Ocean Engineering最新文献_第3页

Beyond uniform roughness: Ship resistance with spatially non-uniform hull surface conditions 超越均匀粗糙度：空间非均匀船体表面条件下的船舶阻力

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124462

Sang-seok Han , Ho-won Lee , Saishuai Dai , Momchil Terziev

Traditional ship resistance models often assume uniform hull surface roughness, potentially misrepresenting the heterogeneous fouling patterns observed in real-world operations. To address this limitation, we investigate the hydrodynamic impact of spatially non-uniform roughness on a KRISO Container Ship (KCS) hull using Computational Fluid Dynamics (CFD) simulations.

Seven hull surface conditions were investigated, including a smooth baseline and six types of roughness distributions: uniform, linear gradient, non-linear gradient, random, direct-shear, and inverse-shear. All cases were designed to have the same arithmetic mean hull surface roughness, allowing isolation of the effects of spatial roughness distribution. Among the tested configurations, the linear gradient distribution exhibited the most favourable resistance characteristics, whereas the shear-based and random distributions showed relatively minor differences from the uniform case.

Spatial roughness patterns significantly influenced boundary layer growth and wake development. Uniform, random, and shear-based distributions induced thicker boundary layers and delayed wake recovery, whereas the linear gradient case resulted in weaker momentum loss and faster wake recovery.

These findings indicate that even under identical arithmetic mean roughness conditions, the spatial distribution of hull surface roughness can significantly affect resistance characteristics. Explicit modelling of roughness patterns is therefore essential for accurate performance prediction and motivates further experimental validation and integration with propeller-hull interaction and free surface effects.

传统的船舶阻力模型通常假设船体表面粗糙度是均匀的，这可能会误解实际操作中观察到的异质性污垢模式。为了解决这一限制，我们使用计算流体动力学（CFD）模拟研究了空间非均匀粗糙度对KRISO集装箱船（KCS）船体的水动力影响。研究了7种船体表面条件，包括光滑基线和6种粗糙度分布：均匀、线性梯度、非线性梯度、随机、正剪切和反剪切。所有情况都设计为具有相同的算术平均船体表面粗糙度，允许隔离空间粗糙度分布的影响。在试验配置中，线性梯度分布表现出最有利的阻力特性，而基于剪切和随机分布与均匀情况的差异相对较小。空间粗糙度模式对边界层生长和尾流发展有显著影响。均匀、随机和基于剪切的分布导致边界层变厚和尾流恢复延迟，而线性梯度情况导致动量损失更弱和尾流恢复更快。这些结果表明，即使在相同的算术平均粗糙度条件下，船体表面粗糙度的空间分布也会显著影响阻力特性。因此，粗糙度模式的明确建模对于准确的性能预测至关重要，并激励进一步的实验验证和螺旋桨-船体相互作用和自由表面效应的整合。

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引用次数: 0

Survivability strategy for an eagle wave energy converter based on CFD modeling 基于CFD建模的鹰波能量转换器生存性策略

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124604

Shanxun Yang , Songwei Sheng , Xianyuan Yang , Xiaolong Dai , Xinhui Chen

Severe sea states pose significant challenges to the survivability of wave energy converters (WECs). To address collision problems caused by excessive motion of the floating body observed during sea trials of the Eagle WEC, a CFD numerical model based on overset mesh approach was developed to investigate the motion response. The model was systematically validated against 1:30-scale physical experiments under three scenarios, including empty wave tank, floating body only and PTO included. The results demonstrate excellent agreement. Using the full-scale numerical model, the effects of power take-off (PTO) load and ballast on the pitch response of the floating body were investigated. The results indicate that increasing the PTO load effectively suppresses the motion response of the floating body and enhances the operational safety margin of the device; increasing ballast can suppress upward motion but amplifies the downward response, its impact on operational safety is twofold. The coordinated ballast–PTO adjustment strategy was proposed and evaluated under irregular wave conditions. The results show that, during an extreme wave event with a maximum instantaneous wave height of 6.51 m, by increasing ballast while maintaining a high PTO load, the motion envelope can be shifted downward and kept within the operational safety limits.

恶劣的海况对波浪能转换器（WECs）的生存能力提出了重大挑战。为了解决Eagle WEC海上试验中观测到的浮体过度运动导致的碰撞问题，开发了基于过偏移网格方法的CFD数值模型来研究运动响应。通过1:30比例尺的物理实验对模型进行了系统验证，包括空波槽、仅浮体和含PTO三种场景。结果显示了极好的一致性。采用全尺寸数值模型，研究了载力和压载对浮体俯仰响应的影响。结果表明：增大PTO载荷可有效抑制浮体的运动响应，提高装置的运行安全裕度；增加压载可以抑制上升运动，但会放大下降响应，对运行安全的影响是双重的。提出了非规则波条件下的压舱- pto协调调整策略，并对其进行了评价。结果表明，在最大瞬时波高为6.51 m的极端波浪事件中，通过增加压载量同时保持较高的PTO负载，可以将运动包络线向下移动并保持在运行安全范围内。

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引用次数: 0

Convex formulation of the maritime fleet size and mix problem considering battery electric ships 考虑纯电动船舶的海上船队规模和混合问题的凸公式

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124415

Antti Ritari, Jani Romanoff, Kari Tammi

This paper focuses on the problem of determining a minimum-cost fleet of battery electric ships for a given liner shipping operation. The problem is strongly nonlinear and includes integer decision variables, which make it intractable for most real-world instances. The conventional approach in the literature is to formulate a linear approximation by restricting available ship types to a small number of predetermined alternatives. Contrary to the conventional linearization approach, this paper models the nonlinearities directly. We show that the nonlinearities have a hidden convex form uncovered by changes of variables. Computational experiments show that our convex formulation achieves 15.1% lower fleet cost on average and reduces solve time by at least 10 ×  compared to the linear formulation. The solve time advantage is attributed to the elimination of binary variables for ship type selection. Our implementation is available at https://github.com/ajritari/cvxfleet.

本文主要研究在给定的班轮运输条件下，如何确定一个成本最低的纯电动船队。该问题是强非线性的，并且包含整数决策变量，这使得它对于大多数现实世界的实例来说都很棘手。文献中的传统方法是通过将可用的船型限制为少数预先确定的备选方案来制定线性近似。与传统的线性化方法相反，本文直接对非线性进行建模。我们证明了非线性具有一种由变量变化所揭示的隐凸形式。计算实验表明，与线性公式相比，我们的凸公式平均降低了15.1%的车队成本，并将求解时间减少了至少10 × 。求解时间上的优势在于消除了船型选择的二元变量。我们的实现可以在https://github.com/ajritari/cvxfleet上获得。

引用次数: 0

Bi-level multi-objective optimization of configuration and scheduling of offshore wind-solar-storage hybrid power system considering demand response 考虑需求响应的海上风电-太阳能-储能混合动力系统配置与调度的双层多目标优化

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124614

Meng Shao , Yutong Han , Jinwei Sun , Hao Xu , Xiangqi Kong , Huimin Wang , Bingjie Wang , Zhuxiao Shao , Jian Guan , Zezhi Qu

Due to the fluctuation and intermittency of offshore wind and solar power generation, offshore wind-solar-storage hybrid power system (OWSS-HPS) has emerged as a significant field for promoting energy transformation and addressing climate change. For ensuring the economic benefits and reliability of the OWSS-HPS over the entire life cycle, it necessitates a scientific and reasonable capacity planning configuration optimization which takes consideration of the practical operation scheduling. This paper proposes a novel bi-level multi-objective optimization model that couples the capacity configuration and operation scheduling based on the demand response (DR). An improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) with an enhanced elite selection strategy is introduced to generate the Pareto front, and the TOPSIS method is applied to determine the final optimal solution. A coastal industrial area in the South China Sea serves as the case study. The results show that under the DR mechanism with 30% participation, the system achieves optimal performance, comprising 497.31 MW of offshore wind turbines, 488.65 MW of offshore photovoltaics, and 397.67 MW of battery energy storage systems. Under this setup, the LCOE is 0.5581 CNY/kWh, and the LPSP is 1.90%. This study provides theoretical support for the construction of practical OWSS-HPS.

由于海上风电和太阳能发电的波动性和间歇性，海上风能-太阳能-储能混合发电系统（OWSS-HPS）已成为促进能源转型和应对气候变化的重要领域。为保证OWSS-HPS全生命周期的经济效益和可靠性，需要在考虑实际运行调度的基础上进行科学合理的容量规划配置优化。提出了一种基于需求响应的容量配置与运行调度耦合的双层多目标优化模型。引入改进的非支配排序遗传算法II （NSGA-II）和增强的精英选择策略来生成Pareto前沿，并采用TOPSIS方法确定最终最优解。南中国海的一个沿海工业区作为案例研究。结果表明，在30%参与率的DR机制下，系统性能最优，包括497.31 MW海上风电、488.65 MW海上光伏和397.67 MW电池储能系统。在此设置下，LCOE为0.5581元/千瓦时，LPSP为1.90%。本研究为构建实用的OWSS-HPS提供了理论支持。

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引用次数: 0

Prediction of safe water areas under adverse weather conditions for pilot boarding and disembarkation based on PCA and sparse broad learning neural networks 基于PCA和稀疏广义学习神经网络的恶劣天气条件下飞行员登降安全水域预测

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124472

Lizhen Zhu , Wei Li , Jun Ning , Tong Zhang

The safe boarding and disembarking of pilots in adverse weather conditions are typically achieved by maneuvering the vessel to the leeward side. However, the quantification of the safe operational zone for pilot transfer has long remained a critical research gap in the field of maritime pilotage operations. To address the challenge of predicting safe water areas for pilot boarding and disembarkation during leeward maneuvers under adverse sea conditions, this article proposes a prediction model based on Principal Component Analysis (PCA) and a sparsified Broad Learning System (BLS). Firstly, Maneuvering data from multiple sea areas under low-speed, large-rudder-angle conditions are processed using PCA for dimensionality reduction and feature extraction. Subsequently, a sparsification method based on the Iterative Soft Thresholding (IST) algorithm is applied in the feature mapping layer of the model, constructing a nonlinear mapping between ship parameters and the lateral and longitudinal distances to enable prediction of the safe water area. Finally, key influencing factors are identified through Permutation Feature Importance (PFI), and type-specific safety boundaries are derived through linear fitting. Based on comprehensive validation from comparison prediction models, 86 pilot questionnaires, and three full-scale ship trials, the model proves to be highly effective in predicting safe water areas for pilot boarding and disembarkation.

在恶劣的天气条件下，飞行员的安全上下船通常是通过将船只操纵到下风侧来实现的。然而，引航人转移安全操作区域的量化一直是海上引航作业领域的一个重要研究空白。为了解决在不利海况下下风机动中飞行员登船和下船安全水域预测的挑战，本文提出了一种基于主成分分析（PCA）和稀疏广义学习系统（BLS）的预测模型。首先，对多海域低速大舵角机动数据进行主成分分析，进行降维和特征提取；随后，在模型的特征映射层采用基于迭代软阈值（IST）算法的稀疏化方法，构建船舶参数与横向和纵向距离之间的非线性映射，实现对安全水域的预测。最后，通过排列特征重要性（PFI）识别关键影响因素，并通过线性拟合得到特定类型的安全边界。通过对比预测模型、86份引航员问卷和3次全船试验的综合验证，该模型在预测引航员登船和下船安全水域方面具有较高的有效性。

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引用次数: 0

Free-surface dynamics and hydrodynamic characteristics in the buoyancy-driven exit of axisymmetric bodies 轴对称体浮力驱动出口的自由面动力学和水动力特性

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124495

Bülent Güzel , Fatih C. Korkmaz

This study experimentally investigates the buoyancy-driven water exit of axisymmetric bodies to improve understanding free-surface dynamics and hydrodynamic loading relevant to marine and offshore applications. Cylindrical and spherical models were released from rest at different initial submergence depths, with motions captured using high-speed imaging and strain-gauge measurements. Results show that early-stage motion prior to surface interaction is self-similar and largely independent of submergence depth, characterized by constant acceleration and negligible viscous effects. As the bodies approach and breach the free surface, strong coupling occurs between body motion, free-surface deformation, and added-mass variation. The amplitude and width of the disturbed free surface, as well as total hydrodynamic load, increase with submergence depth due to enhanced fluid inertia. Maximum hydrodynamic force occurs immediately before or during surface breach, then decreases rapidly as the entrained water layer detaches. The spherical body exhibits smoother and faster exit with reduced surface disturbance compared to the cylinder. The effect of superhydrophobic coating was also examined; while hydrophobicity did not affect overall exit kinematics or surface evolution, it promoted post-exit breakup of the residual water layer. Overall, submergence depth is identified as the dominant parameter governing free-surface morphology, hydrodynamic loading, and exit velocity.

本研究通过实验研究轴对称体的浮力驱动水出口，以提高对与海洋和近海应用相关的自由表面动力学和水动力载荷的理解。圆柱形和球形模型在不同的初始淹没深度下从静止状态释放，并使用高速成像和应变仪测量捕获运动。结果表明，在表面相互作用之前的早期运动是自相似的，并且在很大程度上与淹没深度无关，其特征是恒定的加速度和可忽略的粘性效应。当物体接近并突破自由表面时，物体运动、自由表面变形和附加质量变化之间发生强耦合。受扰动自由表面的幅值和宽度以及总水动力载荷由于流体惯性的增强而随着深度的增加而增加。最大水动力发生在地表破裂之前或期间，然后随着夹带水层的分离而迅速减小。与圆柱体相比，球形体具有更平滑和更快的出口，减少了表面扰动。还考察了超疏水涂层的效果；虽然疏水性不影响整体的出口运动学或表面演化，但它促进了出口后残余水层的破裂。总的来说，淹没深度被认为是控制自由表面形态、水动力载荷和出口速度的主要参数。

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引用次数: 0

Long-term fatigue reliability analysis of large floating offshore wind turbine structures based on the full probabilistic modeling of multiple uncertainties 基于多不确定性全概率建模的大型海上浮式风力机结构长期疲劳可靠性分析

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124585

Zenghui Liu , Yongbo Peng , Zili Zhang , Zhangjun Liu

This paper proposes a meticulous probabilistic analysis approach for the fatigue reliability assessment of large FOWTs. First, a full probabilistic wind-wave load model considering the uncertainties of wind-wave parameters and wind-wave stochastic field is established based on the C-vine copula method and the dimension-reduction spectral decomposition method (DR-SDM) with just two elementary random variables. Then, three types of uncertainties relating to external loads, material properties and Miner's rule model are considered, and a unified probability space is constructed and partitioned to obtain the representative points for eight-dimensional random variables. On this basis, the full probabilistic analysis framework for the long-term fatigue reliability assessment of FOWTs is established by combining the time-domain S-N curve method and the probability density evolution method (PDEM). Using the proposed method, the long-term fatigue reliability of a 5 MW spar-type FOWT is evaluated and compared with the conventional Monte Carlo simulation method, the sensitivity of the fatigue reliability to the number of representative points of random variables is also investigated. The numerical results demonstrate that the proposed method can provide robust fatigue reliability assessment results using just a few hundred representative points of the random variables. During the normal service period, special attention should be given to the maintaining the tower bottom because its fatigue reliability is significantly lower than that of the blade root.

本文提出了一种精细概率分析方法，用于大型风力发电机组的疲劳可靠性评估。首先，基于C-vine copula方法和降维谱分解（DR-SDM）方法，建立了考虑风浪参数和风浪随机场不确定性的全概率风浪荷载模型。然后，考虑外载荷、材料性质和Miner规则模型三种不确定性，构造并划分统一的概率空间，得到八维随机变量的代表点；在此基础上，将时域S-N曲线法与概率密度演化法（PDEM）相结合，建立了FOWTs长期疲劳可靠性评估的全概率分析框架。利用该方法对某5mw梁式FOWT的长期疲劳可靠性进行了评估，并与传统的蒙特卡罗模拟方法进行了比较，研究了疲劳可靠性对随机变量代表点个数的敏感性。数值计算结果表明，该方法仅需要几百个随机变量的代表性点，就能提供鲁棒的疲劳可靠性评估结果。在正常使用期间，应特别注意塔底的维护，因为它的疲劳可靠性明显低于叶根。

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引用次数: 0

Design and depth control of a beaver-inspired underwater robot based on center-of-mass adjustment 基于质心调整的仿海狸水下机器人设计与深度控制

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124616

Gang Chen , Xianghui Meng , Jianzhong Qiao , Zhixuan Zhang , Wei Wu , Yidong Xu , Huosheng Hu

To enhance the adaptability and maneuverability of underwater bionic robots in complex environments, this study proposes a novel bio-inspired robotic design based on the beaver as a biological prototype, emulating its key locomotion mechanisms. The robot incorporates a flexible spine, an adjustable pitch angle mechanism, and actively actuated webbed feet. By integrating the dynamics of the pitch angle adjustment system with the propulsion actuation system, a comprehensive dynamic model is established. For precise depth control, a hierarchical sliding mode control (HSMC) strategy enhanced by a nonlinear state observer (NSO) is developed. The NSO estimates forward velocity from depth measurements, enabling the HSMC controller to cooperatively regulate propulsion frequency and pitch angle displacement. Experimental results demonstrate that the proposed method achieves high-precision depth control with a steady-state error of less than 0.05 m, significantly improving the robot's stability and robustness under varying hydrodynamic conditions.

为了提高水下仿生机器人在复杂环境中的适应性和可操作性，本研究提出了一种以海狸为生物原型的仿生机器人设计，仿真了其关键运动机制。该机器人包括一个灵活的脊柱，一个可调的俯仰角机构和主动驱动的蹼足。将俯仰角调节系统的动力学与推进作动系统的动力学相结合，建立了综合动力学模型。为了精确控制深度，提出了一种基于非线性状态观测器（NSO）的分层滑模控制策略。NSO从深度测量中估计前进速度，使HSMC控制器能够协同调节推进频率和俯仰角位移。实验结果表明，该方法实现了高精度深度控制，稳态误差小于0.05 m，显著提高了机器人在不同水动力条件下的稳定性和鲁棒性。

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引用次数: 0

Centrifuge modeling-based p-y curves for laterally loaded monopiles in sand considering the effect of pile-soil relative stiffness 考虑桩土相对刚度影响的砂土中横向加载单桩的离心模型p-y曲线

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124518

Yilun Lao , Jiro Takemura , Weihsuan Hsiao , Akihiro Takahashi

This paper presents a new p-y model for predicting the lateral response of monopiles in sand, developed from 18 centrifuge tests on single steel tubular piles of varying dimensions. The model's contribution centers around a new and simple formulation for the initial p-y curve slope that accounts for pile-soil relative stiffness effects typically neglected in other models, a correction coefficient that incorporates the findings in direct p-y measurements by other studies, and the use of an updated ultimate soil resistance calculation incorporating pile-soil skin friction effects. Validated against 18 centrifuge tests featuring a wide range of pile diameters (0.26-4m), embedment depths (1.73-26m), pile wall thicknesses (2 mm −200mm), load eccentricities (0.33-13m), and sand densities (80% and 95%) in prototype scale, the proposed model demonstrates greater accuracy in predicting load-displacement curves and bending moment profiles compared to benchmark models. The model successfully captures the effects of load eccentricity on lateral capacity without requiring additional testing. While the model shows strong agreement with experimental data, the study acknowledges limitations regarding its verification across broader conditions, the need for further refinement in bending moment predictions, and the simplified nature of the correction coefficient for engineering applicability.

本文提出了一种新的预测砂土中单桩横向响应的p-y模型，该模型是由18个不同尺寸的单钢管桩的离心试验发展而来的。该模型的贡献集中在一个新的和简单的初始p-y曲线斜率公式上，该公式考虑了其他模型中通常被忽略的桩-土相对刚度效应，一个校正系数，该系数结合了其他研究中直接p-y测量的结果，以及使用了包含桩-土表皮摩擦效应的更新的最终土阻力计算。通过18次离心试验验证，该模型具有广泛的桩径（0.26-4m）、埋深（1.73-26m）、桩壁厚度（2mm - 200mm）、荷载偏心（0.33-13m）和砂密度（80%和95%）的原型尺度，与基准模型相比，该模型在预测荷载-位移曲线和弯矩曲线方面具有更高的准确性。该模型成功地捕获了载荷偏心对横向承载力的影响，而无需进行额外的测试。虽然该模型与实验数据非常吻合，但该研究承认其在更广泛条件下的验证存在局限性，需要进一步改进弯矩预测，以及工程适用性修正系数的简化性质。

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引用次数: 0

Integrating FELA with EPR MOGA-XL and XGBoost for assessing uplift capacity of buried pipelines in dense sand 将FELA与EPR MOGA-XL和XGBoost集成，用于评估致密砂中埋地管道的提升能力

IF 5.5 2区工程技术 Q1 ENGINEERING, CIVIL

Ocean Engineering

Pub Date : 2026-02-12 DOI: 10.1016/j.oceaneng.2026.124624

Syaifulloh Qoimuddin Ali Basyah , Wittaya Jitchaijaroen , Suraparb Keawsawasvong , Pitthaya Jamsawang

The uplift stability of buried subsea pipelines remains a critical challenge in offshore engineering, particularly in dense sandy seabeds where soil behavior is strongly governed by stress-dependent dilatancy. While geometric modifications such as radial fins have shown promise in improving uplift resistance, their performance in dense sand has not been systematically quantified. The objective of this study is to quantitatively investigate the uplift behavior of finned pipelines embedded in dense sand and to develop efficient predictive tools for design applications. A hybrid framework integrating Finite Element Limit Analysis (FELA) with machine learning techniques is proposed. A comprehensive dataset comprising 2113 numerical simulations was generated by varying embedment ratio (H/D), fin configuration (w_f/D), and soil parameters including relative density (D_R), critical-state friction angle (ϕ_cv), and crushing strength (Q). The results demonstrate that fin integration can enhance uplift resistance by up to 30%, with embedment ratio and particle crushing strength identified as the dominant governing factors. Failure mechanism analyses reveal that the improved performance of finned pipelines is primarily associated with enhanced soil confinement and stress-dependent dilatancy. To facilitate practical design, Extreme Gradient Boosting (XGBoost) was employed to achieve high-accuracy predictions, while Evolutionary Polynomial Regression with Multi-Objective Genetic Algorithm (EPR Moga-XL) was used to derive explicit, interpretable design equations. The proposed framework represents a novel integration of physics-based limit analysis and data-driven modeling for finned pipeline uplift assessment, providing both mechanistic insight and efficient predictive tools. The findings offer a practical basis for preliminary design and assessment of finned subsea pipelines in dense sandy seabeds.

在海上工程中，埋地海底管道的隆升稳定性仍然是一个关键的挑战，特别是在密集的砂质海床中，那里的土壤行为受到应力依赖性膨胀的强烈控制。虽然径向翅片等几何修饰在提高抗隆升能力方面显示出了希望，但它们在致密砂中的性能尚未得到系统的量化。本研究的目的是定量研究嵌入在致密砂中的翅片管道的隆升行为，并为设计应用开发有效的预测工具。提出了一种将有限元极限分析（FELA）与机器学习技术相结合的混合框架。通过不同的嵌入比（H/D）、翅片配置（wf/D）和土壤参数（包括相对密度（DR）、临界状态摩擦角（ϕcv）和抗压强度(Q)），生成了包含2113个数值模拟的综合数据集。结果表明，翅片集成可使抗拔性能提高30%，其中埋置比和颗粒破碎强度是主要影响因素。破坏机制分析表明，翅片管道性能的改善主要与土体约束和应力相关扩容的增强有关。为了便于实际设计，采用极端梯度增强（XGBoost）实现高精度预测，采用多目标遗传算法进化多项式回归（EPR Moga-XL）推导出显式、可解释的设计方程。所提出的框架代表了基于物理的极限分析和数据驱动的翅片管道隆升评估建模的新集成，提供了机制洞察力和有效的预测工具。研究结果为致密砂质海底翅片管道的初步设计和评价提供了实践依据。

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引用次数: 0