International Journal of Naval Architecture and Ocean Engineering最新文献

Anti-swing overhead crane control algorithm based on multi-body dynamics using reinforcement learning 基于多体动力学强化学习的桥式起重机防摆控制算法

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-12-09 DOI: 10.1016/j.ijnaoe.2025.100719

Jun-Gi Jang, Seung-Ho Ham

Excessive cargo sway during crane operations in the current shipbuilding industry is a major problem that causes safety accidents and work delays. Therefore, the development of stable crane control technology is essential. In this study, a crane control algorithm that simultaneously achieves accurate movement to target positions and sway minimization was developed using reinforcement learning. In dynamics modeling, the Discrete Euler-Lagrange Equation was applied to significantly reduce the computational complexity of existing methods, and the Proximal Policy Optimization (PPO) method was used for control policy learning. A three-dimensional virtual environment was constructed to perform learning under various travel distances and operating conditions, and the performance of the developed algorithm was compared and verified against the traditional trapezoidal velocity profile. Experimental results showed that the proposed method exhibited significant improvements in position control precision and sway suppression performance compared to existing methods. The results of this study are expected to contribute to the implementation of automated crane control systems in actual shipyard environments.

在目前的造船业中，起重机作业中货物晃动过大是造成安全事故和工作延误的主要问题。因此，开发稳定的起重机控制技术是必不可少的。本研究采用强化学习的方法，开发了一种同时实现精确运动到目标位置和摆动最小化的起重机控制算法。在动力学建模中，采用离散欧拉-拉格朗日方程（Discrete Euler-Lagrange Equation）大大降低了现有方法的计算复杂度，并采用近端策略优化（Proximal Policy Optimization， PPO）方法进行控制策略学习。构建了三维虚拟环境，在不同的行驶距离和工况下进行学习，并与传统的梯形速度剖面进行了性能比较和验证。实验结果表明，与现有方法相比，该方法在位置控制精度和抑制摆动性能方面有显著提高。本研究的结果可望有助于在实际船厂环境中实施自动起重机控制系统。

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引用次数: 0

Numerical investigation on the turning motion of a near-surface self-propelled submarine 近水面自航潜艇转向运动的数值研究

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-12-08 DOI: 10.1016/j.ijnaoe.2025.100718

Haipeng Guo , Yi Liu , Junyu Ge , Lin Du , Guangnian Li

The present work performs a numerical study on the turning motion of a near surface self-propelled submarine. The turbulent flow around the submarine is solved by using the Reynolds-Averaged Navier-Stokes (RANS) method. The interaction between the submarine and the free surface is captured by using the Volume of Fluid (VOF) method. The motion of submarine and rudder is achieved through overset grid technology, while the rotating propeller is modeled by using the body force model. Numerical simulations of the turning circle test are performed for those conditions, and the variation law of the turning motion parameters at different immersion depths is revealed. Based on the obtained flow field details, including free surface waveform, shedding vortices, and velocity distribution, the interaction between the self-propelled submarine and the free surface and its relationship with the submarine turning characteristics are explored.

本文对近水面自航潜艇的转弯运动进行了数值研究。采用reynolds - average Navier-Stokes （RANS）方法求解潜艇周围的湍流。利用流体体积法（VOF）捕捉潜艇与自由表面的相互作用。潜艇和方向舵的运动通过反置网格技术实现，螺旋桨的运动采用体力模型建模。在这些条件下进行了回转试验的数值模拟，揭示了不同浸泡深度下回转运动参数的变化规律。基于所获得的流场细节，包括自由面波形、脱落涡和速度分布，探讨了自主潜艇与自由面相互作用及其与潜艇转向特性的关系。

引用次数: 0

A study on the avoidance timing of autonomous surface ships through machine learning 基于机器学习的自主水面舰艇避碰时机研究

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-12-06 DOI: 10.1016/j.ijnaoe.2025.100717

Mu-Yeong Seo , Kwang-Jun Paik , Won-Jun Yoo , Sanghyun Kim , Soo-Yeon Kwon

The technologies for autonomous navigation are steadily being developed for the International Maritime Organization level 4 fully unmanned ships. Autonomous surface ships must comply with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs), which requires them to perceive and judge their situation and generate a collision avoidance path for safe navigation. While COLREGs are designed to prevent collisions between individual vessels, they do not provide clear criteria for when to initiate collision avoidance, which is why maritime collisions continue to occur. This study analyzed the collision avoidance timing of navigators using Automatic Identification System (AIS) data and applied the findings to the collision avoidance system of autonomous ships. A machine learning approach was employed using a decision tree model to classify collision avoidance timing rules, which were then integrated into the collision avoidance system of autonomous surface ships. By analyzing collision avoidance timing through a machine learning model, a system was developed to determine avoidance points in various scenarios. The effectiveness of the proposed system was validated through simulations conducted in diverse and complex environments.

国际海事组织（imo） 4级完全无人驾驶船舶的自主导航技术正在稳步发展。自主水面舰艇必须遵守《国际海上避碰规则公约》（COLREGs），该公约要求它们感知和判断自己的情况，并生成避碰路径，以确保安全航行。虽然COLREGs旨在防止个别船只之间的碰撞，但它们并没有为何时启动避碰提供明确的标准，这就是海上碰撞继续发生的原因。本文利用自动识别系统（AIS）数据对导航员避碰时机进行了分析，并将研究结果应用于自主船舶避碰系统。采用机器学习方法，采用决策树模型对避碰时间规则进行分类，并将其集成到自主水面舰艇避碰系统中。通过机器学习模型对避碰时机进行分析，开发了一套确定不同场景下避碰点的系统。通过在多种复杂环境下的仿真，验证了该系统的有效性。

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引用次数: 0

Multi-USV cooperative path planning via FSM-based distance field and enhanced hippopotamus optimization 基于fsm的距离场和增强河马优化的多usv协同路径规划

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-12-04 DOI: 10.1016/j.ijnaoe.2025.100714

Youjia Han , Huibin Wang

With single Unmanned Surface Vehicle (USV) no longer meeting growing mission demands, cooperative multi-USV systems have become essential, particularly in obstacle-rich waters where task allocation deviates and path planning struggles to balance distance and safety. To address these challenges, an integrated framework combining a constrained-distance-based Hungarian assignment algorithm and an improved Hippopotamus Optimization algorithm (CDH-IHO) is developed to achieve simultaneous target assignment and path planning (STAPP). The CDH module achieves globally optimal assignment by exploiting a constrained distance matrix constructed through the Fast Sweeping Method (FSM), while the IHO module introduces a Cubic chaotic map and a mutation operator to enhance convergence and avoid local optima. Distance, turning angle, safety, and penalty terms are jointly considered for collision-free path generation. Simulations in five scenarios verify global optimality in assignment and superior performance in path length, smoothness, and safety. CDH-IHO provides an efficient and robust solution for STAPP.

随着单个无人水面车辆（USV）不再满足日益增长的任务需求，协作式多USV系统变得至关重要，特别是在任务分配偏离和路径规划难以平衡距离和安全性的障碍物丰富的水域。为了解决这些问题，开发了一种基于约束距离的匈牙利分配算法和改进的河马优化算法（CDH-IHO）的集成框架，以实现目标分配和路径规划（STAPP）的同时进行。CDH模块利用快速扫描法（Fast Sweeping Method， FSM）构造的约束距离矩阵实现全局最优分配，IHO模块引入三次混沌映射和突变算子来增强收敛性，避免局部最优。在生成无碰撞路径时，将距离、转弯角度、安全性和处罚条件综合考虑。在五个场景下的仿真验证了分配的全局最优性以及路径长度、平滑性和安全性方面的优越性能。CDH-IHO为STAPP提供了高效、稳健的解决方案。

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引用次数: 0

Line contact induced bending failures of ice sheets during ship-ice interactions 船-冰相互作用中冰原线接触引起的弯曲破坏

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-12-03 DOI: 10.1016/j.ijnaoe.2025.100711

Fan Zhang , Qikai Zhang , Dong Peng , Yudi Wang , Yihe Wang , Qi Qin , Shihong Hu , Gang Wu

Recent field observations from the Xuelong icebreaker indicate that line contact induced bending failures of ice sheets are prevalent during consecutive ice breaking processes. However, the corresponding ice force and breaking length have rarely been studied. Against this backdrop, this study proposes a model with seven independent input parameters to characterize the loading scenario without assuming ice sheet geometric symmetry. The normalized governing equation based on the theory of thin plates on elastic foundations is solved by the finite element (FE) method, and the results are further utilized to train a XGBoost model. The established line contact induced bending failure model is implemented into a non-smooth discrete element method (DEM) framework for ship-ice interaction simulations, and the numerical result for ice resistance of the Xuelong 2 icebreaker in level ice is validated against model test data. This study facilitates a more accurate real-time description of ice-sloping structure interactions.

雪龙号破冰船最近的野外观测表明，在连续的破冰过程中，线接触引起的冰盖弯曲破坏是普遍存在的。然而，对相应的冰力和断裂长度的研究却很少。在此背景下，本研究提出了一个具有7个独立输入参数的模型，在不假设冰盖几何对称的情况下表征加载情景。基于弹性基础薄板理论的归一化控制方程采用有限元法求解，并将求解结果进一步用于训练XGBoost模型。将建立的线接触诱导弯曲破坏模型应用到船冰相互作用的非光滑离散元法（DEM）框架中，通过模型试验数据验证了雪龙2号破冰船在水平冰面上的冰阻数值结果。该研究有助于更准确地实时描述冰坡结构相互作用。

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引用次数: 0

Predicting ship hull flow-field distributions using a soft-constrained ANN model 用软约束人工神经网络模型预测船体流场分布

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-12-02 DOI: 10.1016/j.ijnaoe.2025.100712

Christoforos Lefkiou , Phoevos (Foivos) Koukouvinis , Sotirios Chatzis , Stefanos Xyfolis

Accurate determination of shear and pressure force distributions around a ship's hull is paramount for hydrodynamic optimization tasks, as integrating these fields across the hull's surface provides the total drag force applied on the hull. While Computational Fluid Dynamics (CFD) provides this capability, it is often limited by high computational cost and time-consuming pre-processing, post-processing, and simulation times. The challenge is further amplified during design exploration studies, where simulations are performed across multiple operational conditions. To address these limitations, we propose a soft-constrained Multitask deep neural network, named HydroForceNet, which serves as a surrogate model for CFD simulations on marine vessel hulls. Our proposed architecture can accurately predict pressure and shear distributions on various Wigley-based geometries and calculates the resistance components, using three-dimensional geometric and operational inputs, at a fraction of the computational cost of a traditional CFD evaluation. Finally, to further illustrate its applicability, the proposed artificial neural network is integrated into a genetic algorithm-based optimization task, producing a new hull geometry with a 15.77 % reduction of hydrodynamic resistance compared to a reference hull geometry, after evaluating over 2500 designs within 2 min, while faithfully reproducing the flow field.

准确确定船体周围的剪切力和压力力分布对于流体动力优化任务至关重要，因为将这些场整合到船体表面上可以提供施加在船体上的总阻力。虽然计算流体动力学（CFD）提供了这种能力，但通常受到高计算成本和耗时的预处理、后处理和模拟时间的限制。在设计探索研究期间，在多种操作条件下进行模拟，挑战进一步扩大。为了解决这些限制，我们提出了一个软约束的多任务深度神经网络，名为HydroForceNet，它可以作为船舶船体CFD模拟的替代模型。我们提出的架构可以准确地预测各种基于wigley的几何结构上的压力和剪切分布，并使用三维几何和操作输入计算阻力分量，而计算成本只是传统CFD评估的一小部分。最后，为了进一步说明其适用性，将所提出的人工神经网络集成到基于遗传算法的优化任务中，在2分钟内评估了2500多个设计后，生成了一个新的船体几何形状，与参考船体几何形状相比，水动力阻力降低了15.77%，同时忠实地再现了流场。

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引用次数: 0

Data-driven model for predicting cargo tank pressure of an LNG carrier considering environmental effects 考虑环境影响的LNG运输船货舱压力预测数据驱动模型

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-12-02 DOI: 10.1016/j.ijnaoe.2025.100713

Hyun Soo Kim , Myung-Il Roh

The utilization of natural gas is expanding as part of efforts to reduce greenhouse gas (GHG) emissions. Natural gas is typically liquefied at cryogenic temperatures in order to enhance the efficiency of maritime transport. When these cryogenic cargoes are shipped, BOG (Boil-Off Gas) is generated by the external heat and wave-induced ship motion. Proper management of BOG is critical to maintaining the cargo tank pressure within a safe operational range. In the case of LNG (Liquefied Natural Gas) carriers, BOG is used as fuel for main engines and generator engines, with any surplus being burned in the GCU (Gas Combustion Unit) or reliquefied by a reliquefaction system. Accurate prediction of BOG generation and cargo tank pressure is therefore essential for optimizing reliquefaction system operations and voyage planning. Although various experimental and CFD-based studies have been conducted, it remains challenging to capture the complex, irregular characteristics of real marine environments, particularly the effects of ship motion and sloshing. This study presents a framework for developing a data-driven model that predicts cargo tank pressure in LNG carriers. The data-driven model is based on long-term operation data from a 174K-class LNG carrier, enabling consideration of the combined effects of BOG consumption, reliquefaction performance, and marine environmental conditions on cargo tank pressure. The variables related to cargo tank pressure are derived from ship operation, BOG consumption, and marine environmental conditions. Several regression and machine learning algorithms were compared to identify the most effective predictive model. The model's accuracy was verified by comparing predicted values with actual measurements from an LNG carrier that had been in operation for 2 years, and the results confirmed high predictive accuracy. This approach provides a practical framework for data-driven cargo tank pressure prediction and contributes to improving energy efficiency and reducing GHG emissions in LNG carrier operations.

作为减少温室气体（GHG）排放努力的一部分，天然气的利用正在扩大。为了提高海上运输的效率，天然气通常在低温下液化。当这些低温货物运输时，BOG（沸腾气体）是由外部热量和波浪引起的船舶运动产生的。正确的BOG管理对于将液货舱压力保持在安全运行范围内至关重要。在LNG（液化天然气）运输船的情况下，BOG被用作主机和发电机发动机的燃料，任何剩余的燃料都在GCU（气体燃烧单元）中燃烧或通过再液化系统再液化。因此，准确预测BOG生成和货舱压力对于优化再液化系统操作和航行计划至关重要。尽管已经进行了各种实验和基于cfd的研究，但要捕捉真实海洋环境的复杂、不规则特征，特别是船舶运动和晃动的影响，仍然具有挑战性。本研究提出了一个用于开发数据驱动模型的框架，该模型可以预测LNG运输船的货舱压力。数据驱动模型基于一艘174k级LNG运输船的长期运行数据，考虑了BOG消耗、再液化性能和海洋环境条件对货油舱压力的综合影响。与货舱压力相关的变量来自船舶操作、BOG消耗和海洋环境条件。比较了几种回归和机器学习算法，以确定最有效的预测模型。通过将预测值与一艘运行了2年的LNG运输船的实际测量值进行比较，验证了该模型的准确性，结果证实了预测的准确性。该方法为数据驱动的货舱压力预测提供了实用框架，有助于提高LNG运输船运营中的能源效率和减少温室气体排放。

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引用次数: 0

Numerical and experimental investigation of an Inertial Tilting hybrid wave energy converter for powering small-scale marine systems 小型海洋系统惯性倾斜混合波能转换器的数值与实验研究

IF 2.3 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 DOI: 10.1016/j.ijnaoe.2025.100658

Chongfei Sun , Huaiyu Teng , Xiaoyan Ma , Hailong Chen , Liming Sun , Cun Shao , Fei Cao , Hengxu Liu

The increasing global demand for marine resource exploration, maritime rights protection, and deep-sea engineering applications highlights the need for the diversification of marine engineering equipment and the expansion of its deep-sea capabilities, presenting significant technical and economic value. As the use of small-scale marine engineering equipment in deep-sea environments becomes more prevalent, optimizing energy supply methods for such equipment is critical to ensure their durability and efficiency in complex marine conditions. This paper proposes an Inertial Tilting Electromagnetic-Triboelectric Hybrid Energy Converter (ITHEC), which efficiently harvests energy from ocean waves to power small marine engineering devices. A comprehensive design and optimization framework was developed for this energy converter. This framework was based on theoretical analysis and simulations of structural dynamics and characteristics. Validation experiments were conducted using a custom-built structural characteristics testing platform. The results showed that under horizontal harmonic motion excitation with an amplitude of d = 60 mm and a frequency of f = 1.5Hz, the open-circuit voltages of the triboelectric nanogenerator (TENG) and electromagnetic generator (EMG) reached 60V and 0.23V, respectively, with short-circuit currents of 1.3 μA and 2.2 mA, and peak power densities of 1.18 mW/m² and 0.51 mW/m². When arrayed, the hybrid energy converter can meet the operating current requirements of small marine sensors. This study offers an innovative solution for energy supply challenges in small marine equipment and establishes the practical viability of hybrid power systems for marine energy harvesting.

全球对海洋资源勘探、海洋权益保护和深海工程应用的需求日益增长，凸显了海洋工程设备多样化和深海能力扩展的需求，呈现出重大的技术和经济价值。随着小型海洋工程设备在深海环境中的使用越来越普遍，优化此类设备的能源供应方法对于确保其在复杂海洋条件下的耐久性和效率至关重要。本文提出了一种惯性倾斜电磁-摩擦电混合能量转换器（ITHEC），它可以有效地从海浪中收集能量，为小型海洋工程设备提供动力。建立了该能量转换器的综合设计与优化框架。该框架基于理论分析和结构动力学特性仿真。在定制的结构特性测试平台上进行了验证实验。结果表明，在幅值为d = 60 mm、频率为f = 1.5Hz的水平谐波激励下，摩擦纳米发电机（TENG）和电磁发电机（EMG）的开路电压分别达到60V和0.23V，短路电流分别为1.3 μA和2.2 mA，峰值功率密度分别为1.18 mW/m2和0.51 mW/m2。混合能量转换器阵列后，可以满足小型船用传感器的工作电流要求。该研究为小型船舶设备的能源供应挑战提供了一种创新的解决方案，并建立了用于海洋能源收集的混合动力系统的实际可行性。

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引用次数: 0

Numerical simulations and large-scale experimental research into air-lifting system for deep-sea mining 深海采矿气举系统数值模拟与大型试验研究

IF 2.3 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 DOI: 10.1016/j.ijnaoe.2025.100656

JianYu Xiao , Zhuang Kang , Jing Leng , Ming Chen , Jun Liu

The deep seabed harbors abundant mineral resources. To achieve the economic viability of deep-sea mining, the efficiency of polymetallic nodule lifting is critical. In this study, we investigate the performance of air-lifting systems, which is a key component of deep-sea mining operations. Through two-phase flow simulations, we establish the relationship between the air-injection velocity and water-lifting velocity and validate the experimental data. We constructed a large-scale air-lifting system in a 20-m-deep water tank to explore the feasibility and energy efficiency of lifting water and nodules under varying air-injection velocities and depths. In detailed energy efficiency calculations, we determined the optimal operational parameters which provide novel insights into the design and optimization of deep-sea mining lifting systems. The experimental data and findings offer valuable references for future system designs that can enhance operational stability and economic feasibility.

深海海底蕴藏着丰富的矿产资源。为了实现深海采矿的经济可行性，多金属结核的提升效率至关重要。在本研究中，我们研究了空气提升系统的性能，这是深海采矿作业的关键组成部分。通过两相流模拟，建立了注气速度与提水速度的关系，并对实验数据进行了验证。我们在20m深的水箱中构建了大型气举系统，探索在不同的注气速度和深度下举升水和结核的可行性和能效。在详细的能源效率计算中，我们确定了最佳操作参数，为深海采矿提升系统的设计和优化提供了新的见解。实验数据和研究结果为今后系统的设计提供了有价值的参考，可以提高系统的运行稳定性和经济可行性。

引用次数: 0

Experiment and modeling of submarine emergency rising motion using free-running model 基于自由运行模型的潜艇应急上升运动实验与建模

IF 2.3 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 DOI: 10.1016/j.ijnaoe.2024.100641

Jooho Lee, Seonhong Kim, Jihwan Shin, Jaemoon Yoon, Jinheong Ahn, Minjae Kim

Development of submarine and its safe operational envelope requires an understanding of motion characteristics including emergency rising motion. In this study, the emergency rising motion is investigated using submarine free-running model equipped with ballast systems. The emergency rising test was conducted according to the initial vehicle speed, yaw rate, depth, ballast water discharge ratio and time interval between bow and stern ballast systems. Experimental results reveal that the maximum pitch angle before surface is affected by initial velocity and the operation conditions of ballast systems. In addition, excessive roll occurs after the surface when the submarine passes through the water surface at a negative pitch angle. Furthermore, the system parameters that comprise the emergency rising model are estimated using the collected test data. The identified model is verified by comparing emergency rising simulation with the free-running model test results.

潜艇及其安全操作包线的发展需要了解包括紧急上升运动在内的运动特性。本文采用装有压载系统的潜艇自由运行模型，研究了潜艇的应急上升运动。根据船舶初始航速、横摆角速度、深度、压载水排放比和船首尾压载系统间隔时间进行应急上升试验。实验结果表明，初始速度和压载系统运行条件对最大俯仰角有一定的影响。此外，当潜艇以负俯仰角通过水面时，水面后会出现过大的横摇。此外，利用收集到的试验数据估计了构成应急上升模型的系统参数。通过应急上升仿真与自由运行模型试验结果的对比，验证了所识别的模型的正确性。

引用次数: 0