Abstract: This paper introduces a novel approach to modeling and control system design for tugboat-assisted operations, such as docking and rescuing marine vessels. The control objective is to ensure effective positioning and movement of the vessels while maintaining overall system stability, even in the presence of system uncertainties, imperfect control allocation, and ocean disturbances. First, a mathematical model of a general tugboat-assisted system is derived. Second, a new vector of variables is introduced, leading to a modified model representation where the mismatches from the allocation and lower-level tugboat controllers can be realized in the vessel’s motion equation. Thus, the design of a supervisory controller for the vessel can take this aspect into account to enhance the overall system’s performance and stability. Then, a control system design method is proposed, employing a centralized control framework and ensuring a mixed H₂/H∞ performance criterion. Finally, a case study is conducted with a particular tugboat-assisted configuration and the results validate the effectiveness of the control solution.

Abstract: Wave energy converters (WECs) have gained significant attention as a promising renewable energy source. Optimal control strategies, crucial for maximizing energy extraction, have traditionally relied on linear models based on small motion assumptions. However, recent studies indicate that these models do not adequately capture the complex dynamics of WECs, especially when large motions are introduced to enhance power absorption. The nonlinear Froude-Krylov (FK) forces, particularly in heaving point absorbers with varying cross-sectional areas, are acknowledged as key contributors to this discrepancy. While high-fidelity computational models are accurate, they are impractical for real-time control applications due to their complexity. This paper presents a parameterized approach for expressing nonlinear FK forces across a wide range of point absorber buoy shapes inspired by implementing real-time, model-based control laws. The model was validated using measured force data for a stationary spherical buoy subjected to regular waves. The FK model was also compared to a closed-form buoyancy model, demonstrating a significant improvement, particularly with high-frequency waves. Incorporating a scattering model further enhanced force prediction, reducing error across the tested conditions. The outcomes of this work contribute to a more comprehensive understanding of FK forces across a broader range of buoy configurations, simplifying the calculation of the excitation force by adopting a parameterized algebraic model and extending this model to accommodate irregular wave conditions.

Abstract: This work aims to analyze the responses of eight floating wind turbines. From this perspective, this paper will compare the response offset regarding the motions of the six degrees of freedom of the respective floating wind turbines. The applied forces these analyses consider mainly come from constant wind forces applied on the wind turbines’ blades, as well as forces from waves and currents. Different response offset values are considered and compared regarding the different constant wind speeds, as well as the different velocities of waves and currents. This paper also considers a wide range of innovative references related to floating wind turbine analyses and software. Validation and verification studies are left for future work due to the complexity of the data provided in this paper. However, some comparisons will be made between the obtained analysis results and some external references. These references may have floating wind turbines with different wind and wave environmental conditions, power capacities, and dimensional characteristics.

Abstract: The global energy transition has spurred the rapid development of LNG (Liquefied Natural Gas) as a cleaner alternative to traditional fossil fuels. As LNG demand grows, the role of specialized LNG bunkering ships becomes increasingly critical for efficient maritime fuel supply. Among these vessels, aluminum alloy IMO B-type tank LNG bunkering ships have emerged as a promising solution, combining lightweight construction, high safety standards, and adaptability to diverse operational environments. This paper explores the technical innovations driving this ship type and evaluates its potential in reshaping the LNG bunkering landscape.

Abstract: The soil-pile interaction damping plays a crucial role in reducing wind turbine loads and fatigue damage in monopile foundations, thus aiding in the optimized design of offshore wind structures and lowering construction and installation costs. Investigating the damping properties at the element level is essential for studying monopole-soil damping. Given the widespread distribution of silty clay in China's seas, it is vital to conduct targeted studies on its damping characteristics. The damping ratio across the entire strain range is measured using a combination of resonant column and cyclic simple shear tests, with the results compared to predictions from widely used empirical models. The results indicate that the damping ratio-strain curve for silty clay remains "S"-shaped, with similar properties observed between over-consolidated and normally consolidated silty clay. While empirical models accurately predict the damping ratio at low strain levels, they tend to overestimate it at medium to high strain levels. This discrepancy should be considered when using empirical models in the absence of experimental data for engineering applications. The results in this study are significant for offshore wind earthquake engineering and structural optimization.

Abstract: Natural gas hydrates (shorted as hydrates) are expected to be a prospective alternative for traditional fossil energies in the future. The main strategy of exploring hydrates is achieved by dissociating solid hydrates into gas and water in situ with the depressurization method. Many studies have been conducted to understand the process of hydrate dissociation in porous media from perspectives of temperature, fluid flow, mechanical deformation and hydrate saturation. However, we have few deeper analyses on the evolutions of heat and energy, which are implicit essences compared with the explicit temperature. Thus this paper focuses the changes of heat and energy during depressurization-induced natural gas hydrate dissociation in porous media by fully coupled THMC modelling. Results show that the cumulative conduction heat tends to increase first and then decrease during the dissociation of hydrate, while the cumulative convection heat has the tendency of increasing monotonically in the whole process. Phase change, conduction heat, advection heat and external heat play different roles in the change of energy in the hydrate-bearing porous media. External heat source increases the energy, while phase change has a negative effect on the change of energy. The role of conduction heat is minor, but the contribution of advection heat is considerable for the change of energy. Additionally, a comprehensive analysis of changes of heat and energy is suggested to carry out more observation after hydrate dissociation due to the unceasing advection heat and external heat supply. New findings provides new insights into the mechanism of hydrate dissociation and has implications to the real-world project of hydrate exploration in terms of energy evaluation.

Abstract: Ports serve as logistical hubs through which approximately 80% of the world's goods are transported annually. New regulations from the International Maritime Organization (IMO) and the European Union require both ships and ports to implement measures designed to reduce the environmental, global, and local impact of port activities and mitigate climate change. These measures involve investing in renewable energy generation systems to transition from fossil fuel-based energy to renewable electricity. Consequently, constructing new power generation plants is necessary to meet ports' energy demands. However, ports are primarily logistics-focused platforms with limited space for other activities. Therefore, the use of port service areas, inner docks, and exterior/adjacent water zones for installing marine renewable energy generation plants is under consideration. This study employs high-resolution meteorological and oceanographic modelling, including wave agitation models validated with real-world data, to assess the feasibility of integrating marine renewable energy within port service areas.

Abstract: This paper focuses on the ship control system and studies the problem of unknown control direction. Considering that the traditional Nussbaum gain method has to consider the complex situation where the gain converges to both positive and negative infinity when proving the system stability, a unilateral Nussbaum function is defined in this paper. By constructing this function, the design and proof process of the adaptive Nussbaum gain method are simplified. Taking the ship course - keeping control system as the research object, a course angle tracking controller is designed by combining neural network, robust adaptive and sliding mode control techniques. A dual - input RBF single - output neural network is used to approximate the uncertain part of the system, and the robust adaptive control is adopted to deal with the unknown disturbance. The simulation results show that the proposed method can effectively cope with the problems of unknown control direction and its jump, keeping the system stable, which has great theoretical and engineering application value.

Abstract: This work investigates the water exit problems of slender cylinders under various con-ditions by experiment. The experimental platform is designed with a high-speed pho-tography. 13 experimental cases with varying head shapes, length-to-diameter ratios, ejection velocities, and elastic moduli was conducted to capture water-exit character-istics. The investigation identified ejection velocity as the predominant parameter governing cavity morphology and stability, with higher velocities correlating to in-creased cavity dimensions and reduced drag coefficients. Conical head shape resulted in superior drag reduction characteristics, forming a typical cigar-shaped cavity with clear and regular boundaries. Additionally, an increased length-to-diameter ratio sub-stantially improved drag reduction performance. Material elastic moduli proved cru-cial for water-exit stability, as cylinders with lower moduli experienced severe bending deformation and even trajectory changes, while higher moduli cylinders maintained their form with minimal deformation. This study illuminates the physical mechanisms of slender body water-exit under multi-factor coupling conditions, providing experi-mental evidence and theoretical guidance for cross-media vehicle design and under-water equipment optimization.

Abstract:

The underwater conditions of the coastal ecosystem require careful monitoring to anticipate potential environmental hazards. Moreover, the unique characteristics of the marine underwater environment have presented numerous challenges for the advancement of underwater sensor networks. Current studies have not extensively integrated Digital Twins with underwater sensor networks aimed at monitoring the marine ecosystem. Consequently, this study proposes a decision-making framework based on Underwater Digital Twins (UDT) utilizing the Exponential Hyperbolic Crisp Adaptive Network-based Fuzzy Inference System (EHC-ANFIS). The process begins with the initialization and registration of the Underwater Autonomous Vehicle (UAV). Subsequently, data is collected from the sensor network and relayed to the UDT. To ensure efficient data transmission, the optimal path is determined using Adaptive Pheromone Ant Colony Optimization (AP-ACO). Following this, data compression is achieved through the Sliding-Huffman Coding (SHC) algorithm. To enhance data security, the Twisted Koblitz Curve Cryptography (TKCC) method is employed. Additionally, an Anomaly Detection System (ADS) is trained, which involves the collection and pre-processing of sensor network data. The Radial Chart is then utilized for effective visualization. Anomalies are detected using the CosLU - Variational Shake - Long Short-Term Memory (CosLU -VS-LSTM) approach. For standard data, decision-making based on UDT is conducted using EHC-ANFIS, with a fuzzification duration of 21045 milliseconds. Finally, alerts are dispatched to the Maritime Alert Command Centre (MACC). This approach enhances maritime communication and monitoring along coastal areas, with specific reference to the Coromandel Coast, thereby contributing to the protection of the coastal ecosystem.

Abstract: This study develops and validates a three-dimensional CFD model for a 12-liter large-bore active-type pre-chamber spark-ignition (PCSI) engine fueled by natural gas. The model incorporates an advanced Extended Coherent Flamelet Model (ECFM-3Z) with a tuned stretch factor to capture complex turbulence–flame interactions, flame propagation, and pollutant formation under ultra-lean conditions. By systematically varying pre-chamber geometries—specifically orifice diameter, cone angle, diverging-tapered nozzle and volume—the simulations assess their effects on combustion dynamics, heat release rates, turbulent jet penetration, and emissions (NOx and CO). Model predictions of in-cylinder and pre-chamber pressure profiles, combustion phasing, and emission trends are validated against experimental data. The results demonstrate that optimizing pre-chamber and orifice configurations enhances turbulent mixing, accelerates flame development, and reduces local high-temperature zones, thereby suppressing NOx and CO formation. Although some discrepancies in NOx predictions persist due to limitations in current turbulence–chemistry models, the findings offer valuable insights for the design of high-efficiency, low-emission PCSI engines.

Abstract: Ship wake detection plays a crucial role in compensating for target detection failures caused by defocusing or displacement in SAR images due to vessel motion. This study addresses the challenge of enhancing wake features in high-resolution spaceborne SAR by exploiting the distinct linear characteristics of wake echoes and the random motion of ocean background clutter. We propose a novel method based on sub-aperture image sequences, which integrates equivalent multi-channel technology to fuse wake and wave information. This approach significantly improves the quality of raw wake images by enhancing linear features and suppressing background noise. The Radon transform is then applied to evaluate the enhanced wake images. Through a combination of principle analysis, enhancement processing, and both subjective and objective evaluations, we conducted experiments using real data from AS01 SAR satellite and compared our method with traditional wake enhancement techniques. The results demonstrate that our method achieves significant wake enhancement and improves the recognition of detail wake features.

Abstract:

The article offers a solution to the current problem of determining the values of longitudinal accelerations acting on the ship when it encounters a wave. There is insufficient information on the values of this quantity in existing published works. In some IMO documents, the data obtained by research are given and proposed for calculating the strength of the means for securing the cargo on the ship. It became necessary to create a theoretical basis for calculations of this type and calculations related to the effect on the physiological state of the crew of these accelerations and ensuring the strength of ship structures. It is proposed to calculate the longitudinal accelerations using a new formula for calculating the longitudinal force. This formula is derived after analysing the expression for the Energy Wave Criterion (EWC), which is based on the ratio of the total wave energy to the vessel's kinetic energy. The total wave energy is calculated by representing the wave profile as a trochoid. The similarity of the Energy Wave Criterion and Newton's criterion was revealed. For different ratios of length and height of the wave, the values of longitudinal accelerations were calculated and a comparison of these values with the results obtained by research was carried out.

Abstract: The maritime industry is a major contributor to global greenhouse gas emissions, for which new and innovative tools need to be developed to enhance energy efficiency and cut ship emissions. This paper introduces ShipNetSim, an open-source multi-vessel simulator that targets real-time quantification of marine fuel consumption and emissions over large-scale shipping networks. ShipNetSim combines propulsion-resistance models, ship-following dynamics, and path finding algorithms with the ability to simulate the longitudinal vessel motion and provide insight into the vessels’ energy consumption and their environmental impact. The simulator adapts to changing ship type, environmental conditions, and fuel sources, providing robust and scalable performance. Using real routes and ship specifications, case studies performed confirm the accuracy of the model and highlights the potential for fuel-consumption and operational-efficiency improvements. Additionally, the ability of the simulator to model operational policy-driven changes in the form of reduced speeds or alternative fueling strategies positions it as a leading-edge tool to help inform compliance with international maritime regulations, including those regarding carbon-reduction targets posed by the International Maritime Organization (IMO). Thus, ShipNetSim offers a unique mix of technical precision and environmental relevance by integrating two fields: that of maritime engineering and global sustainability efforts.

Abstract:

This paper focuses on three artificial reefs with different functionalities to be placed in the marine pasture in South Sulawesi Province, Indonesia, and investigates the effects of different incoming current velocities and headward current angles on their flow field effects, aiming to explore the flow field effects of the three reefs and analyze the functionality of their flow fields and flow regimes on the sea area. A combination of PIV experiments and numerical simulation is used to analyze the velocity at the measurement point of the flume, the characteristics of the cross-section flow pattern, and the flow field effects under different incoming velocities and head-on angles, and the accuracy of numerical simulation is verified by flume tests. The results show that the changes in the incoming velocity and the angle of flow on the three reefs have different effects on the volume of upwelling and back eddy; the shape of the reef and the internal structure of the reef do not have any impact on the flow pattern, and the changes of the flow field are different under different conditions. The scale of the flow field reaches the optimization under specific conditions.

Abstract: The transition to a low-carbon future necessitates innovative approaches to renewable energy deployment, particularly in the marine environment, where abundant resources remain underutilized. This paper explores the potential of hybrid renewable energy systems and green hydrogen production to address the energy challenges faced by Very Small Islands (VSIs). These islands heavily rely on imported fossil fuels, making them vulnerable to global price fluctuations and contributing to economic instability and environmental degradation. Offshore floating platforms present a transformative opportunity by harnessing marine renewable resources, integrating wind, solar, and wave energy to maximize energy production while minimizing land use conflicts. Green hydrogen, produced through electrolysis of sea water, powered by these renewable sources, offers a sustainable alternative for decarbonizing transportation, particularly in the maritime sector. The study aims to assess the feasibility of converting small conventional passenger vessel to hydrogen propulsion and evaluate the technical, economic, and environmental impacts of deploying offshore platform for hydrogen production. By examining these aspects, this research contributes to the broader discourse on sustainable energy solutions for island communities and provides actionable insights into implementing renewable hydrogen-based maritime transport.

Abstract: This study presents a methodological framework for incorporating LCA principles into the preliminary design phase of an offshore vessel, based on the case of the wind farm installation vessel (WTIVs). The proposed approach diverges from traditional ship design methodologies by treating environmental impact as a key criterion and integrates the LCA into the early design stages of offshore vessels which is a novelty toward the sustainability-driven ship design. On the basis of steps usually conducted in preliminary ship design a parametric analysis was conducted to estimate the life-cycle emissions associated with shipbuilding, operation, maintenance, and dismantling phases, with special attention given to the operational profiles of WTIVs. Using statistical regression models, ship characteristics such as displacement, lightship weight, and main dimensions were correlated with LCA-relevant factors, enabling the quantification of emissions at an early design stage. Power demand estimation for different operational scenarios—free running transit, dynamic positioning, and stationary installation—highlighted the significant contribution of offshore-specific vessel activities to life-cycle emissions. The results demonstrate that the structure operational phases remain the dominant contributor to overall emissions, particularly through CO₂ and NOx production. However, emissions from shipbuilding, maintenance, and dismantling also play a critical role, reinforcing the need for early design interventions The findings emphasize the importance of integrating LCA considerations into the design spiral to achieve optimized trade-offs between environmental sustainability, operational efficiency, and economic feasibility. This study provides a foundation for future research into multi-objective optimization models that incorporate LCA into offshore vessel design.

Abstract: Port pricing strategies are key tools for optimizing revenue, enhancing competitiveness, and ensuring efficient resource allocation. To help port operators effectively utilize the port yard, this paper investigates the port yard storage pricing problem under varying free storage periods and pricing strategy ranges. This problem involves a revenue game between the container yard (CY), remote container yard (RCTY), and carriers, in this game problem, each player has a large range of decision variables, which significantly increases the complexity of the entire problem. Based on carrier data from port services, we use a voting clustering approach to group multiple carriers, this can significantly reduce the pricing calculation complexity for port operators. Subsequently, we establish game-theoretic pricing models for CY, RCTY, and the carriers, both before and after the implementation of pricing clustering. During the pricing strategy simulation phase, we conduct sensitivity analysis on pricing ranges and free storage periods, using data from a port in Southeast China. The final conclusions related to port pricing are derived from this analysis, providing management insights for CY operators.

Abstract: According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults suffer from attention deficit hyperactivity disorder (ADHD). This disorder can have significant negative consequences on people’s lives, particularly children. In recent years, methods based on artificial intelligence and neuroimaging techniques, such as MRI, have made significant progress, paving the way for more reliable diagnostic methods than traditional clinical approaches. In this paper, we present our machine learning based analytical approach, more precisely, a novel feature extraction technique, to more accurately and reliably diagnose ADHD using clinically available neuroimaging data. Utilizing the ADHD200 dataset, which encompasses demographic factors and anatomical MRI scans in a diverse ADHD population, our study focuses on leveraging modern machine learning methods. The preprocessing stage employs a pre-trained Visual Geometry Group16 (VGG16) network to extract Two-Dimensional (2D) feature maps from anatomical 3D MRI data, thereby reducing computational complexity and enhancing efficiency. The inclusion of personal attributes, such as age, gender, intelligence quotient, and handedness, strengthens the diagnostic models. Four deep-learning architectures, Convolutional Neural Network 2D (CNN2D), CNN1D, Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU), were explored for the analysis of the MRI data, with and without inclusion of clinical characteristics. A 10-fold cross-validation revealed that the LSTM model, which incorporated both MRI data and personal attributes, had the best performance, achieving higher accuracy (0.8637) and area under the curve (AUC:0.9025). Our findings demonstrate that the proposed approach, which extracts 2D features from 3D MRI images and integrates these features with clinical characteristics, may be useful in diagnosis of ADHD with high accuracy.

Abstract: Recently, the maritime logistics industry has been transitioning to smart logistics by leveraging such technologies as AI and IoT. In particular, maritime big data plays a significant role in providing various services, including ship operation monitoring and greenhouse gas emissions assessment, and is considered essential for delivering maritime logistics services. Marine big data comprises real-world data collected during ship operations, but it is susceptible to loss due to temporal and environmental constraints. Together with identifying and addressing the root causes of data loss, it is mandatory to supplement the loss by analyzing and utilizing the collected data. This study proposes an emulator that repetitively generates new data such as location data, data count, and average distance using maritime transport data cumulated up to now. The location data is generated using the cumulative distance and trigonometric ratios based on the location information of standard routes. The data count and average distance are calculated based on user-input parameters such as voyage time and data interval. The generated data is inserted into a database and monitored on a map in real time. To evaluate the emulator's performance, experiments were conducted using the maritime transport route data, and the results demonstrated its effectiveness.