–ESS). The target ship is a tug operating in South Korea, and the main parameters are based on the specific circumstances of South Korea. The optimal capacity of the ESS for each proposed system is determined using an optimization tool. The total cost for a ship’s lifetime is calculated using economic analysis. The greenhouse gas (GHG) emission for the fuel’s lifecycle (well-to-wake) is calculated using environmental analysis. The results reveal that the proposed ZESs are 1.7–3.4 times more expensive than the conventional marine gas oil (MGO)-fueled ship; however, it could be reduced by 1.3–2.4 times if the carbon price is considered. The proposed ZESs have 58.7–74.3% lower lifecycle GHG emissions than the one from the conventional ship. The results also highlight that the electricity- or hydrogen-based ZESs should reduce GHG emissions from the upstream phase (well-to-tank) to realize genuine ZESs. Full article

This paper proposes an algorithm that performs the task of tracking the desired trajectory for underactuated marine vehicles (primarily underwater) that move horizontally. The control scheme, which takes into account model inaccuracies and external disturbances, was designed using the quantities obtained after the transformation of the dynamic equations of motion resulting from the decomposition of the inertia matrix. This, in turn, led to the equation of dynamics with a diagonal inertia matrix. A specific feature of the offered controller is its dual role. It not only allows tracking the desired trajectory, but at the same time, makes it possible to estimate the impact of dynamic couplings when the vehicle is in motion. Such an approach to the tracking task is important at the initial design stage when the choice of the control algorithm has not yet been decided and experimental tests have not been performed. This is feasible because the new variables after the velocity transformation include not only vehicle parameters, but also actual velocities and forces. Therefore, it is also possible to track the original variables. The theoretical results were followed up with simulation tests conducted on a model with three degrees of freedom for two underwater vehicles. Full article

Due to light absorption and scattering underwater images suffer from low contrast, color distortion, blurred details, and uneven illumination, which affect underwater vision tasks and research. Therefore, underwater image enhancement is of great significance in vision applications. In contrast to existing methods for specific underwater environments or reliance on paired datasets, this study proposes an underwater multiscene generative adversarial network (UMGAN) to enhance underwater images. The network implements unpaired image-to-image translation between the underwater turbid domain and the underwater clear domain. It has a great enhancement impact on several underwater image types. Feedback mechanisms and a noise reduction network are designed to optimize the generator and address the issue of noise and artifacts in GAN-produced images. Furthermore, a global–local discriminator is employed to improve the overall image while adaptively modifying the local region image effect. It resolves the issue of over- and underenhancement in local regions. The reliance on paired training data is eliminated through a cycle consistency network structure. UMGAN performs satisfactorily on various types of data when compared quantitatively and qualitatively to other state-of-the-art algorithms. It has strong robustness and can be applied to various enhancement tasks in different scenes. Full article

Discretization is the process of converting a continuous function or model or equation into discrete steps. In this work, learning and adaptive techniques are implemented to control DC motors that are used for actuating control surfaces of unmanned underwater vehicles. Adaptive control is a strategy wherein the controller is designed to adapt the system with parameters that vary or are uncertain. Parameter estimation is the process of computing the parameters of a system using a model and measured data. Adaptive methods have been used in conjunction with different parameter estimation techniques. As opposed to the ubiquitous stochastic artificial intelligence approaches, very recently proposed deterministic artificial intelligence, a learning-based approach that uses the physics-defined process dynamics, is also applied to control the output of the DC motor to track a specified trajectory. This work goes further to evaluate the performance of the adaptive and learning techniques based on different discretization methods. The results are evaluated based on the absolute error mean between the output and the reference trajectory and the standard deviation of the error. The first-order hold method of discretization and surprisingly large sample time of seven-tenths of a second yields greater than sixty percent improvement over the results presented in the prequel literature. Full article

Around the world, the development of electric vehicles is underway, including in maritime transportation. However, the development of clean energy vessels still has a long way to go. Fuel cells (FCs) are a relevant choice among the many clean energy sources to power clean energy vessels. However, due to the complex and drastic change in the shipload power, FCs need to be equipped with dynamic fast-response energy storage equipment to make up for it. For multiple energy storage devices connected in parallel, the state of charge (SOC) is not balanced, which affects their service life and the stability of the vessel microgrid, as well as slowing the speed and lowering the accuracy of SOC equalization. This paper proposes a distributed variable sag slope control strategy for vessels to improve SOC equalization, with a FC as the energy source and a battery and supercapacitor as the energy storage system (ESS). For the output power distribution problem of energy storage equipment caused by shipload power variation, a power distribution strategy with a variable filter time constant is used to improve the reasonableness of the output power distribution of energy-based lithium batteries and power-based supercapacitors. Meanwhile, this paper considers the power generation equipment’s service life and energy cost as the optimization objectives, considering the discharge depth of the energy storage equipment. Finally, a method based on the combination of the lithium battery SOC rule (the rule formulated according to the state of charge and load power change in energy storage equipment) and particle swarm optimization algorithm is proposed to solve this problem. The simulation results show that the proposed strategy improves the equalization speed and accuracy of the SOC of energy storage devices, fully realizes the characteristics of different energy storage devices, and reduces the life loss of energy storage devices. Full article

The ship hull structure is composed of plates and stiffened panels. Estimating the maximum load-carrying capacity, or the ultimate strength, of these structural components is fundamental. One of the main challenges nowadays is the implementation of new materials and technologies to enhance the structural integrity, economy, safety and environmentally friendly design of the ship’s hull structure. A new design solution may be represented by aluminium alloy honeycomb sandwich structures, both as plane panels or stiffened ones, which are characterised by excellent impact-absorption capabilities and a high stiffness-to-weight ratio. Still, their response to some conditions typical of ship structural design needs to be deeply investigated. Axial compressive loading is one of the most critical conditions that could impact the structural integrity of such light-weight solutions. Hence, the uniaxial compressive behaviour of aluminium honeycomb sandwich structures has to be deeply investigated to promote their integration in ship structural design. Within this context, the present work performs an experimental and numerical study of a honeycomb sandwich panel subjected to uniaxial compressive loads. The results will help develop models for predicting the uniaxial compressive load-carrying capacity of hybrid honeycomb sandwiches of aluminium alloy design. Full article

To date, hydraulic collection is the most widely considered technology in polymetallic-nodule mining, since there is no direct contact between hydraulic collectors and ocean floor. To construct a hydraulic collector that results in the least sediment disturbance, it is critical to develop an insightful understanding of the interaction between the collector and sediment bed. To this end, we conducted a set of small-scale experiments in which several operational conditions were tested, delivering the first quantitative data for sediment erosion resulting from a hydraulic collector driving over a sand bed. This paper presents and discusses the experimental results and observations. It is found that the collector’s forward velocity is inversely proportional to the bed-sediment erosion depth, since the bed is exposed to the flow for a longer time when the collector drives slower and vice versa. In contrast, an increased jet velocity leads to a larger erosion depth. Furthermore, when the collector underside is nearer to the sediment bed, a larger sediment layer is exposed to the water flow, resulting in a larger erosion depth. Finally, the experimental results show that collector water jets strike the sediment bed under an inclined angle, destabilizing the upper sediment layer and consequently dragging sediment particles along toward the collection duct and behind the collector head. This study improves the predictability of sediment erosion created by Coandă-effect-based collectors, which is a crucial asset to optimize the collector design and decrease the extent of the associated sediment plumes. 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

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

Primary production in the Southern Ocean highly depends on phytoplankton and has been reported to be limited by the availability of the micronutrient iron. The aim of this review is to summarize the past and current knowledge on iron limitation in the Southern Ocean, and specifically how it affects primary producers, thus influencing the whole Southern Ocean community structure, carbon cycling, and large-scale ocean biogeochemistry. In this region, extensive variability exists between different areas regarding iron availability, but also between seasons. Moreover, co-limitations with other abiotic environmental factors exist, further complicating the assessment of the role of iron as limiting factor for phytoplankton productivity. Currently, climate change is altering the Southern Ocean environment. How these changes will affect resident phytoplankton is still not clear, possibly modifying the iron supply mechanisms. Existing projections point towards a possible partial relief of iron stress on phytoplankton, but the interactions between different environmental changes, and the cascade effects they will have, are still poorly understood, and some aspects understudied. Here we try to synthetize the available predictions and uncertainties concerning this topic. Full article

In this study, a series of resonant-column experiments were conducted on marine clays from Bohai Bay and Hangzhou Bay, China. The characteristics of the dynamic shear modulus (G) and damping ratio (D) of these marine clays were examined. It was found that G and D not only vary with shear strain (γ), but they also have a strong connection with soil depth (H) (reflected by the mean effective confining pressure (σ_m) in the laboratory test conditions). With increasing H (σ_m) and fixed γ, the value of G gradually increases; conversely, the value of D gradually decreases, and this is accompanied by the weakening of the decay or growth rate. An intelligent model based on a back-propagation neural network (BPNN) was developed for the calculation of these parameters. Compared with existing function models, the proposed intelligent model avoids the forward propagation of data errors and the need for human intervention regarding the fitting parameters. The model can accurately predict the G and D characteristics of marine clays at different H (σ_m) and the corresponding γ. The prediction accuracy is universal and does not strictly depend on the number of neurons in the hidden layer of the neural network. Full article