To improve the noise reduction accuracy of reciprocating friction vibration signals of piston ring friction pairs in marine diesel engines, this paper proposes a collaborative noise reduction method that integrates complementary ensemble empirical mode decomposition (CEEMD) and an adaptive correlation coefficient screening mechanism. Simulated vibration signals were obtained using the BRUKER UMT friction and wear testing machine to construct an experimental dataset. The original signals were subjected to multi-scale decomposition using CEEMD, and effective intrinsic modal components were screened using an adaptive correlation coefficient threshold. The dominant noise component was removed to achieve signal reconstruction. MATLAB software was applied to implement the noise reduction processing. Three types of indicators—signal-to-noise ratio (SNR), normalized cross-correlation coefficient (NCC), and mean square error (MSE)—were used for quantitative evaluation. Multi-scale permutation entropy (MPE) theory was also innovatively introduced to verify the dynamic characteristics of the denoised signal. The experimental results show that the CEEMD adaptive correlation coefficient screening method has significantly improved noise reduction performance compared to other methods. The correlation coefficients between the multi-scale permutation entropy image of the stripped noise signal and the overall laboratory noise signal image are all above 0.8, thus proving the accuracy of effective signal denoising.

Economic globalization has driven the development of China’s manufacturing industry. The rise of major clean energy projects such as offshore wind power has increased the demand for maritime transportation of super-large structures. In view of the problems of poor universality, cumbersome procedures, and high cost faced by the current lashing tools for super-heavy marine modules such as offshore wind power jackets during sea transport, this paper designs a new gantry-type lashing tooling and systematically evaluates its strength and deformation through finite element analysis. The results show that when transporting a typical wind power jacket module, the maximum stress and deformation of the tooling are 236.62 MPa and 2.15 mm, respectively; when transporting an offshore pile module, the values are 110.85 MPa and 1.80 mm, respectively. Both are below the allowable stress of Q355B steel (273.08 MPa). The tooling has reliable strength, strong versatility, and high reusability. It can significantly shorten the lashing preparation cycle for major components such as wind power jackets, reduce the comprehensive transportation cost, and provide a feasible solution for cost reduction and efficiency improvement in the maritime transport of major components within the offshore wind power industry chain.

The unsteady forces generated when a pump-jet propulsor operates behind a submarine hull are a major excitation source for hull vibration and radiated noise. Accurate prediction of these forces is therefore central to the design of low-noise propulsors. This study presents a numerical framework that couples the prediction of tonal forces via unsteady Reynolds-averaged Navier-Stokes (URANS) equations with the estimation of broadband forces using large eddy simulation (LES). The framework is applied to a model-scale pump-jet installed behind the SUBOFF hull. Numerical simulations characterize the unsteady forces on the rotor and stator blades, yielding their respective tonal and broadband force spectra. The results indicate that the tonal force and moment fluctuations occur predominantly at the first and the second blade passing frequency (BPF), while the broadband force and moment spectra exhibit a distinct hump around the first BPF.

To investigate the distribution and characteristics of slamming loads on a self-propelled jack-up wind turbine installation vessel (WTIV) during transit and preloading conditions, a three-dimensional hydrodynamic numerical tank model was established based on Computational Fluid Dynamics (CFD). The generation mechanism, time-history curves, and spatial distribution of slamming loads under operational sea states and two typical air gap conditions were obtained and analyzed. The results show that under transit (free-sailing) conditions, the peak slamming load increases with wave height and wave steepness, primarily depending on the water-entry velocity at the slamming point and the vessel's hull flare. During preloading operations, a trapped air cushion beneath the hull is significantly compressed and struggles to escape, leading to higher slamming loads at smaller air gaps. In the same region, slamming loads under beam seas are 6% to 14% higher than those under head seas, while also inducing a lateral horizontal load of approximately 300 t. The characteristics of slamming pressure obtained in this study provide critical references for the structural safety of similar vessels and safe operations during preloading conditions.

Self-propelled cutter suction dredgers feature large open slots at the bow and stern for equipment installation, giving them a hull form that is distinctly different from conventional merchant ships. Current loads constitute a major environmental force during their operation. This paper investigates the current load characteristics resulting from these large slots via computational fluid dynamics (CFD) simulations. Two typical hull configurations—the positioning-bow type and the excavation bow type—are examined. Simulations are performed on a scaled model using the SST k-ω turbulence model to analyze the variation in current loads under flow incidence angles ranging from 0° to 180°. The results show that the large open slots create pronounced low velocity zones and vortices behind the hull, significantly increasing the current load coefficients. For instance, at a 180° flow angle, the longitudinal current load coefficient of the excavation-bow type is 122% higher than that of the positioning-bow type. The transverse current load coefficient peaks at a 90° flow angle, exceeding the values given in the OCIMF charts by 18% and 13% for the two hull types, respectively. This study reveals the relationship between hull configuration and flow field characteristics, providing theoretical support for the design of large self-propelled cutter suction dredgers.

To meet the lightweight design requirements of ship composite structures, this paper proposes a multi-objective optimization method for composite laminate layup. The method integrates the NSGA-II algorithm with the micromechanical Voigt-Reuss model and classical lamination theory. Furthermore, a novel tiered constraint strategy, tailored to the loading characteristics of ship structures, is introduced for the first time in the industry, successfully achieving the multi-objective (dual-objective) optimization of laminate layups. Taking a 40-layer carbon-fiber laminate as an example, the optimized design achieves a 14.6% increase in stiffness and a 98% satisfaction rate of manufacturing constraints compared to conventional methods. Finite-element verification under clamped boundary conditions shows a 32% reduction in maximum stress and a 12% increase in the first-order natural frequency. The application of this method to a high-speed composite catamaran demonstrates that the optimized hull-girder design leads to a 10% reduction in deflection and a 15.6% decrease in the fiber stress utilization factor in longitudinal strength calculations. This study provides a valuable reference for advancing ply-optimization design techniques for ship composite structures.

Ship operational data are crucial for assessing vessel performance, predicting energy efficiency, and enabling predictive maintenance, thereby facilitating safe, efficient, and intelligent operations in the maritime industry. However, the effective utilization of such data is often hindered by poor data quality, high uncertainty, and complex processing workflows. To address these challenges, this paper proposes a robust framework for analyzing ship operational data. The framework enhances data usability by optimizing the procedures for data processing and analysis. Specifically, it incorporates a practical method for identifying steady-state operating conditions, establishes rational data filtering strategies, and applies internationally standardized methods for correcting environmental influences. The proposed framework is validated using real operational data from a container ship. Results demonstrate that the processed data can clearly reveal the vessel's long-term performance trends, providing a reliable basis for predictive maintenance decisions. This study offers a practical and effective solution for improving the quality and usability of ship operational data, thereby supporting the advancement of big-data applications towards smart shipping.

This paper investigates the multi-agent formation control problem for underactuated unmanned surface vehicles (USVs) and proposes a distributed control strategy based on partial differential equations (PDE), integrated with an improved artificial potential field (APF) method for obstacle avoidance. A leader-follower formation framework is first established, where the desired positions and tracking velocities of follower vessels are derived. Subsequently, a PDE-based formation control law is designed to ensure stability in multi-USV cooperative motion. The APF approach is enhanced by introducing tangential force components and angle-adaptive coefficients to optimize obstacle avoidance trajectories. The proposed algorithm is validated through simulations using ArduPilot-SITL, ROS, and QGroundControl, demonstrating its effectiveness in formation maintenance, formation switching, and obstacle avoidance. Experimental results show that the method achieves rapid convergence of formation errors while effectively avoiding static obstacles, exhibiting strong robustness and practical applicability.

To address the challenges of path planning for unmanned surface vessels (USVs) in complex environments and the relatively low efficiency of existing algorithms, this paper proposes a novel path planning method that integrates the artificial potential field (APF) approach with the rapidly-exploring random tree star (RRT*) algorithm—referred to as the bidirectional APF-RRT algorithm. The proposed method first introduces a goal-biased strategy, guiding newly generated nodes to expand preferentially toward the target direction. Additionally, a bidirectional search mechanism is adopted to drive two random trees toward each other, thereby accelerating the convergence speed of the algorithm. During node expansion, the attractive force from the artificial potential field guides the expansion toward the target, while the repulsive force enables effective obstacle avoidance. Finally, simulation experiments are conducted on the MATLAB platform to compare the proposed algorithm with traditional RRT* and APF-RRT* algorithms. Experimental results demonstrate that the bidirectional APF-RRT* algorithm outperforms the others in terms of the number of path nodes, path length, and planning efficiency across multiple typical scenarios, indicating superior planning performance and environmental adaptability.

During the 14th Five-Year Plan period, driven by multiple positive factors including a restart of the market cycle and a recovery in external demand, the global offshore engineering equipment market steadily recovered. As international energy prices bottomed out and rebounded, the product structure shifted significantly: floating production equipment became the market focus, offshore wind power orders emerged as a new growth driver, and prices for offshore support vessels continue to rise under capacity constraints. Looking ahead to the 15th Five-Year Plan period, fossil energy is expected to regain prominence as the global energy landscape undergoes profound adjustments. Non-market factors, such as great-power competition and geopolitics, alongside supply-demand fundamentals, will continue to influence energy prices. Consequently, demand for offshore oil and gas equipment orders remains robust, while long-term potential in offshore wind power, other marine renewables, and innovative marine structures continues to hold promise. This paper reviews the recovery and evolution of the global offshore market during the 14th Five-Year Plan period, analyzes the underlying shifts in supply and demand dynamics, and discusses the sector’s development path for the 15th Five-Year Plan period in the context of the ongoing global energy transition, to provide insights for the industry’s high-quality development.

In 2025, the global new shipbuilding market maintained its recent positive momentum, characterized by full orderbooks and sustained high prices, successfully concluding the 14th Five-Year Plan period (2021-2025). China's shipbuilding industry continued to lead global growth, with all major indicators reaching historic highs and further consolidating its position as the world leader. Looking ahead to 2026, operating at a market peak demands heightened caution. Potential risks such as geopolitical competition, demand adjustments, and financial volatility require vigilant attention. Crucially, it is essential to analyze whether the underlying supportive factors will fade, shift, or strengthen—especially regarding the sustainability of shipping demand, the scale of vessel scrapping, and the absorption of new tonnage capacity. These issues represent the core uncertainties and primary sources of divergence in market trend judgments. This paper reviews the development of the global new shipbuilding market in 2025, analyzes the key variables that will influence the market in 2026, forecasts future trends, and provides insights to the industry for its stable development.

To accurately evaluate the energy-saving performance of a pre-swirl duct (PSD) and reveal its underlying mechanisms, this study takes an 8,800 TEU container ship as the research subject. Numerical simulations of ship model resistance, propeller open-water performance, and self-propulsion performance were performed using the Reynolds-averaged Navier-Stokes (RANS) method. The numerical method was validated against towing tank test results. Based on this, the primary energy-saving mechanisms were systematically revealed by analyzing the effects of the PSD on the wake field, propeller performance, and wake kinetic energy. At the design speed, the predicted energy-saving rates are 2.78% (CFD) and 2.74% (EFD). Under off-design conditions, the average rates are 2.86% (CFD) and 2.72% (EFD), showing good agreement between predictions and experiments. The PSD generates a pre-swirl flow via its guide fins, which optimizes the propeller inflow, improves blade performance, and suppresses transverse flow in the wake. The accurate numerical method and the systematic analysis of energy-saving mechanisms presented in this study provide a foundation for future optimization of PSDs.

In the current era of major maritime strategies, the development of grand ocean science programs is becoming an important pathway for the advancement of ocean science. The international community has accumulated considerable experience in implementing such programs, but they face challenges such as insufficient support from high-tech equipment, inadequate research funding, and slow progress in international cooperation. Supported by policies for building a strong maritime country and advancing deep-sea science and technology, China has made certain progress in ocean science research. However, in the future, it will face challenges arising from extreme environments, integrated long-term three-dimensional scientific expeditions, and system integration. Therefore, it is essential to focus on the "four poles" of scientific research—extreme macroscopic, extreme microscopic, extreme environments, and extreme interdisciplinary integration—develop novel ocean technologies and domains, strengthen independent innovation and high-level international cooperation, and use high-tech research equipment as a driver to support future large-scale science programs in key areas.

To investigate the internal sound field of an enclosed cabin equipped with intake and exhaust ducts, numerical acoustic simulations were conducted using the acoustic module of the finite element software LMS Virtual Lab. The study focused on acoustic performance indicators such as the insertion loss of the intake and exhaust mufflers and examined the influence of the intake muffler on the cabin's sound field. The simulation results indicate that the pressure losses of the intake and exhaust mufflers are 19 kPa and 72 kPa, respectively, both meeting the design requirements. Within the frequency range of 20 Hz to 20 kHz, the insertion loss of both mufflers generally complies with the standard, though certain frequency bands still require further optimization. Specifically, the overall noise reduction effect of the intake muffler is slightly lower than that of the exhaust muffler, while the exhaust muffler’s noise attenuation performance in the high-frequency band needs improvement. From the cabin perspective, installing mufflers in the intake duct effectively reduces mid- and high-frequency noise inside the cabin. Additionally, accumulated water in the cabin smooths the sound spectrum and reduces noise, with this effect gradually stabilizing as water depth increases. This study provides valuable insights for optimizing the acoustic design of ship cabins.

To investigate the advantages of the toroidal propeller in hydrodynamic performance and the characteristics of its blade surface pressure distribution, this study first examined the configuration parameters of the toroidal propeller. A parametric modeling approach was applied to the entire propeller, leading to the development of a first-generation toroidal propeller model. Subsequently, based on the STAR-CCM+ software, the open-water performance and pressure distribution of the propeller were computed using the Detached Eddy Simulation (DES) turbulence model. A second-generation toroidal propeller was then developed by adjusting the pitch distribution, which optimized the surface pressure distribution. The research indicates that the configuration design of the toroidal propeller requires the introduction of new parameters. The open-water performance of the toroidal propeller follows a trend similar to that of conventional propellers, but its maximum efficiency is not ideal. The total thrust of the toroidal propeller is considerable; however, the selection of the airfoil and parameters may be unreasonable, leading to pressure loss in both the pressure and suction sides of the front blade and consequently degrading the surface pressure distribution to some extent. Adjusting the pitch distributions of the front and rear blades of the toroidal propeller can significantly optimize the pressure distribution on the blade surface.

Subsea pipelines are prone to developing cracks during long-term service, and traditional methods often suffer from low localization accuracy and poor stability in complex noisy environments. This study investigates defect localization based on an improved cross-correlation time delay estimation method for acoustic emission (AE) signals, which is significant for identifying and localizing sudden AE events under challenging conditions. AE detection technology, as a dynamic, real-time, and non-destructive evaluation method, captures transient elastic waves generated by internal structural changes due to stress or environmental variations, enabling early warning of potential damage and accurate health monitoring of structures. Experimental results demonstrate that the improved cross-correlation time delay method effectively enhances the localization accuracy for AE sources, achieving an average localization error of 0.0133 m and a relative error of 2.67%, which sufficiently meets practical requirements. The findings indicate that this method possesses high practical value for damage detection and localization analysis in complex structures.

As a lift-based energy-saving device, sails are increasingly deployed on modern ships to reduce fuel consumption and carbon dioxide emissions. This study investigates the performance of a NACA airfoil sail installed on a bulk carrier and identifies suitable areas for sail placement. Computational Fluid Dynamics (CFD) simulations were employed to analyze the flow fields around both the sail and the ship. The simulation results show good agreement with Experimental Fluid Dynamics (EFD) data. A comparison between the onboard sail and a freestanding sail reveals that the hull-induced airflow disturbance alters the lift characteristics of the sail. Furthermore, by analyzing the wind speed distribution above the deck under different wind directions, areas with higher wind speeds were identified, determining a "high-performance zone" more suitable for sail layout. This study provides valuable guidance for developing sail arrangement strategies in practical engineering applications.

To facilitate the rational development of engine-propeller integrated control curves and improve the loading response and rapid starting of vessels equipped with a Combined Diesel And Diesel (CODAD) system, mathematical models for the diesel engine, gearbox, shafting, and propeller were established. By analyzing shortcomings of the original emergency loading strategy, an optimized strategy was proposed that prioritizes increasing the rotational speed before adjusting the rate of pitch change. Dynamic simulation results of the CODAD system demonstrate that the optimized strategy ensures that the engine power remains within the overload limit while significantly accelerates the response to engine commands and vessel starting. Compared with three representative strategies, the speed stabilization time under optimized strategy is reduced by 76.6 s, 37.6 s, and 23.8 s, respectively, and the command loading time is shortened by 78.3 s, 35.4 s, and 24.7 s, correspondingly. The simulations also reveal the power variation pattern during emergency loading of large vessels: the main engine power initially increases, then decreases, and finally stabilizes as the vessel's speed steadies. This study provides valuable insights for formulating overload protection strategies and optimizing engine-propeller matching design.

The longitudinal coaming of the liquefied natural gas (LNG) carrier’s cargo tank dome is typically subjected to significant longitudinal loads during operation, leading to stress concentration and potential failure at the toe of the end bracket. To address this issue, a shape optimization study was conducted on the end bracket structure. The optimization process sequentially employed orthogonal experimental design, intuitive analysis, comprehensive experimental design, and a GA-BP-GA (Genetic Algorithm-Back Propagation-Genetic Algorithm) hybrid method for stepwise refinement. The results demonstrate that through shape optimization, the maximum stress of the bracket was reduced by 22.9% compared to the original design. The influence of various design variables on the maximum stress decreases in the order of horizontal arm length ( L), toe height ( h), and arc radius ( r). The introduction of dimensionless parameters C_L and C _r reveals that C_L exerts a greater influence on the maximum stress than C_r. A lower maximum stress is observed when the stress concentration is located at the arc edge. Furthermore, the optimal structural dimensions, which yield a lower maximum stress located at the arc edge, correspond to C_L values ranging from 1.15 to 1.25 and C_r values ranging from 1.1 to 1.3. The optimization design process, methodology, and related conclusions presented in this study can provide valuable references for the design of ship bracket structures.

Green and environmental sustainability are perpetual themes in the shipping industry. Driven by the "Dual Carbon" policy and emerging technologies, new energy vessels and green ships have become an irreversible trend. This paper begins by employing the Strengths-Weakness-Opportunities-Threats (SWOT) analysis to review the development trends of domestic green shipping and lithium-battery powered ships. Subsequently, taking the coastal Yangtze River Delta region as a case study, it systematically analyzes the strengths, weaknesses, opportunities, and threats associated with developing the lithium-battery powered ship industry in this area. The study reveals that, influenced by resources, policies, and environmental factors, the coastal Yangtze River Delta region possesses significant advantages for developing this industry. However, it also faces challenges such as inadequate infrastructure, competitive pressures, and technological risks. In response to these issues, this paper proposes targeted optimization strategies to provide insights for the long-term and sustainable development of the lithium-battery powered ship industry.

This paper addresses the control problem of uncertain systems subject to external disturbances, unknown nonlinearities, and input saturation constraints in ship heading control. A nonlinear regulation control algorithm is designed that integrates adaptive neural networks with dynamic surface control (DSC) technology. The algorithm employs a radial basis function (RBF) neural network to approximate external disturbances and unknown nonlinear functions, while the integration of DSC technology effectively reduces computational complexity. A nonlinear function featuring error-dependent gain characteristics is incorporated into the control law design. This adaptive nonlinear control approach effectively eliminates potential singularity issues, while an auxiliary system is designed to compensate for the effects of input saturation constraints. Using Lyapunov stability theory, the uniform ultimate boundedness of all closed-loop signals is rigorously proven. The proposed algorithm is validated through MATLAB simulations of ship heading tracking control under input saturation constraints. Comparative experimental results demonstrate the superior performance and advantages of the proposed method. The findings provide both theoretical foundations and practical references for related fields, demonstrating significant application value in ship engineering practice.

This study investigates the hydrodynamic response of polar transport ships under ice-propeller-rudder multi-body interactions in brash ice channels. The study develops a numerical ice tank and a discrete element model for brash ice using a coupled Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) integrated with overset grid technology. The research analyzes the self-propulsion characteristics of ships navigating in brash ice channels. The reliability of the Discrete Element Method (DEM) is validated through quantitative comparisons between numerical results and experimental data for ice-induced resistance. The analysis examines the influence of propeller rotational speed on the hydrodynamic performance of the propeller-rudder system under different loading conditions, considering both ice-free and ice-covered environments. Results indicate that the propeller rotational speed required to achieve the self-propulsion point at scantling draft condition is higher than that required at design draft condition. Furthermore, the study compares the force characteristics of the propeller-rudder system in both time and frequency domains, contrasting environments with and without brash ice. These findings provide valuable insights for predicting ice loads and ensuring navigational safety of ships in ice-covered waters.

The Moving Particle Semi-implicit (MPS) method is a meshless method based on the Lagrangian perspective. It effectively avoids mesh distortion when simulating problems with large free-surface deformations, such as water entry and exit of structures, numerical wave generation, and dam breaks. Additionally, its free surface detection algorithm is straightforward and ensures accurate interface tracking, showing broad application prospects. To date, research on numerical wave generation using the MPS method has primarily focused on wave-structure interactions, with relatively limited validation analysis dedicated to the wave generation process itself. To address this gap, this study establishes a two-dimensional numerical wave tank model based on the MPS method, incorporating an improved particle shifting scheme and stabilization operators. Regular waves were generated using a piston-type wavemaker and numerically absorbed in a damping zone. Multiple sets of regular waves with different parameters were simulated to analyze the influence of damping coefficients on the results. Furthermore, the model was validated against experimental motion data of a floating box in waves. The results demonstrate that the proposed model can accurately simulate regular waves with various parameters. The wave amplitude error is positively correlated with the reflected wave energy, and selecting appropriate damping coefficients can effectively minimize the influence of reflected waves on the numerical results. Moreover, the simulated motion time history of the floating box agrees well with the experimental data, confirming the feasibility of the model for solving wave-structure interaction problems.

A Coal Tar Pitch (CTP) tanker is a specialized chemical tanker developed from conventional petroleum asphalt tankers. This vessel type undergoes significant modifications to meet enhanced damage stability requirements. In recent years, the widespread application of dual-fuel systems, particularly methanol, has presented significant challenges for damage stability design in such vessels. Taking an 8000 DWT petroleum asphalt tanker as a case study, this study analyzes its tank subdivision arrangements, loading characteristics, and damage stability performance. The study compares design requirements and damage stability criteria between petroleum and coal tar pitch asphalt tankers, and analyzes the impact of deck-mounted methanol fuel tanks on damage stability. Optimization measures including tank subdivision redesign, loading pattern adjustments, and flooding point reconfiguration are implemented to enhance vessel performance. These modifications ensure that the converted vessel complies with damage stability criteria when converting to a coal tar pitch asphalt tanker configuration.

As the global shipping industry accelerates its transition toward low-carbon, digital, and intelligent development, emerging technologies including artificial intelligence (AI), the internet of things (IoT), big data, and automatic control systems are profoundly transforming the shipbuilding industry. This transformation has positioned maritime autonomous surface ship (MASS) at the strategic forefront of international maritime technology competition. Although China has launched numerous R & D projects in autonomous ships and has made substantial progresses, challenges persist, such as unclear market demand and inadequate technological drivers. This study selects green-fueled container ships as the primary research focus, addressing their intelligence and autonomy requirements in actual shipping environments. The study identifies four core development directions and constructs a hierarchical logical architecture for autonomous ships. Subsequently, it investigates the application of autonomous technologies in the maritime domain. Furthermore, the paper analyzes evolution trends of autonomous ships and identifies shortcomings in key technological breakthroughs and institutional frameworks. Based on the analysis, targeted development pathways are proposed to facilitate R & D advancement, practical implementation, and systematic capability-building for autonomous ships in China, providing strategic guidance for the industry’s development.

With advancements in computer technology and numerical simulation methods for hydrodynamics, performance-driven ship optimization has become an important approach for improving the hydrodynamic performance of ships. Ship optimization comprises several key components, including parametric modeling, hydrodynamic performance evaluation, surrogate model construction, and optimization algorithms. This paper reviews developments in ship optimization technologies, summarizes typical methods and their characteristics associated with each component, and identifies challenges including high-dimensional design spaces, multidisciplinary coupling, and practical engineering applications. On this basis, the paper focuses on the development and application of OPTShip-SJTU, a ship optimization software independently developed by the Computational Marine Hydrodynamics Laboratory (CMHL) at Shanghai Jiao Tong University. The software integrates parametric modeling, in-house hydrodynamic performance solvers, multiple surrogate models, and optimization algorithms. This enables a fully automated process from geometric modification to performance evaluation and optimization, establishing a ship optimization platform with proprietary intellectual property rights. Through validation via numerous engineering applications and academic studies on various ship types, OPTShip-SJTU has demonstrated effectiveness and reliability in comprehensive ship performance evaluation and optimization. The software provides an advanced tool and solution for China's shipbuilding industry.

Annual maintenance is an important measure in ship maintenance reform and is crucial for enhancing ship operational availability and maintaining technical conditions. Currently, the schedule control of annual maintenance projects still relies on traditional management models, which often result in lengthy maintenance cycles. To improve the traditional methods, this paper introduces coefficients for uncertain factors, process location, time elasticity, and resource utilization, based on the Critical Chain Technology (CCT) theory. A calculation method for the project buffer is established, and a schedule control model for annual maintenance projects based on CCT is constructed. The applicability of the model is verified through a case study of an annual maintenance project. The results show that the application of Critical Chain Technology effectively enhances project management, control, and execution capabilities, while significantly shortening the annual maintenance cycle.

In the alignment calculation process for propulsion shafting systems equipped with shaft-mounted generators, the unbalanced magnetic pull (UMP) is often overlooked, leading to deviations and reduced accuracy in the alignment results. To investigate the influence of the UMP of a shaft-mounted generator on the dynamic alignment of a propulsion shafting system, a finite element model for shafting alignment was established based on a simplified modeling principle. Dynamic alignment analyses were conducted under various conditions: without a shaft-mounted generator, with a shaft-mounted generator but without considering UMP, and with a shaft-mounted generator while considering different UMP values. A comparative analysis of the calculation results was performed. The results demonstrate that the UMP of the shaft-mounted generator affects the shaft deflection, stress, and the load on adjacent bearings. The research findings provide valuable guidance and reference for the accurate alignment calculation of propulsion shafting systems equipped with shaft-mounted generators.

On ships using methanol as fuel, the vent mast of the methanol tank is a potential release point for methanol vapor, which may be released during navigation or bunkering operations. As a toxic substance, excessive inhalation of methanol can harm crew health. Classification rules require a minimum distance of 15 meters between the methanol vent mast and non-watertight openings in accommodation areas. Consequently, the vent mast is typically positioned away from accommodation areas during the design phase. However, some smaller vessels may be unable to meet this requirement due to layout constraints. Furthermore, the extent of the influence of methanol vapor released from the vent mast is affected by factors and conditions such as the release rate, ambient wind speed and direction, and the aerodynamic profile of the surrounding structure. Relying solely on the 15-meter spacing requirement is insufficient to determine whether a release from the vent mast during actual operation could lead to personnel exposure to toxic concentrations. Therefore, this study employs computational fluid dynamics (CFD) simulations to analyze gas dispersion from a methanol vent mast located at the bow of a methanol-fueled ship under different wind speeds. The research aims to investigate the extent of the methanol toxic zone and to verify that the hazardous area generated by the vent mast does not endanger crew health.

Accidents involving chemical tankers are often highly hazardous. The operational status of cargo tanks and loading/unloading systems is critical to the safety of these ships during service. This paper reviews 62 accident cases related to the cargo tanks and loading/unloading systems of chemical tankers occurring between 2003 and 2021. A statistical analysis of the accident causes is conducted from four perspectives: accident type, deadweight tonnage of the involved ship, ship age, and the ship's operational status at the time of the accident. This analysis aims to summarize the conditions under which these accidents occur. Thirty-one typical cases are selected for a more detailed examination. The potential risks leading to these accidents are categorized into human factors and non-human factors. Finally, targeted control measures are proposed, including suggestions for chemical tanker rules and standards, as well as recommendations for the management and operational requirements of shipping companies. These measures are intended to provide technical support for enhancing the safety of chemical tanker transportation.