Traditional planing craft lines design methods are complex and time-consuming, which hampers the improvement of design efficiency. To address this challenge, this paper proposes an intelligent design approach for planing craft, utilizing neural network models to automate both the design and performance prediction processes. A sectional area prediction model is developed, optimized, and integrated with a database of planing craft. The closest parent craft is selected from the database based on the design parameters, and the hull section is generated with minimal error, ensuring high design accuracy. Additionally, a novel effective power prediction model is introduced, which leverages CFD simulations and experimental testing to create a comprehensive effective power database. Furthermore, an intelligent design system integrating both prediction models is developed. By inputting key design parameters, the system generates the craft's hull section, principal dimensions, and performance forecasts, streamlining the design process and significantly improving efficiency. This automated, neural network-based solution greatly enhances design accuracy and efficiency in planing craft design. This study combined neural networks with parametric databases and CFD data to construct an intelligent design framework, successfully automating the design and performance prediction process of planing craft. This framework transformed the traditional complex and iterative design process into an efficient, automatic and accurate paradigm, significantly saving time while maintaining accuracy, providing a more precise and efficient approach than traditional methods for the design and development of planing craft.

Nearshore wave breaking phenomena, which are experimentally intractable, were investigated in this study to determine the physical mechanisms governing quasi-steady state evolution and three-dimensional (3D) vortex dynamics. Six consecutive solitary waves propagating over a 1:10 slope were simulated. A high-precision numerical wave tank was established to characterize the spatiotemporal evolution of free-surface morphology, flow velocity, and vorticity fields. The numerical model is found to accurately reproduce the complex hydrodynamics of wave-beach interactions. The system reaches a quasi-steady state following the fourth wave, characterized by spatiotemporal periodicity in the run-up and run-down flows. This state arises from a transition in the dominant vortex mechanism: the system shifts from being governed by initial “primary breaking vortices” (positive vorticity) generated by self-breaking to “interaction vortices” (negative vorticity) induced by the shear between run-up and run-down flows. Further 3D analysis reveals that these interaction vortices are stable, high-shear zones extending longitudinally, with laterally distributed paired cellular circulation structures acting as primary channels for energy dissipation and momentum exchange. These findings shed light on the energy transfer and 3D flow structures in wave-beach interactions, offering theoretical insights for tsunami hazard assessments and coastal-protection design techniques.

After successful release from the cabin, the underwater structure continues ascending to the water surface under residual buoyancy. However, its ascent velocity and attitude may affect personnel safety, making it essential to study the ascent dynamics and safe surfacing behavior. This paper conducts experimental research on the underwater release and ascent of submerged structures. Numerical simulations of the ascent motion are performed using computational fluid dynamics (CFD) software STAR-CCM+, and the results are compared with experimental data. The close agreement between simulations and experiments validates the feasibility of this numerical approach. Building on this validated method, the study further investigates the ascent process under varying angles of attack. The results demonstrate that this numerical approach can serve as a reliable reference for analyzing the ascent motion of underwater structures.

Research on the hydrodynamic wakes of submerged bodies is essential for optimizing non-acoustic stealth and enhancing anti-submarine detection capabilities. This review addresses the types, characteristics, experimental and numerical methods, as well as the applications of SAR technology in wake detection. Studies on hydrodynamic wake, dating back to the early 20th century, have focused on the complex fluid structures influenced by environmental factors such as waves, temperature gradients, and water density stratification. Advances in CFD and experimental techniques have improved simulations and observations of these wakes. Hydrodynamic wakes are classified into surface waves (including "V"-shaped wakes and Bernoulli humps), turbulent wakes, and internal wave wakes, each resulting from different physical interactions. Key research methods include water tunnel experiments and numerical simulations, with experiments providing direct observations of wake formation, while simulations offer flexible analysis of complex flow fields. The combination of these methods yields comprehensive insights into wake dynamics. SAR technology has revolutionized wake detection in complex maritime environments by offering all-weather detection, passive modes, and wide-area coverage. However, it faces limitations related to radar parameters, sea conditions, cost, and technical challenges. Future research should focus on integrating numerical simulations, laboratory experiments, and field validation to enhance the detection of weak wakes using deep learning, which would improve generalizability with limited data. This will optimize submerged body designs, reduce costs, and enhance stealth performance.

Estimation and prediction of real-time significant wave height (SWH) is a fundamental requirement for the safety of offshore activities. This study utilizes a spatio-temporal deep neural network model to effectively estimate and predict the SWH by extracting key spatial and temporal features from synthetic X-band radar images.The study considers three deep neural networks: InceptionV3, ResNet and Vision Transformer (ViT) to extract multi-scale spatial features from radar images for SWH estimation. Subsequently, a gated recurrent unit (GRU) is employed on these spatial features to perform the time-series SWH prediction. Irregular waves with sea state ranging from 4 to 6 were considered based on the synthetic radar data. Results indicate that the ResNet model with deep residual structure performs the best in both the estimation and prediction tasks, demonstrating excellent generalization ability and adaptability to complex sea conditions. The ViT model shows outstanding performance in scenarios without out-of-distribution data. While the InceptionV3 model is inferior, it exhibits significant improvement for the SWH prediction when the GRU is incorporated.

Phase-resolved ocean wave models have recently garnered significant attention in wave forecasting, as they capture the phase information of each wave component, enabling the prediction of three-dimensional surface elevation distributions within a defined sea area. However, wave fields input into phase-resolved models often deviate from actual wave fields due to limitations in wave surface measurement and reconstruction processes. Moreover, wave evolution is a complex dynamical process influenced by multiple factors, such as wind, currents, and topography, which are challenging to accurately simulate in phase-resolved wave models. To mitigate the impact of wave field disturbances and enhance prediction performance for strongly nonlinear ocean waves, we propose a coupled approach that integrates observations into wave simulations by combining the pseudospectral Fourier-Legendre method with the ensemble Kalman filter. We first establish and validate an assimilation framework applicable to strongly nonlinear phase-resolved wave simulations. Next, we optimize the assimilation parameters for both two-and threedimensional regular and irregular waves, revealing that optimal parameters for irregular waves can be inferred from those of regular waves. Using these optimal parameters, we analyze the assimilation performance for waves with varying nonlinearity and disturbances. The results demonstrate that the coupled simulation approach delivers accurate surface elevation predictions, with errors consistently decreasing over time, even in highly nonlinear wave scenarios.

Nonlinear model for the long-time evolution of two-dimensional water waves under wind forcing effect and energy dissipation effect is established. The wind forcing terms constitute the Miles' shear flow theory and the Jeffreys' sheltering theory with a wind model criterion to determine when and which model to use. The dissipation terms consist of non-breaking dissipation parts and breaking dissipation parts. A wave-breaking onset criterion based on the ratio of local energy flux velocity to the local crest velocity is used for the determining wave breaking. Numerical evolutions of focusing wave trains solved by the wind wave model are compared with previous works to validate the non-breaking and breaking dissipation terms. Non-breaking focusing wave groups under different wind conditions are resolved and the results are compared with previous experimental studies to validate the wind forcing terms. After the validation, the long-time evolutions of the modulational instability wave trains under wind action and wind forcing conditions are investigated by the wind wave model. The variations of surface profiles, wave energy, and spectrum with the effects of wind forcing and energy dissipation are analyzed.

The collective escape capsule is a crucial emergency lifesaving equipment for underwater vehicles. Enhancing the success rate of underwater release of the capsule is a key approach to improve the self-rescue and escape capability of underwater vehicles. The underwater release of the capsule within the hull under environmental flow is a fluid-structure interaction problem involving large displacements and multiple contact collisions. In this paper, the underwater release model of the capsule is established by the Coupled Eulerian-Lagrangian (CEL) method and the release performance of the capsule is investigated through the simulated release process. Firstly, for the predetermined initial attitude of the capsule, the typical complete release and stuck cases are identified by analyzing the vertical displacement of the capsule under different flow directions, and the cause of being stuck is analyzed. Subsequently, the stuck domain of the capsule is established by considering both the direction of the environmental flow and the size of the hull. For environmental flow of typical directions, the impact of flow velocity and the height of the centre of gravity, the density, and the height-to-diameter ratio of the capsule on the underwater release performance are analyzed. It is found that the impact of the environmental flow velocity on the release performance of the capsule depends on the flow direction. For the capsule, increasing the height of the centre of gravity, decreasing the density, or increasing the height-to-diameter ratio will make the capsule release easier. This work is beneficial for conducting rapid evaluations of the underwater release performance of the capsule and can also provide guidance for the design of the escape capsule.

In nature, there are often numerous phenomena of collective movement, such as geese flying and fish swimming. To explore the advantages of swarm motion, this paper examines swarm motion from the perspective of energy consumption. Focusing initially on the common scenario of ducklings swimming with their mother, two ellipsoids with similar geometry were introduced to simulate the swimming motion and analyze movement resistance. The results show that within a certain distance range, the resistance of the ellipsoid in the rear is significantly reduced compared with the resistance of a single ellipsoid. The resistance reduction effect is related to the spacing of the two ellipsoids, and there is an optimal spacing for resistance reduction at different moving speeds. Subsequently, resistance calculations and energy-saving analyses were conducted for four Unmanned Surface Vessel formations, revealing that formation navigation had a significant energy-saving effect. Additionally, this paper includes an experimental study of a ship formation model, and the calculation results are compared with the experimental results, verifying the reliability of the swarm motion resistance calculation method. Finally, a formula for optimal spacing in ship formations to reduce resistance is proposed, providing a convenient and feasible energy-saving reference for actual ship formation navigation.

In this paper, the ditching performance of a seaplane model on calm water and a uniform water current coupled with wind was numerically investigated. The overset grid technique was applied to treat the large amplitude of the body motions of the seaplane without leading to mesh distortion. The effects of the initial velocity and the initial pitch angle on the slamming loads and motion responses were investigated for the seaplane’s ditching on calm water. A good agreement with the experimental data on the velocity and angle was obtained. Besides ditching on calm water without the water current and wind, three more-complicated conditions were adopted, including the seaplane’s ditching on calm water with wind, a water current without wind, and a water current coupled with wind. The accelerations and impact pressures of the seaplane can be influenced by the wind or current. Water splashing and overwashing could be observed during the water entry process, with water overtopping the seaplane head or nose and flowing over the body surface. It can be concluded that the relative motion between the water and the seaplane model should be carefully controlled to avoid possible damages caused by the occurrence of overwashing.

Resistance serves as a critical performance metric for ships. Swift and accurate resistance prediction can enhance ship design efficiency. Currently, methods for determining ship resistance encompass model tests, estimation techniques, and computational fluid dynamics (CFDs) simulations. There is a need to improve the prediction speed or accuracy of these methods. Machine learning is gradually emerging as a method applied in the field of ship research. This study aims to investigate ship resistance prediction methods utilizing machine learning across various datasets. This study proposes two methods: employing stacking ensemble learning to enhance resistance prediction accuracy with identical ship samples and utilizing various ship resistance prediction models for accurate resistance prediction through transfer learning. Initially focusing on container ships as the research subject, the stacking ensemble learning model outperforms the basic machine learning model, the Holtrop and Mennen method, and the updated Guldhammer and Harvald method based on comparative prediction results. Subsequently, the container ship resistance prediction model achieves precise resistance prediction for bulk carriers. This study offers dependable guidance for applying machine learning in predicting ship hydrodynamic performance.

Recent ship-related energy conservation efforts have directed increasing attention on green technology that has the potential to save energy in the shipping industry while protecting the environment. In particular, ship optimum trim energy-saving technology has several advantages, including facile implementation, convenient operation, and high energy-saving effects. This report proposes a method for predicting the optimum trim of container ships based on machine learning, and the developed approach can quickly determine the optimum trim of any container ship to achieve minimum resistance during operation. First, six container ship models from a trim optimization test database were consulted to extract the characteristic parameters of the container ships, thus providing a basic dataset for model training. Four machine learning models were selected to forecast the resistance of the container ship under different trim conditions. The results indicate that the performance of the random forest prediction model was significantly better than the three other tested models (i.e., backpropagation neural network, decision tree, K-nearest neighbor). Therefore, the random forest prediction model was used as the optimal prediction model for determining the optimum trim of container ships. Specifically, the 4700-TEU and 13500-TEU container ships were evaluated; relative to the experimental data, the prediction accuracy reached 85.71% and 88.89%, respectively. Finally, the developed model was applied to the 4250-TEU container ship operation, and the optimum trim angle was predicted under five sets of conditions; the predicted values were consistent with the experimental values. The container ship optimum trim prediction method based on machine learning described in this paper can predict the optimum trim of any container ship (in a certain state), guide its operation, realize energy-saving effects, reduce emissions, and promote the development of green ship technology.

针对船舶与海洋工程领域螺旋桨敞水动力性能实验教学中学生参与性不强的现状,设计并开发了一套螺旋桨敞水动力性能实验教学装置.选取合适大小水箱在其侧壁开口依次连接竖直观测筒、 流量计、 伺服水泵;观测筒上方依次安装电机、 自航仪和螺旋桨,学生自行操作测量推力和扭矩完成螺旋桨敞水实验教学.改变水温,将频闪灯调至与螺旋桨转速相同频率,观测空泡现象完成螺旋桨空泡实验教学.本装置可完成螺旋桨敞水和空泡教学实验,学生在动手完成实验数据测量和实验现象观测的过程中,增强对知识的理解,提高自主创新和动手实践能力.

Aiming at the attitude control of unmanned underwater vehicle (UUV), a control moment gyros (CMGs) control system is designed based on ARM stm32f407, which owns many advantages such as large output torque and does not depend on fluid motion. Firstly, this paper briefly describes the system attitude control mechanism. Then the hardware design scheme is proposed with detailed design and type selection. Considering the requirements of the control task, the lower computer control program and the upper computer control interface are designed. Finally, the system is tested and verified by experiment. The results show that the designed system can effectively control the speed of execution motors, so as to output the required torque and meet the attitude control demand of UUV.

ObjectivesAiming at the high-precision recovery guidance control requirements of current stern ramp recovery technology, a self-adaptive cascade tracking control method for unmanned surface vessels (USVs) is proposed specifically for stern ramp recovery. MethodsBased on the technical requirements of stern ramp recovery, a motion model of an underactuated USV is established, and the generalized Kalman filter (GKF) algorithm is used to predict the navigation state and recovery position of the mother ship. Introducing the idea of constant bearing guidance combined with the sliding mode variable structure control theory, a stable cascade control system is constructed to solve tracking control problems during the recovery process. ResultsIt is proven that the USV can stably track the target, by analyzing the stability of the system through the Lyapunov theory and cascade theorem. ConclusionsThe simulation results show that the proposed control method gives the USV stable tracking performance and strong robustness against uncertain disturbances.

以V形高速艇为研究对象,在船长固定基础上,改变船宽(3组)、斜升角(3组)、排水量(3组)和静倾角(2组),得到54组不同工况,选择合适缩尺比加工模型,完成船模阻力试验并按照二因次换算法得到实船有效功率,通过线型插值得到以该艇为母型船的阻力图谱.学生自主输入船型参数后通过阻力图谱获取有效功率,输入推力减额、伴流分数、相对旋转效率、传动效率等参数,选定主机功率和额定转速后预估设计航速并完成螺旋桨设计,得到螺旋桨直径、盘面比和螺距比等参数.以VB语言为工具对AutoCAD进行二次开发,完成螺旋桨叶剖面参数表和桨叶轮廓形状图绘制.该基于阻力图谱的船舶快速性教学系统将阻力性能、推进性能、船机桨匹配等知识点有机融合,作为课堂教学的辅助软件,可促进学生对船舶设计知识体系的理解,提升学生的思考能力和创新能力.

"船舶流体力学"是船舶与海洋工程(081901)本科专业的专业基础课程之一.以面向行业需求为抓手、以夯实流体力学基础为根本,结合课堂教学实践,文章对国内已有船舶流体力学教材内容进行分析,在此基础上提炼出"船舶流体力学"教学所需解决的核心问题,并就"船舶流体力学"教材大纲编写提出初步建议.明确了"船舶流体力学"课程的定位,厘清了船舶流体力学与相关课程的关系,有助于提高"船舶流体力学"课程及后续专业核心课程的教学效果.

The drift motion of a wrecked target at sea is caused by the combined effect of wind, wave and current loads on the object. A suitable drift prediction model can accurately calculate the drift trajectory of the wrecked target in the marine environment. The purpose of this paper is to explore the accuracy of different drift prediction models for the calculation of drift trajectories of fishing vessels and to make an evaluation. First, the AP98 leeway model and the drifting dynamics model were introduced, and an improved drift prediction model was proposed based on their characteristics and principles. Then, based on the measured data obtained from the drift experiments of fishing vessels in the South China Sea, the drift parameters of the three drift prediction models were calibrated, thus three drift prediction models for fishing vessels in the South China Sea were established. Finally, the simulated drift trajectories of fishing vessels at sea were calculated using three drift prediction models and compared with the actual drift trajectories. Results showed that the improved drift prediction model has the highest prediction accuracy, followed by the AP98 leeway model, while the drifting dynamics model has the worst accuracy. The results of this paper can be directly applied to the drift prediction of wrecked fishing vessels in the South China Sea region.

"船舶静力学"课程是"船舶与海洋工程(081901)"专业本科教学的基础性专业核心课程.课程目的是培养学生完成船舶在静力载荷或等效静力载荷作用下的浮性与稳性的分析能力,其内容涉及流体静力学、理论力学、微积分、数值方法等多个方面.为了建设新时代"船舶与海洋工程(081901)"专业的课程体系,作者对国内设置船舶与海洋工程类高校课程教材内容进行了对比和聚类分析,并据此确定了"船舶静力学"课程的基本共性内容.这些共性内容主要包括船体几何描述、流体静力学、船舶浮性、船舶稳性、船舶静水力资料、重物的状态改变、自由液面、进水与破舱等八个方面.在上述分析的基础之上编写的课程讲义或教材,有望取得更好的教学效果.

For barges staying in inland waters, hydroelectric power generation using the speed of the water itself can provide part of the electrical energy for ships, which can reduce energy consumption and play an important role in energy conservation and environmental protection. The passive flow velocity acceleration device accelerates the water flow and then impacts the water wheel to generate electricity, which can improve efficiency and has certain economic benefits. This paper uses a combination of numerical simulation and model tests to study the passive acceleration effect of the acceleration device in open water under the premise of a certain size of the water inlet and outlet. First taking the most basic arc-shaped cavity as the research object, and the numerical simulation at different speeds is carried out. The research results are compared with the experimental results to verify the reliability of the numerical simulation. On this basis, three improved line types, concave-convex type, micro-concave type and linear type, were designed, and simulation calculations were completed with numerically verified solutions, and the calculation results and speed cloud graphs were analyzed to draw the conclusion that the linear type has the best effect; Model processing and tank tests were performed on the three improved line types, and the test results were in good agreement with the numerical calculation results, which further verified the reliability of the numerical scheme and the credibility of the research results.