Abstract: Autonomous underwater vehicles (AUVs) face significant challenges in complex dynamic marine environments, where ocean currents, uncertain obstacles, and in-ter-vehicle interactions increase collision and mission failure risks. This study proposes a risk-aware cooperative path planning framework for multiple AUVs that integrates conditional Bayesian networks (CBN) for probabilistic environmental risk assessment directly into a receding horizon optimization scheme. The approach models AUV kinematics under time-varying ocean currents, incorporates collision avoidance, en-ergy consumption, path smoothness, and dynamic risk constraints derived from CBN-inferred probabilities. Risk levels are mapped nonlinearly to enable gradi-ent-based optimization while maintaining continuous sensitivity. The framework is evaluated through Monte Carlo simulations in a realistic South China Sea canyon en-vironment using HYCOM reanalysis current data, with comparisons against baseline methods. Results demonstrate substantial improvements: mission success rate increas-es by up to 35%, energy consumption decreases by 12–18%, path smoothness improves, and risk exposure is significantly reduced across various current intensities and obsta-cle densities. This method enhances operational safety and efficiency for cooperative AUV missions in uncertain dynamic oceans, offering a promising engineering solution for real-world underwater applications. This work presents an engineering-oriented framework that embeds a CBN-derived probabilistic risk index into cooperative re-ceding-horizon trajectory optimization for multi-AUV systems operating under realis-tic, time-varying ocean current fields. The main contributions of this work are summarized as follows: (1) A risk-aware cooperative path planning framework is developed for mul-ti-AUV systems, in which a probabilistic environmental risk model based on a Conditional Bayesian Network (CBN) is directly embedded into a reced-ing-horizon optimization process, rather than used as a post hoc evaluation or external safety filter. (2) Unlike existing deterministic or purely reactive approaches, the proposed CBN-based risk inference mechanism enables the planner to explicitly reason about coupled terrain–current–uncertainty effects, providing a continuous risk gradient that cannot be obtained from binary obstacle representations. (3) The proposed receding-horizon cooperative optimization embeds probabilis-tic risk directly into the planning objective, allowing multi-AUV systems to proactively trade off efficiency and safety in a mathematically tractable manner, rather than relying on post hoc risk filtering. (4) The effectiveness and practical applicability of the proposed method are demonstrated through extensive Monte Carlo simulations in a realistic sub-marine canyon environment using reanalysis-based ocean current data, showing statistically consistent improvements in mission success rate, energy efficiency, trajectory smoothness, and reduction of high-risk exposure com-pared with a baseline cooperative planning strategy. The proposed framework provides a practical and scalable solution for real-world multi-AUV missions, with potential applications in marine environmental monitoring, seabed surveying, underwater inspection, and ocean engineering operations.

Abstract: Stiffened panels are essential structural elements that play a critical role in maintaining the integrity of engineering structures, particularly when subjected to torsional loading. Ensuring their adequate strength is therefore a fundamental requirement in design and assessment. Conventional approaches to strength evaluation using the finite element method (FEM) often face challenges due to the complexity of modeling stiffened geometries and the time-consuming setup required, which can reduce efficiency and limit accessibility for practical applications. To overcome these limitations, this study introduces the development of a graphical user interface (GUI) specifically designed to facilitate FEM-based strength analysis of stiffened panels under torsional loads. The GUI, implemented in Python, automates essential modeling steps, streamlines the input process, and enhances user interaction through an intuitive interface, thereby making torsional strength analysis more efficient and user-friendly. Numerical simulations were carried out on nine panel configurations, systematically combining three variations of plate thickness with three variations of longitudinal stiffener geometry. The results demonstrate that plate thickness has a direct influence on torsional resistance, with thicker plates exhibiting significantly higher strength, while stiffener design was also found to strongly affect performance: the 80 x 80 x 8 stiffener provided the greatest resistance against general torsional loading, whereas the 100 x 65 x 9 stiffener displayed superior behavior under pure torque conditions. These findings are consistent with theoretical predictions, confirming the reliability of the developed approach, and overall, the proposed GUI proves to be an effective tool in supporting FEM-based strength assessment of stiffened panels, offering both accuracy and efficiency while highlighting the potential of integrating computational modeling with user-oriented interfaces to broaden the applicability of FEM in structural engineering practice, particularly in analyzing complex torsional behaviors of stiffened panel systems.

Abstract: Suspended sediment concentration affects the erosion and deposition of estuaries and coastal zones, and affects channel construction and safety. Sediment settling velocity controls sediment transport and sedimentation processes, and is crucial for assessing sediment distribution, diffusion, and material transport. As an important means for the inversion study of sediment concentration in estuaries and coasts, remote sensing alone cannot establish a model of the nearshore suspended sediment concentra-tion field by inverting surface sediment. Based on the remote sensing inversion of surface sediment, this study, in combination with the vertical distribution calculation method of sediment concentration in estuaries, inversely deduced the sediment concentration patterns in the middle and bottom layers, and proposed a sediment settling velocity calculation formula considering turbulent shear and concentra-tion influence. The results show that the highest concentration of suspended sediment in the study area appears in the east of Guan River Estuary, which is characterized by a high concentration in the east and a low concentration in the west. At a low suspended sediment concentration, the settling velocity is positively correlated with the suspended sediment concentration. At a high suspended sediment con-centration, the two are negatively correlated. The method introduced in this study is simple and feasi-ble, and the results are stable and reliable. It can be effectively used to evaluate the suspended sediment concentration and sediment settling velocity in different research areas.

Abstract: Driven by global initiatives to mitigate climate change, the offshore wind power industry is experiencing rapid growth. Personnel transfer between service operation vessels (SOVs) and offshore wind turbines under complex sea conditions remains a critical factor governing the safety and efficiency of operation and maintenance (O&M) activities. This study establishes a fully coupled dynamic response and control simulation framework for an SOV equipped with an active motion-compensated gangway. A numerical model of the SOV is first developed using potential flow theory and frequency-domain multi-body hydrodynamics to predict realistic vessel motions, which serve as excitation inputs to a co-simulation environment (MATLAB/Simulink coupled with MSC Adams) representing the Stewart platform-based gangway. To address system nonlinearity and coupling, a composite control strategy integrating velocity and dynamic feedforward with three-loop PID feedback is proposed. Simulation results demonstrate that the composite strategy achieves an average disturbance isolation degree of 21.81 dB, significantly outperforming traditional PID control. Validation is conducted using a ship motion simulation platform and a combined wind-wave basin with a 1:10 scaled prototype. Experimental results confirm high compensation accuracy, with heave variation maintained within 1.6 cm and a relative error between simulation and experiment of approximately 18.2%.

Abstract: Microplastic quantification in marine vegetated ecosystems remains analytically demanding, yet little is known about the environmental footprint of the laboratory procedures required to isolate and measure these particles. This study applies Life Cycle Assessment (LCA) to laboratory analytical workflows for microplastics quantification, focusing exclusively on sample preparation and analytical procedures rather than natural environmental absorption or fate processes, in two ecologically relevant matrices: (i) pelagic algae (Sargassum) and (ii) seagrass biomass. Using openLCA 2.5 and the ReCiPe Midpoint (H) v1.13 method, the analysis integrates foreground inventories of digestion, filtration, drying, and spectroscopic identification, combined with background datasets from OzLCI2019, ELCD 3.2 and USDA. Results show substantially higher impacts for the algae scenario, particularly in climate change, human toxicity, ionising radiation and particulate matter formation, largely driven by longer digestion times, increased reagent use and higher energy demand during sample pre-treatment. Conversely, the seagrass scenario exhibited lower burdens per functional unit due to reduced organic complexity and shorter laboratory processing requirements. These findings highlight the importance of matrix-specific methodological choices and the influence of background datasets on impact profiles. The study provides a first benchmark for the environmental performance of microplastic analytical workflows and underscores the need for harmonised, low-impact laboratory protocols to support sustainable monitoring of microplastic pollution in marine ecosystems.

Abstract: The development of autonomous cargo ships necessitates reliable anchoring operations, a critical challenge due to low-speed maneuverability issues and anchorage disturbances. This paper addresses the challenges of reduced maneuverability at low speeds and susceptibility to anchorage disturbances in autonomous cargo ships, conducting research on anchoring decision-making methods. The process was systematically analyzed. Safety anchorage areas were quantified using ship parameters and environmental data. An available anchor position identification method based on grid theory, combined with an anchorage allocation mechanism to derive optimal anchorage selection. The development of a multi-level guided anchoring trajectory planning algorithm was informed by practical anchoring. This algorithm was designed to facilitate the scientific calculation of turning and stopping guidance points, with the objective of guiding cargo ship to navigate towards the anchorage in a predetermined attitude. An integrated autonomous anchoring system was constructed, encompassing perception, decision-making, planning, and control. Digital simulations verified the system's effectiveness and robustness under complex sea conditions. This study provides a theoretical foundation and feasible technical approach for enhancing the autonomous decision-making and safety control capabilities of intelligent ships during anchoring operations.

Abstract: Nowadays, decarbonization of the shipping industry has become the top priority of the maritime community. In an effort to reduce emissions from shipping, numerous tech-nological and design solutions are being investigated; Waste Heat Recovery (WHR) by marine engines is one of the most important and widespread ones. This paper investi-gates the utilization of a carbon dioxide Supercritical Brayton Cycle (SBC) for WHR of a LNG carrier. SBC is an innovative, promising technology for power generation with unprecedented performance and a small form factor, due to the properties of the working fluid. A thermodynamic model is developed and programmed in MATLAB using the CoolProp free library. By means of this model, the performance of simple and recuperated SBC (RSBC) for WHR of a specific marine engine at its full load operation is assessed and the optimum compressor pressure ratio for power maximization of the RSBC is selected. The combined system Diesel-RSBC exhibits an increase of about 2.9% in thermal efficiency and a similar reduction in specific fuel oil consumption, com-pared to the sole power production by the Diesel engine, at its full load operation. Sig-nificant performance benefits are also demonstrated at part-load operation of the main engine. To assess how the benefits scale with the main engine power, seven similar marine engines of different power are considered, revealing a possible relationship between the optimal pressure ratio and SBC efficiency with the engine’s exhaust gas temperature.

Abstract: This paper presents the development and validation of a 3D CFD model of a heave plate under forced oscillations using a Lattice-Boltzmann, LES software, which has never been used for industrial applications in this context. The main objective of the model is to be versatile enough to maintain accuracy in extreme cases of amplitudes and frequencies. The validation is carried out with experimental results from previous research, with some results also compared with the ones obtained using a finite-volume software. A lattice and time step convergence is achieved along with a symmetry study. Once the optimal model has been selected it is tested under 4 extreme cases, analyzing the results yielded for the force, added mass and damping coefficients and also assessing its limitations. Results show good correlation between the model and the experimentation, especially in cases of higher force values, and also with the results from the finite-volume software. Further-more, a vorticity field study will be carried out to better understand the behavior of the heave plate in these extreme cases. Finally, an assessment of the dominance of pres-sure-induced forces over viscous forces under low KC numbers is carried out using radial and surface integration.

Abstract: Against the backdrop of the global energy transition, the efficient exploitation of marine renewable energy has become a key pathway toward carbon neutrality. Wind–wave hybrid systems (WWHSs) have attracted increasing attention due to their resource complementarity, efficient spatial utilization, and shared infrastructure. However, most existing studies focus on single components or local optimization. A systematic integration of the full technology chain remains limited, hindering the transition from demonstration projects to commercial deployment. This review provides a comprehensive overview of the technological evolution and key characteristics of offshore wind turbine (OWT) foundations and wave energy converters (WECs). Fixed-bottom foundations remain the mainstream solution for near-shore development. Floating offshore wind turbines (FOWTs) represent the core direction for deep-sea deployment. Among WEC technologies, oscillating buoy (OB) WECs are the dominant research pathway. Yet high costs and poor performance under extreme sea states remain major barriers to commercialization. On this basis, the paper summarizes three major integration modes of WWHSs. Among them, hybrid configurations have become the research focus due to their structural sharing, hydrodynamic coupling, and significant cost and energy synergies. Furthermore, the review synthesizes optimization strategies for both technology design and spatial layout, aiming to enhance energy capture, structural stability, and overall economic performance. Finally, the paper critically identifies current research gaps and bottlenecks, and outlines key technological pathways required for future commercial viability. These include the development of high-performance adaptive power take-off (PTO) systems, deeper understanding of multi-physics coupling mechanisms, intelligent operation and maintenance enabled by digital twins, and comprehensive life-cycle techno-economic and environmental assessments. This review aims to provide a systematic reference for the advancement of multi-energy offshore systems and to support future integrated energy development in deep-sea environments.

Abstract: Time-domain fatigue analysis of floating offshore wind turbines (FOWTs) is accurate but often prohibitive for early-stage design. The Unit Load Response (ULR) method, based on linear superposition, offers an efficient alternative, but its application to large, shell-based structures with complex distributed loads remains a challenge. We propose a workflow that integrates ULRs with force-based submodelling to enable whole-structure fatigue screening at design cost. Two key innovations make it practical: (i) A "Virtual Test Rig" is used to create a computationally fast, stiffness-equivalent simplified global model for extracting boundary loads. (ii) A ULR catalogue is generated for a detailed local submodel, which includes a trilinear interpolation scheme (with water height, pitch, roll) to efficiently handle complex, wave pressure fields. The workflow is first verified on a canonical portal frame and then applied to a full-scale semisubmersible FOWT. Across 14 critical locations, the reconstructed stress time histories match the submodel with a median bias ≈ of approximately −3.8% to −4.9%, and the stress and fatigue rankings are preserved, with Kendall’s τ-a ≥ 0.7 at stress concentrations and τ-a ≥ 0.8 overall. Compared to classic step-by-step submodelling, the method achieves ~13-29 times lower wall-clock effort and produces outputs that are otherwise impractical at scale (e.g., full-hull damage maps), enabling earlier, more informed fatigue-driven design decisions.

Abstract: In view of the requirements and characteristics that a deep-sea polymetallic nodule collector must travel according to a planned path and speed during operation, a collector trajectory tracking system scheme based on virtual target vehicle following is proposed. In this system, the virtual target vehicle travels according to the planned path and speed, thereby generating a dynamic target path and speed. A fuzzy controller calculates the collector’s angular-velocity command based on the lateral position deviation and the heading-angle deviation between the collector and the target vehicle, and a proportional controller calculates the collector’s body linear velocity control command based on the longitudinal position deviation between the collector and the target vehicle. By integrating these two commands, the collector follows the target vehicle and thereby realizes trajectory tracking of the planned path and speed. A tracking system is designed and simulation studies are carried out. The results show that the designed system enables the collector to follow the planned path and speed well under operational conditions. The trajectory tracking method based on virtual target vehicle following can also form an organic integration of path planning and trajectory tracking, generate dynamic planned paths and speeds for the entire mining area, and realize tracking travel of the collector along the planned path and speed throughout the whole operation.

Abstract: Deep-sea cages are highly susceptible to biofouling due to long-term seawater immersion, which promotes the attachment and growth of marine organisms on nets, significantly reducing fish survival. To address this issue, this study explores the use of low-pressure abrasive-water jets (LPAWJ) for cage fouling removal through numerical simulation. Based on a Box-Behnken response surface design, nozzle inlet pressure X1, nozzle outlet diameter X2, and target distance X3 were selected as optimization parameters. The peak jet impact force Z1, stable jet impact force Z2, peak abrasive-water jet velocity Z3, and peak abrasive particle velocity Z4 were chosen as evaluation indicators to characterize the jet’s instantaneous impact ability, sustained action ability, and dynamic particle behavior. Using the entropy method, weights for each indicator were determined, and the jet’s overall removal capability was calculated. A regression model was developed by integrating numerical simulation with the response surface methodology (RSM), and the optimal parameter combination was identified as X1 = 4.5 MPa, X2 = 10 mm, and X3 = 205.396 mm. Compared with the poorest experimental condition (Condition 1), the jet’s overall removal capability obtained under the optimal parameter combination increases by 101.35%. Experimental validation further confirms that the optimized parameters yield the best oyster-removal performance of the low-pressure abrasive jet, with the average removal rate improving by 100.55% relative to Condition 1. The methodology and results of this study provide a theoretical foundation and technical reference for the design and optimization of automated net-cleaning systems or net-cleaning robots equipped with low-pressure abrasive jets. By integrating the proposed model and operating parameters, future robotic systems will be able to predict and dynamically adjust jet conditions according to fouling characteristics, thereby improving the efficiency, cost-effectiveness, and sustainability of maintenance operations in marine aquaculture.

Abstract: Marine Spatial Planning (MSP) and Terrestrial Spatial Planning (TSP) have traditionally operated as separate systems, resulting in fragmented governance of coastal territories. This article introduces Integrated Spatial Planning (ISP), a methodology that unifies MSP and TSP through a multi‑level zoning framework spanning municipal, regional, national, and international scales. ISP embeds climate change adaptation into planning instruments, ensuring resilience and sustainability in land–sea interactions. The approach is applied to the Region of Murcia (Spain), where numerous instru-ments—urban development plans, the Regional Land and Urban Planning Law, the Territorial Strategy, the Mar Menor Integrated Management Plan, the Regional Climate Change Strategy, the Segura River Basin Hydrological Plan, and Coastal Adaptation Guidelines —exist but remain fragmented. The case study highlights gaps in runoff management, infrastructure coherence, renewable energy planning, and climate adap-tation. ISP addresses these by creating integrated governance mechanisms, enhancing ecosystem protection, socio‑economic development, and adaptive coastal management.

Abstract: Underwater Vehicle-Manipulator Systems (UVMS) play a critical role in various marine operations, where the choice of manipulator architecture significantly influences system performance. While serial robotic arms have been widely adopted in UVMS applications due to their operational flexibility, their inherent structural characteristics present certain challenges in underwater environments. These challenges primarily stem from the cu-mulative effects of joint mechanisms and dynamic interactions with the fluid medium. In this context, we explore an innovative UVMS solution that incorporates the Delta parallel mechanism, which offers distinct advantages through its symmetrical architecture and unilateral motor configuration, particularly in maintaining operational stability. We de-velop a comprehensive framework that includes mechanical design optimization, imple-mentation of distributed control systems, and formulation of closed-form kinematic mod-els, with comparative analysis against conventional serial robotic arms. Experimental validation demonstrates the system's effectiveness in underwater navigation, target ac-quisition, and object manipulation under operator-guided control. The results reveal sub-stantial enhancements in motion consistency and gravitational stability compared to tra-ditional serial-arm configurations, positioning the Delta-based UVMS as a viable solution for complex underwater manipulation tasks. Furthermore, this study provides a compar-ative analysis of the proposed Delta-based UVMS and conventional serial-arm systems, offering valuable design insights and performance benchmarks to inform future develop-ment and optimization of underwater manipulation technologies.

Abstract: Unmanned underwater vehicles (UUVS) capable of agile, high-speed maneuvering in complex environments require propulsion systems that can dynamically modulate three-dimensional forces. The California sea lion (Zalophus californianus) provides an exceptional biological model, using its foreflippers to achieve rapid turns and powerful propulsion. However, the specific kinematic mechanisms that govern instantaneous force generation from its powerful foreflippers remain poorly quantified. This study experimentally characterizes the time-varying thrust and lift produced by a bio-robotic sea lion foreflipper to determine how flipper twist, sweep, and phase overlap modulate propulsive forces. A three-degree-of-freedom bio-robotic flipper with a simplified, low-aspect-ratio planform and single compliant hinge was tested in a circulating flow tank, executing parameterized power and paddle strokes in both isolated and combined-phase trials. The time-resolved force data reveal that the propulsive stroke functions as a tunable hybrid system. The power phase acts as a force-vectoring mechanism, where the flipper’s twist angle reorients the resultant vector: thrust is maximized in a broad, robust range peaking near 45°, while lift increases monotonically to 90°. The paddle phase operates as a flow-insensitive, geometrically driven thruster, where twist angle (0° optimal) regulates thrust by altering the presented surface area. In the full stroke, temporal phase overlap governs thrust augmentation, while power-phase twist provides robust steering control. Within the tested inertial flow regime (Re ≈ 10⁴–10⁵), this control map is highly consistent with propulsion dominated by geometric momentum redirection and impulse timing, rather than circulation-based lift. These findings establish a practical, experimentally derived control map linking kinematic inputs to propulsive force vectors, providing a foundation for the design and control of agile, bio-inspired underwater vehicles.

Abstract: The intelligent decision-making systems of Autonomous Underwater Vehicle (AUV) are undergoing a significant transformation, shifting from traditional control theories to data-driven paradigms. Deep learning (DL) serves as the primary driving force behind this evolution; however, its application in complex and unstructured underwater en-vironments continues to present unique challenges. To systematically analyze the de-velopment, current obstacles, and future directions of DL-enhanced AUV deci-sion-making systems, this paper proposes an innovative "four-module" decomposition framework, which are information processing module, information understanding module, information judgment module and output module. This framework enables a structured review of the progression of deep learning technologies across each stage of the AUV decision-making information flow. To further bridge the gap between theo-retical advancements and practical implementation, we introduce a task complexity–environment uncertainty four-quadrant analytical matrix, offering strategic guidance for selecting appropriate DL architectures across diverse operational scenarios. Addi-tionally, this work identifies key challenges in the field as well as anticipates future developments to solve these challenges.This paper aims to provide researchers and engineers with a comprehensive and strategic overview to support the design and op-timization of next-generation AUV decision-making architectures.

Abstract: Sargassum seaweed beaching events in the Northern Brazilian coast pose environ-mental and economic challenges. Understanding these occurrences is essential for preparing effective management strategies. This study systematically reviews scien-tific articles — screening 2,821 records and assessing 17 full texts — to identify gaps in research and practice, focusing on the impacts, management, and potential uses of pelagic Sargassum biomass. The review identified significant gaps in existing infra-structure and public policy to manage future seaweed influxes effectively. Although innovative approaches—such as the use of Sargassum biomass in sustainable con-struction materials — have been reported as potential strategies, their implementa-tion remains incipient. However, further development of local processing facilities and regulatory frameworks is crucial to reduce logistical challenges, support local economies, and minimize environmental impacts. This study underscores the urgent need for integrated strategies combining infrastructure investments, technological innovation, and policy reforms to address the socio-environmental challenges posed by Sargassum and harness its potential as a valuable resource.

Abstract: Offshore wind farms (OWFs) represent an increasingly important and strategically growing renewable energy source. However, their environmental impacts, particularly noise emissions, require further systematic study. Estimating the operational source level (SL) of a single turbine is challenging, and implementing open-source propagation models to predict sound pressure levels (SPL) at vulnerable locations can be tedious. In this study, we integrate a state-of-the-art turbine operational SL prediction algorithm with open-source propagation models in a Jupyter Notebook to streamline cumulative SPL estimation for OWFs. We also incorporate species-specific audiograms and weighting functions to assess the potential biological impacts of received noise levels. The developed tool is applied to four planned OWFs, two in the Canary region and two in the Belgian and German North Seas, under conservative assumptions. Results indicate that at 10 m/s wind speed single turbine’s operational SL reaches 143 dB re 1 µPa in the one-third octave band centered at 160 Hz. Propagation varies notably with bathymetric and seabed character-istics, with maximum SPLs of 112 dB re 1 µPa at 160 Hz within OWFs (exceeding heavy marine traffic noise levels from generic ambient-noise curves), decreasing in some cases to 50 dB re 1 µPa at ~100 km. Weighted SPL against audiograms analyses show that within OWFs, Phocid Carnivores in Water (PCW) and Low-Frequency (LF) cetacean hearing groups are likely to be affected, while outside the farms, only LF groups are impacted.

Abstract: Offshore wind energy is a key enabler of the global net-zero transition. As nearshore fixed-bottom projects reach maturity, floating offshore wind turbines (FOWTs) are becoming the next major focus for large scale deployment. To accelerate this development and reduce construction costs, it is essential to optimize mooring systems through a systematic and performance driven framework. This study focuses on the mooring optimization of the Taiwan-developed DeltaFloat semi-submersible platform supporting a 15 MW turbine at a 70 m water depth offshore Hsinchu, Taiwan. A full chain catenary mooring system was designed based on site specific metocean conditions. The proposed framework integrates ANSYS AQWA and Orcina OrcaFlex simulations with sensitivity analyses and performance-based Fitness metrics including offset, inclination, and line tension to identify key parameters governing mooring behavior. Additionally, an analysis of variance (ANOVA) was conducted to quantitatively evaluate the statistical significance of each design parameter. Results indicate that mooring line length is the most influential factor affecting system performance, followed by line angle and diameter. Optimizing these parameters significantly improves platform stability and reduces tension loads without excessive material use. Building on the optimized symmetric configuration, an asymmetric mooring concept with unequal line lengths is proposed. The asymmetric layout achieves performance comparable to traditional 3×1 and 3×2 systems under extreme environmental conditions while demonstrating potential reductions in material use and overall cost. Nevertheless, the unbalanced load distribution highlights the need for multi scenario validation and fatigue assessment to ensure long-term reliability. Overall, the study establishes a comprehensive and sensitivity-based optimization framework for floating wind mooring systems. The findings provide a balanced and practical reference for the cost-efficient design of floating offshore wind farms in the Taiwan Strait and other shallow-water regions.

Abstract: This study presents an optimal bearing arrangement for the propulsion shafting system of ships equipped with multiple strut bearings, ensuring both structural stability and cost-effectiveness under shallow-draft conditions where the propeller must remain fully submerged. To this end, the shafting flexibility, alignment characteristics, and whirling vibration responses were analyzed for various bearing arrangements. The analysis results show that removing the stern tube bearing and supporting the shaft using only the Y-type and I-type strut bearings, with the bearing span adjusted so that the L/d ratio remains within 15 to 18, minimizes the reaction influence number, shaft bending moments, and variations in bearing loads. At this configuration, the first natural frequency corresponding to the propeller blade order is also more than 30 percent higher than the service speed, thereby avoiding resonance caused by transverse vibration. Accordingly, this study confirms that adjusting the layout of strut bearings can simultaneously enhance both the structural reliability and dynamic stability of the propulsion shafting system.