International Journal of Naval Architecture and Ocean Engineering最新文献_第6页

Enhancing passage efficiency in cabin spaces: A layout optimization approach for submarine integrating intelligent algorithms and passage capacity 提高舱室空间通行效率：一种集成智能算法和通行能力的潜艇布局优化方法

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 Epub Date: 2025-07-03 DOI: 10.1016/j.ijnaoe.2025.100672

Jing Chen , Mingjiu Yu , Weilan An , Qiuyuan Zhu , Hao Fan

Confined spaces in submarines pose a serious barrier to crew operations and mobility. To enhance internal passage efficiency in submarines, this study proposed the Passage Efficiency Driven Layout Optimization Strategy (PEDLOS), which considers passage capacity as a key factor. Congestion risks were identified using a passage simulation of the current simulated layout. After building a network of passage nodes, the shortest path matrix was computed by Dijkstra's algorithm, which also involved passage coefficients for revision. An optimal layout scheme that balanced circulation passage efficiency, adjacency, and circulation requirements was subsequently produced by multi-objective optimization based on genetic algorithm. The PEDLOS could provide an innovative approach to enhance internal passage efficiency and overcome the limitations of current layout methods that unduly rely on expert experience and overlook passage capacity drivers. The study provides theoretical and practical support for confined space design by incorporation of passage capacity as a major optimization indicator.

潜艇的密闭空间严重阻碍了艇员的操作和机动性。为了提高潜艇内部通道效率，本文提出了以通道容量为关键因素的通道效率驱动布局优化策略（PEDLOS）。使用当前模拟布局的通道模拟来识别拥堵风险。在建立通道节点网络后，使用Dijkstra算法计算最短路径矩阵，其中还涉及到通道系数进行修正。通过基于遗传算法的多目标优化，得到了平衡流通通道效率、邻接性和流通需求的最优布局方案。PEDLOS可以提供一种创新的方法来提高内部通道效率，克服当前布局方法过度依赖专家经验和忽视通道容量驱动因素的局限性。研究结果为以通道通行能力为主要优化指标的密闭空间设计提供了理论和实践支持。

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引用次数: 0

Experimental study on ultimate bearing capacity of pre-cracked ship hull stiffened panel under low-cycle fatigue and accumulative plasticity coupling 低周疲劳-累积塑性耦合作用下预裂船体加筋板极限承载力试验研究

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 Epub Date: 2025-08-22 DOI: 10.1016/j.ijnaoe.2025.100688

Xu Geng , Dong Qin

Ships navigating in complex sea conditions typically do not experience catastrophic failure due to a single extreme load; rather, the primary structural components such as stiffened panels of the hull undergo plastic deformation under repeated cyclic loading and may develop cracks under low-cycle fatigue. This leads to a decrease in ultimate bearing capacity and eventual structural failure due to insufficient ultimate strength, resulting in hull buckling. Currently, methods for evaluating the ultimate strength of ship hull stiffened panels under cyclic extreme loading considering the coupling effects of accumulative plasticity and low-cycle fatigue are not well-developed. Therefore, there is a need for research into computational methods for assessing the ultimate strength of stiffened panels structures considering the coupling effects of these two factors. This paper investigates the ultimate load-bearing capacity of pre-cracked stiffened panels under the combined effects of accumulative plasticity and low-cycle fatigue. During the experiments, hysteresis curves of stress-strain relationships and relevant fracture parameters for stiffened panels were obtained under various crack positions and load conditions. Ultimately, the study provides the ultimate load-bearing capacity of stiffened panels considering low-cycle fatigue and accumulative plasticity interactions, offering a foundational calculation basis for designing vessels under severe sea conditions.

在复杂海况下航行的船舶通常不会因单一极端载荷而发生灾难性故障；相反，船体加筋板等主要结构部件在反复循环载荷下发生塑性变形，并可能在低周疲劳下产生裂纹。这将导致极限承载能力下降，最终由于极限强度不足而导致结构破坏，从而导致船体屈曲。目前，考虑累积塑性和低周疲劳耦合效应的船体加筋板极限强度评估方法尚不成熟。因此，有必要研究考虑这两个因素耦合作用的加筋板结构极限强度计算方法。研究了累积塑性和低周疲劳共同作用下预裂加筋板的极限承载能力。实验中，得到了加筋板在不同裂纹位置和荷载条件下的应力-应变关系的滞回曲线及相关断裂参数。最终得到考虑低周疲劳和累积塑性相互作用的加筋板的极限承载能力，为恶劣海况下船舶设计提供基础计算依据。

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引用次数: 0

Numerical analysis of water management and reactant distribution in PEM fuel cells with a convergent 5-channel serpentine flow field for emission-free ships 无排放船舶5通道蛇形流场PEM燃料电池水管理及反应物分布数值分析

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 Epub Date: 2025-02-13 DOI: 10.1016/j.ijnaoe.2025.100649

Rashed Kaiser , Chi-Yeong Ahn , So-Yeon Lee , Yun-Ho Kim , Jong-Chun Park

Polymer Electrolyte Membrane Fuel Cells (PEMFCs) represent a promising energy solution for the marine industry, facilitating a sustainable transition from fossil fuels to emission-free alternatives. Despite their high power density and efficiency, water management is an issue. The serpentine flow channel (SFC) design is known for its efficient reactant distribution and enhanced water removal due to high-pressure drops when certain design conditions are met. Regardless these channels exhibit drawbacks such as increased flow resistance due to extended lengths and sharp bends, alongside non-uniform reactant distribution near the channels. This study develops a multiphase three-dimensional model to simulate the transport of mass, species and water within a PEMFC equipped with a five-channel SFC. The simulation results are validated through experiments and compared with two novel convergent 5-channel serpentines. The newly proposed convergent five-channel SFCs demonstrated improved performance at high current densities, notably in power density, pressure drop, water distribution, and removal.

聚合物电解质膜燃料电池（pemfc）代表了海洋工业一种有前途的能源解决方案，促进了从化石燃料到零排放替代品的可持续过渡。尽管它们的功率密度和效率很高，但水管理是一个问题。蛇形流道（SFC）设计以其高效的反应物分布和在满足一定设计条件时由于高压降而增强的除水能力而闻名。然而，这些通道也存在一些缺点，如由于长度延长和急转弯而增加的流动阻力，以及通道附近的反应物分布不均匀。本研究建立了一个多相三维模型来模拟装有五通道SFC的PEMFC内的质量、物种和水的输运，并通过实验验证了模拟结果，并与两种新型收敛的五通道蛇形体进行了比较。新提出的会聚五通道sfc在高电流密度下表现出更好的性能，特别是在功率密度、压降、水分布和去除方面。

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引用次数: 0

Identification of maneuvering models for wind-assisted ships with large rudders using virtual captive tests 基于虚拟约束试验的大舵风助船舶操纵模型辨识

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 Epub Date: 2025-06-02 DOI: 10.1016/j.ijnaoe.2025.100664

Martin Alexandersson , Wengang Mao , Jonas W. Ringsberg , Martin Kjellberg

Ships with wind-assisted propulsion systems (WAPS) are often equipped with large rudders to compensate for WAPS-induced drifting forces. The WAPS also significantly affects the effectiveness of mathematical models used to describe the ship’s maneuvering characteristics. In this study, a modular maneuvering model is proposed to enhance the original MMG model, with the aim of producing accurate maneuvering simulations for ships with WAPS. Methods of virtual captive tests (VCT) are proposed to recreate the forces acting on WAPS ships during free-running model tests (FRMT) in motor mode, identifying all the parameters in the modular model. The hydrodynamic damping coefficients within the model are determined through linear regression of the VCT data. The added masses are then determined from pure yaw and pure sway simulations using a fully nonlinear potential flow (FNPF) panel method. Two ships designed for WAPS, wPCC and Optiwise, are used to validate the proposed method based on the inverse dynamics of their experimental model tests. The wPCC is equipped with a semi-empirical rudder that has previously shown to work well for this twin-rudder ship. The Optiwise single rudder is modeled with a new quadratic version of the MMG rudder model, proposed in this paper. Inverse dynamics analysis, together with state VCTs, is concluded to be an efficient way to analyze the models, and the maneuvering model can be efficiently identified when the correct VCTs are used in the proposed method. However, the inverse dynamics analysis also revealed potential errors in the wPCC VCT data due to false assumptions about wave generation and roll motion. The Optiwise test case, where these assumptions should be more valid, showed much better agreement with the FRMT inverse dynamics.

采用风助推进系统（WAPS）的船舶通常配备大型方向舵以补偿风助推进系统引起的漂移力。WAPS也显著影响用于描述船舶机动特性的数学模型的有效性。本文提出了一种模块化的机动模型，对原有的MMG模型进行了改进，目的是对具有WAPS的舰船进行精确的机动仿真。提出了一种虚拟自保试验（VCT）方法，用于模拟机动模式下自由运行模型试验（FRMT）中作用在WAPS船舶上的力，识别模块化模型中的所有参数。通过对VCT数据的线性回归，确定了模型内的水动力阻尼系数。然后利用全非线性势流（FNPF）面板法从纯偏航和纯摇摆模拟中确定附加质量。以wPCC和Optiwise两艘WAPS船舶为例，通过模型试验的逆动力学验证了所提方法的有效性。wPCC配备了半经验舵，该舵先前已被证明可以很好地用于这种双舵船。本文提出了一种新的二次型MMG舵模型，对优选单舵进行了建模。结果表明，逆动力学分析和状态vct是一种有效的模型分析方法，当使用正确的vct时，可以有效地识别出机动模型。然而，逆动力学分析也揭示了由于对波浪产生和横摇运动的错误假设，wPCC VCT数据可能存在误差。在Optiwise测试用例中，这些假设应该更有效，与FRMT逆动力学表现出更好的一致性。

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引用次数: 0

RANS analysis of the self-propulsion performance for a twin-screw ship 双螺杆船舶自推进性能的RANS分析

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 Epub Date: 2025-07-13 DOI: 10.1016/j.ijnaoe.2025.100674

Je-In Kim , Bu-Geun Paik , Jong-Woo Ahn , Il-Ryong Park

This study presents a comprehensive estimation of full-scale self-propulsion performance for a high-speed, twin-screw, single-skeg surface vessel using Reynolds-averaged Navier–Stokes (RANS)-based computational fluid dynamics (CFD). Resistance, propeller open-water characteristics, and self-propulsion behavior were analyzed by incorporating recent benchmark data on surface roughness—identified as a critical factor in full-scale CFD analysis. The numerical predictions, including key self-propulsion parameters, were validated against full-scale performance data extrapolated from model tests conducted at KRISO. Additionally, ship speeds were estimated by simulating surge motion induced by thrust from specified propeller RPMs under wave conditions, replicating sea trial environments. Finally, ship speeds corresponding to the prescribed RPMs were compared across CFD simulations, model tests, and actual sea trial results.

本研究利用基于reynolds -average Navier-Stokes （RANS）的计算流体动力学（CFD）技术，对一艘高速双螺杆单桅水面舰艇的全尺寸自推进性能进行了综合评估。阻力、螺旋桨开放水域特性和自推进行为通过结合最近的表面粗糙度基准数据进行分析，表面粗糙度被认为是全面CFD分析的关键因素。数值预测，包括关键的自推进参数，根据从KRISO进行的模型试验推断的全尺寸性能数据进行了验证。此外，通过模拟波浪条件下由特定螺旋桨转速引起的推力引起的浪涌运动来估计船速，模拟海上试验环境。最后，通过CFD模拟、模型试验和实际海试结果比较了规定rpm对应的船速。

引用次数: 0

Estimation of ship operational performance degradation using deep-learning-based fuel oil consumption prediction models 基于深度学习的燃油消耗预测模型的船舶使用性能退化估计

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 Epub Date: 2025-05-29 DOI: 10.1016/j.ijnaoe.2025.100666

Donghyun Park , Jae-Yoon Jung , Beom Jin Park

This paper proposes a novel method for estimating ship operational performance degradation (SOPD) using a fuel oil consumption (FOC) prediction model based on deep neural networks with shortcut connections. The model leverages operational and environmental data from a crude oil tanker over a 21-month period to predict FOC and assess SOPD. A cumulative anchoring effect is introduced as a new feature of the FOC prediction model, capturing the impact of biofouling caused by prolonged anchoring in warm waters. In this study, SOPD is considered the additional fuel rate required for a journey leg due to degradation, which is estimated by comparing predicted FOC with and without the cumulative anchoring effect. The SOPD estimation is illustrated according to increasing journey legs based on the FOC prediction models. The proposed SOPD estimation method provides valuable insights for shipping companies to optimize operational schedules and improve fuel efficiency.

提出了一种基于快速连接深度神经网络的船舶燃油消耗预测模型，用于船舶使用性能退化（SOPD）估计。该模型利用一艘原油油轮在21个月期间的运行和环境数据来预测FOC和评估SOPD。作为FOC预测模型的新特征，引入了累积锚定效应，捕捉了在温暖水域长时间锚定引起的生物污染的影响。在本研究中，SOPD被认为是由于退化导致的行程段所需的额外燃油率，通过比较有和没有累积锚定效应的预测FOC来估计。在FOC预测模型的基础上，给出了基于增加行程的SOPD估计。提出的SOPD估计方法为航运公司优化运营计划和提高燃油效率提供了有价值的见解。

引用次数: 0

Machine learning-based optimal value calculation for welding variables in AR training 基于机器学习的AR训练中焊接变量最优值计算

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 Epub Date: 2025-02-23 DOI: 10.1016/j.ijnaoe.2025.100652

Chang Sub Song , Jong-Ho Nam

Currently, the shipbuilding industry is experiencing a surge in orders due to the rising demand for eco-friendly ships, necessitating the optimal use of available resources for production. However, the production workforce has not fully recovered to the level required to meet these increased orders following large-scale industry restructuring. In particular, there is a shortage of highly skilled welders, and concerns are growing about the transfer of expertise due to an aging workforce and a lack of younger workers. Shipbuilders worldwide face similar challenges and are exploring various methods to transfer the tacit knowledge of skilled welders to less experienced workers, which has introduced unforeseen challenges. In this study, we develop a machine learning algorithm that suggests the optimal values of key welding variables for an AR-based welding training system designed to assist less skilled workers. We collected welding data from highly skilled workers using the FCAW (Flux-Cored Arc Welding) technique, which is commonly employed in the shipbuilding process. The welding variables that represent tacit knowledge were identified and trained using the Extra Trees Regressor model. Subsequently, a welding AR training system was implemented, allowing the trained model to guide users on the optimal values for welding variables. Finally, the effectiveness of this system in training welders was verified at a shipyard technical training center.

目前，由于对环保船舶的需求不断增加，造船业的订单量急剧增加，因此必须充分利用现有资源进行生产。然而，在大规模行业重组之后，生产劳动力还没有完全恢复到满足这些增加的订单所需的水平。特别是，高技能焊工短缺，而且由于劳动力老龄化和年轻工人缺乏，人们越来越担心专业知识的转移。世界各地的造船商都面临着类似的挑战，他们正在探索各种方法，将熟练焊工的隐性知识传授给经验不足的工人，这带来了意想不到的挑战。在本研究中，我们开发了一种机器学习算法，该算法为基于ar的焊接培训系统提供关键焊接变量的最佳值，旨在帮助技能较低的工人。我们收集了使用FCAW（药芯弧焊）技术的高技能工人的焊接数据，这种技术通常用于造船过程。使用额外树回归模型对代表隐性知识的焊接变量进行识别和训练。随后，实现了焊接AR训练系统，训练后的模型可以指导用户选择焊接变量的最优值。最后，以某船厂技术培训中心为例，验证了该系统在焊工培训中的有效性。

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引用次数: 0

Adaptive event-triggered anti-windup control for dynamic positioning of turret-moored vessels with nonconvex input constraint and uncertainties 具有非凸输入约束和不确定性的炮塔系泊船舶动态定位自适应事件触发反卷绕控制

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 Epub Date: 2025-10-11 DOI: 10.1016/j.ijnaoe.2025.100694

Bingyao Tan , Yulong Tuo , Yuanhui Wang , Zhouhua Peng , Shasha Wang

This paper proposes an adaptive event-triggered anti-windup dynamic positioning (DP) control method for a turret-moored vessel subject to the uncertainties and nonconvex control input constraint. Firstly, by introducing a nonconvex constraint operator, the designed control input is mapped to the actual control input vector with the maximum amplitude constraint in the same direction, thereby ensuring that the actual control input remains within the nonconvex constraint set. Secondly, the uncertainties are ingeniously separated into an unavailable single parameter and available state-related items. The unavailable single parameter is estimated by an adaptive law online. Then, an adaptive nonconvex constraint anti-windup DP controller is proposed based on the single parameter adaptive law and the nonconvex constraint operator. Furthermore, we integrate an adaptive event-triggered mechanism into the DP controller to decrease its execution frequency. The adaptive event-triggered mechanism can effectively balance the control performance and control signal update frequency. Finally, the effectiveness of the proposed methods is validated through simulations.

针对具有不确定性和非凸控制输入约束的炮塔系泊船舶，提出了一种自适应事件触发反卷绕动态定位控制方法。首先，通过引入非凸约束算子，将设计的控制输入映射到具有最大振幅约束的实际控制输入向量上，从而保证实际控制输入保持在非凸约束集内。其次，将不确定性巧妙地分离为不可用的单个参数和可用的状态相关项。通过自适应律在线估计不可用的单个参数。然后，基于单参数自适应律和非凸约束算子，提出了一种自适应非凸约束抗卷绕DP控制器。此外，我们将自适应事件触发机制集成到DP控制器中，以降低其执行频率。自适应事件触发机制可以有效地平衡控制性能和控制信号更新频率。最后，通过仿真验证了所提方法的有效性。

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引用次数: 0

Design optimization of Savonius hydrokinetic turbine with aid of an artificial neural network model 基于人工神经网络模型的萨沃纽斯水轮机设计优化

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 Epub Date: 2025-09-30 DOI: 10.1016/j.ijnaoe.2025.100693

Mafira Ayu Ramdhani, Senthil Kumar Natarajan, Il Hyoung Cho

The Savonius hydrokinetic turbine (SHT), a vertical-axis turbine, efficiently extracts energy from low-speed water currents in rivers, canals, and marine environments. Optimizing the tip speed ratio (TSR), gap ratio (GR), and immersion ratio (

Z / D

) enhances its power extraction efficiency. Traditionally, optimization relies on computationally intensive CFD simulations, which are time-consuming. To address this, a machine learning-based approach, specifically an Artificial Neural Network (ANN) model is employed, reducing reliance on extensive CFD simulations while maintaining accuracy. The ANN model was trained using CFD simulations performed in StarCCM+ and then used to predict power coefficients for various design configurations. The CFD simulations are validated against experimental results reported in the literature. The optimal parameters, tip speed ratio (0.7808), gap ratio (−0.0498), and immersion ratio (1.0661) yielded the highest power coefficient (0.2179). This study demonstrates that machine learning accurately predicts turbine performance, reducing reliance on extensive CFD simulations, making turbine optimization more efficient.

Savonius水动力涡轮机（SHT）是一种垂直轴涡轮机，可以有效地从河流、运河和海洋环境中的低速水流中提取能量。通过对叶尖速比（TSR）、间隙比（GR）和浸泡比（Z/D）的优化，提高了抽油效率。传统上，优化依赖于计算密集型的CFD模拟，这非常耗时。为了解决这个问题，采用了基于机器学习的方法，特别是人工神经网络（ANN）模型，减少了对大量CFD模拟的依赖，同时保持了准确性。通过在StarCCM+中进行CFD模拟来训练人工神经网络模型，然后用于预测各种设计配置的功率系数。CFD模拟与文献报道的实验结果进行了对比验证。在叶尖速比（0.7808）、间隙比（−0.0498）和浸没比（1.0661）的优化参数下，功率系数最高，为0.2179。该研究表明，机器学习可以准确预测涡轮机性能，减少对大量CFD模拟的依赖，从而提高涡轮机优化效率。

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引用次数: 0

Integrated analysis of ice-induced vibration characteristics of monopile offshore wind turbines 单桩海上风力发电机组冰激振动特性综合分析

IF 3.9 3区工程技术 Q2 ENGINEERING, MARINE

International Journal of Naval Architecture and Ocean Engineering

Pub Date : 2025-01-01 Epub Date: 2025-08-26 DOI: 10.1016/j.ijnaoe.2025.100687

Yijie Zhao , Zhenju Chuang , Yan Qu , Haoyang Yin , Zhenze Yang , Lulin Xia

The rapid development of offshore wind power in cold regions drives turbine deployment into deep-sea areas, yet ice-induced loads pose severe challenges to structural safety. This study aims to accurately predict dynamic responses of offshore wind turbines under ice-wind coupling, proposing a Discrete Element Method-Wind Turbine Integrated Analysis (DEM-WTIA) approach. This method synchronously simulates ice fragmentation processes and aero-structural dynamic responses by constructing an integrated model with rotor and control systems. Findings reveal: The model precisely captures transient energy dissipation during ice crushing and characterizes high-low frequency coupling effects with nonlinear superposition of ice-wind-wave loads; Tower-top displacement sensitivity to ice loads significantly exceeds foundation displacement; Under no-wind/cut-in wind speeds (3–5 m/s), ice dominates tower vibration, while aerodynamic damping suppresses ice-induced vibrations at rated/cut-out speeds; Spectral analysis shows dominant displacement frequency shifts from 0.27 Hz (near OWT fundamental frequency) to 0.24 Hz as wind increases; Sensitivity analysis indicates ice thickness sensitivity index (35.6) far exceeds ice velocity (7.2) in parked mode; Anti-ice design identifies 70° cone angle as optimal for monopile foundations. This research provides critical theoretical support and a novel simulation method for anti-ice design of offshore wind structures in cold seas, offering key technical guidance for far-sea wind farm planning.

寒冷地区海上风力发电的快速发展推动了涡轮机向深海部署，但冰荷载对结构安全提出了严峻挑战。为了准确预测冰-风耦合作用下海上风力发电机组的动力响应，提出了一种离散元法-风力发电机组集成分析（DEM-WTIA）方法。该方法通过建立旋翼和控制系统的集成模型，同步模拟冰破碎过程和气动结构动力响应。研究结果表明：该模型准确地捕捉了冰破碎过程中的瞬态能量耗散，表征了冰-风波载荷非线性叠加的高低频耦合效应；塔顶位移对冰荷载的敏感性显著超过基础位移；在无风/切断风速（3 ~ 5 m/s）条件下，冰主导了塔的振动，而在额定/切断风速下，气动阻尼抑制了冰引起的振动；频谱分析表明，随着风力的增加，主导位移频率从0.27 Hz（接近wt基频）转变为0.24 Hz；敏感性分析表明，在停车模式下，冰厚敏感性指数（35.6）远远超过冰速敏感性指数（7.2）；抗冰设计确定70°锥角为最佳的单桩基础。该研究为寒冷海域海上风结构的防冰设计提供了重要的理论支持和新的模拟方法，为远海风电场规划提供了关键的技术指导。

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引用次数: 0