Applied Ocean Research最新文献_第10页

Designing robust adaptive ensemble deep learning based decomposition technique for sea level variability prediction 基于鲁棒自适应集成深度学习的海平面变率预测分解技术设计

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2026-01-10 DOI: 10.1016/j.apor.2026.104925

Mohammed Diykh , Mumtaz Ali , Aitazaz Ahsan Farooque , Anwar Ali Aldhafeeri , Abdulhaleem H. Labban

Sea level variability is an urgent climate risk, threatening to vanish islands and coastal areas. Forecasting future sea level rise accurately is fundamental to support experts for flooding and erosion control. In this paper, a novel sea level variability forecast model (CG-CEEMDANHFS-AEM) is proposed integrating correlation graph (CG), a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), Hilbert feature selection approach (HFS), adaptive ensemble model (AEM), and oppositional learning sparrow search algorithm (OLSSA). The AEM is a novel ensemble model that combines the strengths of GRU, self-attention LSTM and XGBoost models based on dynamic weights assignment strategy, adjusting to real-time changes in sea level rise by updating the weights according to the error and performance of the models. Firstly, the input data is pre-processed using correlation graph to remove lower correlated variables and fill the missing values in the data. After that the CEEMDAN technique is employed to decompose the data, followed by HFS to select the most efficient features. The selected features are then employed into the AEM model where the OLSSA is adopted to select the optimal hyper-parameters of the proposed model. To verify the efficiency of the proposed CG-CEEMDANHFS-AEM against comparing models, extensive experiments were conducted to forecast sea level variability for Hillary and Burnie stations in Australia. The results shows that the proposed model obtained the highest accuracy in terms of goodness-of-fit metrics against the state-of-the-art benchmark comparing models. The proposed model can offer a valuable tool for coastal planning and policy making under the recent climate change.

海平面变化是一个紧迫的气候风险，有可能使岛屿和沿海地区消失。准确预测未来海平面上升是支持洪水和侵蚀控制专家的基础。结合相关图（CG）、带自适应噪声的完整集合经验模态分解（CEEMDAN）、Hilbert特征选择方法（HFS）、自适应集合模型（AEM）和对立学习麻雀搜索算法（OLSSA），提出了一种新的海平面变率预测模型CG- ceemdanhfs -AEM。AEM是一种基于动态权值分配策略，结合GRU、自关注LSTM和XGBoost模型优势的新型集成模型，通过根据模型误差和性能更新权值来适应海平面上升的实时变化。首先，利用相关图对输入数据进行预处理，去除相关性较低的变量，填充数据中的缺失值。然后使用CEEMDAN技术对数据进行分解，再使用HFS选择最有效的特征。然后将所选择的特征应用到AEM模型中，其中采用OLSSA来选择所提出模型的最优超参数。为了验证所提出的CG-CEEMDANHFS-AEM与比较模式的效率，进行了大量的实验来预测澳大利亚希拉里和伯尼站的海平面变化。结果表明，所提出的模型在拟合优度指标方面与最先进的基准比较模型相比获得了最高的精度。该模型可为近期气候变化下的沿海规划和政策制定提供有价值的工具。

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引用次数: 0

A massive MPI parallel framework of 3D local discontinuous Galerkin method for simulating large-scale underwater explosion problems 模拟大规模水下爆炸问题的三维局部不连续Galerkin方法的海量MPI并行框架

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2026-01-06 DOI: 10.1016/j.apor.2025.104895

Zhaoxu Lian , Wenbin Wu , Moubin Liu

The discontinuous Galerkin method (DGM) has showed appealing performances in addressing underwater explosion (UNDEX) problems with strong discontinuities. However, most of the DGM are limited to the axisymmetric modeling due to the expensive computational cost required in 3D simulations. In this work, we develop a massive MPI parallel framework of 3D local discontinuous Galerkin method (LDGM) for simulating large-scale UNDEX problems with the cavitation effects. The 3D LDGM based on unstructured tetrahedron elements is adopted to solve the wave equation about dynamic pressure excited by the UNDEX and simulate the propagation of the UNDEX shock waves in the fluid domain. To accelerate the calculation of 3D LDGM, the MPI parallel framework scalable on a high-performance computer is designed. In order to improve the parallel efficiency and expand the computational scalability, some optimized techniques are incorporated into the parallel 3D LDGM model. In particular, the information for data communication is stored contiguously in the access-friendly data structures to efficiently implement concurrent non-blocking communications. The real-time memory management strategies with local parallel I/O are developed in terms of reducing latency and restraining memory utilization. Several numerical examples are performed to assess the accuracy, efficiency and scalability of the MPI-based parallel 3D LDGM model. It is demonstrated that the present model can accurately and efficiently simulate the propagation of UNDEX shock waves and well capture the evolution of the cavitation region in 3D spaces. The parallel efficiency can achieve up to 94.1 % even for 155 million tetrahedral elements on 12,000 CPU cores.

不连续伽辽金方法（DGM）在求解强不连续的水下爆炸问题中表现出了令人满意的性能。然而，由于三维模拟的计算成本昂贵，大多数DGM都局限于轴对称建模。在这项工作中，我们开发了一个三维局部不连续伽辽金方法（LDGM）的大规模MPI并行框架，用于模拟具有空化效应的大规模UNDEX问题。采用基于非结构四面体单元的三维LDGM求解UNDEX激发的动压力波动方程，模拟UNDEX激波在流体域中的传播。为了加快三维LDGM的计算速度，设计了可在高性能计算机上扩展的MPI并行框架。为了提高并行效率和扩展计算可扩展性，在三维LDGM并行模型中引入了一些优化技术。特别地，将用于数据通信的信息连续存储在易访问的数据结构中，以有效地实现并发非阻塞通信。从降低延迟和限制内存使用的角度出发，提出了具有本地并行I/O的实时内存管理策略。通过数值算例验证了基于mpi的并行三维LDGM模型的精度、效率和可扩展性。实验结果表明，该模型能够准确、高效地模拟UNDEX冲击波的传播，并能很好地捕捉空化区域在三维空间中的演化过程。即使在12,000个CPU内核上处理1.55亿个四面体元素，并行效率也可以达到94.1%。

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引用次数: 0

Experimental validation of a modular navigation architecture for marine autonomous surface vehicles with reactive collision avoidance 基于响应式避碰的海上自主水面车辆模块化导航体系结构的实验验证

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2026-01-06 DOI: 10.1016/j.apor.2025.104903

Raphael Zaccone, Filippo Ponzini, Michele Martelli

This paper presents a modular software architecture for the autonomous navigation of surface vehicles, designed around a layered awareness, navigation, guidance, and control structure. The proposed framework separates global path management, reactive local planning for collision avoidance, and control, while situation awareness combines LiDAR perception with INS/GNSS localization to maintain an up-to-date, and realistic representation of the surrounding environment. The architecture is designed around the concepts of modularity and scalability, enabling distributed computation and the flexible integration of modules. The implementation employs a lightweight publish/subscribe protocol to enable efficient real-time communication among modules. The experimental validation of the proposed architecture in a collision avoidance test featuring a research ASV is reported and discussed. The vehicle successfully executed polygonal paths, adapting its trajectory to avoid multiple unexpected obstacles while still reaching its prescribed waypoints. These results demonstrated the reliability of the proposed framework in supporting path following and adaptive collision avoidance under realistic operating conditions.

本文提出了一种基于分层感知、导航、制导和控制结构的地面车辆自主导航模块化软件体系结构。提出的框架分离了全局路径管理、避免碰撞的反应性局部规划和控制，而态势感知将激光雷达感知与INS/GNSS定位相结合，以保持对周围环境的最新和真实的表示。该体系结构是围绕模块化和可伸缩性的概念设计的，支持分布式计算和模块的灵活集成。该实现采用轻量级发布/订阅协议来实现模块之间的高效实时通信。本文报道并讨论了该架构在一辆研究型自动驾驶汽车避碰测试中的实验验证。车辆成功地执行多边形路径，调整其轨迹以避免多个意外障碍物，同时仍然到达指定的路径点。这些结果证明了该框架在实际操作条件下支持路径跟踪和自适应避碰的可靠性。

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引用次数: 0

Integrated berthing risk assessment framework using a combination of machine learning with measured berthing velocity 综合靠泊风险评估框架，结合机器学习和测量靠泊速度

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2026-01-06 DOI: 10.1016/j.apor.2025.104904

Sang-Won Lee , Ik-Soon Cho

Port terminals face increasing operational demands that often result in elevated berthing velocities and potential structural damage to berthing facilities. Traditional berthing design criteria primarily rely on static velocity thresholds without considering dynamic interactions between ship characteristics, environmental conditions, and structural response of marine infrastructure. This study presents a comprehensive berthing risk assessment framework that integrates measured berthing velocity with machine hybrid machine learning approaches to enhance port terminal safety and infrastructure protection. Field measurements were conducted over five years (2017–2022) at a major tanker terminal using laser-based Docking Aid Systems, capturing over 900 berthing events across three jetties with varying vessel capacities. The proposed methodology employs K-means clustering to establish risk levels for various influence factors, including weather conditions, ship particulars, and human factors such as pilot experience. Multiple machine learning algorithms were combined to determine optimal weight factors for each risk category, enabling comprehensive risk quantification. The developed model achieved a detection rate of approximately 79 % for high-risk situations, successfully identifying 41 out of 52 cases that exceeded safety criteria. The ensemble approach, combining multiple algorithms with performance-weighted coefficients, demonstrated superior accuracy compared to individual models. This proposed methodology enables quantitative risk evaluation before berthing operations, providing early warning capabilities and objective decision-making support for port operations.

港口码头面临着日益增长的运营需求，这往往导致靠泊速度的提高和靠泊设施的潜在结构损坏。传统的靠泊设计准则主要依赖于静态速度阈值，而没有考虑船舶特性、环境条件和海洋基础设施结构响应之间的动态相互作用。本研究提出了一个综合的靠泊风险评估框架，该框架将测量靠泊速度与机器混合机器学习方法相结合，以增强港口码头安全和基础设施保护。在2017-2022年的5年时间里，使用基于激光的停靠辅助系统在一个主要的油轮码头进行了现场测量，在三个不同船舶容量的码头捕获了900多个靠泊事件。所提出的方法采用k均值聚类来确定各种影响因素的风险水平，包括天气条件、船舶细节和人为因素（如飞行员经验）。结合多种机器学习算法来确定每个风险类别的最佳权重因子，从而实现全面的风险量化。开发的模型在高风险情况下的检测率约为79%，成功识别出52例中超过安全标准的41例。与单个模型相比，集成方法将多种算法与性能加权系数相结合，显示出更高的准确性。提出的方法能够在靠泊作业前进行定量风险评估，为港口作业提供早期预警能力和客观决策支持。

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引用次数: 0

Shallow-water acoustic analysis with an accelerated isogeometric boundary element approach 用加速等几何边界元方法进行浅水声学分析

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2025-12-15 DOI: 10.1016/j.apor.2025.104894

Yongsong Li , Jinsheng Xuan , Chengmiao Liu , Gaochao Zhao , Yanming Xu

Underwater acoustic modeling plays a crucial role in marine engineering applications, especially in shallow-water environments where complex boundary interactions dominate sound propagation. Traditional numerical approaches like the finite element method often struggle with the challenges posed by unbounded domains and artificial boundary conditions. In contrast, the isogeometric boundary element method (IGABEM) offers a powerful alternative by combining the dimensionality reduction and infinite domain handling capabilities of the boundary element method with the exact geometry representation and smooth basis functions of isogeometric analysis. This paper presents a novel IGABEM framework tailored for acoustic simulations in shallow-water settings, where acoustic propagation is governed by coupled reflections from the sea surface and sea floor. Additionally, in order to enhance computational efficiency and scalability, we integrate and adapt advanced acceleration techniques, including the fast multipole method, frequency decoupling via Taylor expansion, and the second-order arnoldi algorithm. The numerical results validate the accuracy, robustness, and computational advantages of the proposed method, establishing it as a promising tool for high-fidelity underwater acoustic analysis.

水声建模在海洋工程应用中起着至关重要的作用，特别是在复杂的边界相互作用主导声音传播的浅水环境中。传统的数值方法，如有限元法，经常受到无界域和人工边界条件的挑战。而等高边界元法（IGABEM）将边界元法的降维和无限域处理能力与等高分析的精确几何表示和光滑基函数相结合，提供了一种强大的替代方法。本文提出了一种新的IGABEM框架，专门用于浅水环境下的声学模拟，在浅水环境下，声音传播受海面和海底的耦合反射控制。此外，为了提高计算效率和可扩展性，我们集成并采用了先进的加速技术，包括快速多极子方法、Taylor展开频率解耦和二阶arnoldi算法。数值结果验证了该方法的精度、鲁棒性和计算优势，表明该方法是一种很有前途的高保真水声分析工具。

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引用次数: 0

Viscosity and nonlinear resonant heave response of a semi–submersible floating wind energy platform 半潜式浮式风能平台的黏度与非线性共振升沉响应

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2025-12-04 DOI: 10.1016/j.apor.2025.104830

Lulu Liu , Ian A. Milne , Hugh A. Wolgamot , Wenhua Zhao , Raúl Guanche

Floating offshore wind energy represents a promising frontier in marine renewable energy, enabling deployment in deeper waters. Among the various solutions for floating wind energy, semi-submersible platforms have emerged as the most viable option. The success of this technology depends on their hydrodynamic performance. Current engineering practice for design and operability assessment has primarily focused on short wave excitation, with less attention to long-period waves. Swells carry energy near the natural periods of these structures and are more likely to induce resonant responses in heave, in which scenario the prediction is challenging and less understood. This may lead to over-conservative designs and thus unnecessarily high cost. To address this gap, this study examines resonant responses driven by long-period waves through linear processes. In resonance, viscous effects play a critical role, e.g., in determining response amplitudes. However, estimating viscous effects is challenging as a result of their underlying complex physics and nonlinearity. To better understand the viscous effects and their impact on floating wind turbines, a series of scaled model tests was analysed for a 10-MW floating wind energy platform. To facilitate the interpretation of the experimental results, inviscid flow calculations were also performed. The results indicate that viscous damping is positively correlated with the Keulegan–Carpenter (KC) number that characterizes the relative velocity between the floating system and the surrounding water particles. A striking observation is that viscosity can significantly alter the added mass, which is key to the estimation of the natural frequency of the floating system.

浮动海上风能代表了海洋可再生能源的一个有前途的前沿，可以在更深的水域部署。在浮式风能的各种解决方案中，半潜式平台已成为最可行的选择。这项技术的成功取决于它们的水动力性能。目前的工程设计和可操作性评估主要集中在短波激励上，而对长周期波的关注较少。在这些结构的自然周期附近，涌浪携带能量，更有可能引起起伏时的共振反应，在这种情况下，预测是具有挑战性的，而且人们对其了解较少。这可能会导致过度保守的设计，从而导致不必要的高成本。为了解决这一差距，本研究通过线性过程考察了长周期波驱动的共振响应。在共振中，粘性效应起着关键作用，例如，在确定响应振幅方面。然而，由于其潜在的复杂物理和非线性，估计粘性效应是具有挑战性的。为了更好地了解粘性效应及其对浮式风力发电机组的影响，对一个10兆瓦的浮式风力发电平台进行了一系列比例模型试验分析。为了便于对实验结果的解释，还进行了无粘流计算。结果表明，粘性阻尼与表征漂浮系统与周围水颗粒之间相对速度的Keulegan-Carpenter （KC）数呈正相关。一个引人注目的观察是，粘度可以显著改变增加的质量，这是估计浮动系统固有频率的关键。

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引用次数: 0

A triad framework for ship carbon reduction: Direct CO2 measurement, multi-intelligence fusion prediction, and Cauchy-enhanced speed optimization 船舶碳减排的三重框架：直接二氧化碳测量，多智能融合预测和柯西增强速度优化

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2025-12-06 DOI: 10.1016/j.apor.2025.104879

Xinxing Tan , Dehua Wang , Pu Sun , Tian Lan

Ship carbon emissions have become a global concern, yet significant challenges persist in precise quantification, real-time assessment, and operational optimization. This study proposes an integrated "direct measurement-emission prediction-speed optimization" framework to bridge these gaps. Firstly, a shipboard CO₂ direct measurement system is deployed to collect high-frequency dynamic data. Through synergistic application of domain expertise, statistical methods, and HDBSCAN clustering, erroneous values, anomalies, and outliers are effectively identified and eliminated, yielding a high-confidence fine-grained dataset for microscopic emission analysis and operational decisions. Secondly, four metaheuristic algorithms are incorporated into a dual-adaptive prediction architecture, expanding its mechanistic boundaries to construct a highly reliable and precise CO₂ prediction model. Finally, an Enhanced Equilibrium Optimizer (EEO) with Cauchy mutation strategy demonstrates superior performance in carbon-oriented speed optimization. During a 6-day coastal voyage, EEO algorithm achieves direct carbon reduction of 12.27 tons and 4.11% energy efficiency improvement, realizing synergistic gains in decarbonization and Energy Efficiency Operational Indicator (EEOI). This research provides a holistic technical framework and granular decision support for shipping decarbonization.

船舶碳排放已成为全球关注的问题，但在精确量化、实时评估和运营优化方面仍存在重大挑战。本研究提出了一个综合的“直接测量-排放预测-速度优化”框架来弥补这些差距。首先，部署了船载二氧化碳直接测量系统，收集高频动态数据。通过协同应用领域专业知识、统计方法和HDBSCAN聚类，可以有效识别和消除错误值、异常值和异常值，从而生成高置信度的细粒度数据集，用于微观排放分析和操作决策。其次，将四种元启发式算法纳入双自适应预测体系结构，扩展其机制边界，构建高可靠、高精度的CO₂预测模型；最后，基于柯西突变策略的增强型均衡优化器（EEO）在碳定向速度优化中表现出了优异的性能。在6天的沿海航次中，EEO算法实现了12.27吨的直接减碳和4.11%的能效提升，实现了脱碳和能效运营指标（EEOI）的协同收益。本研究为航运脱碳提供了整体的技术框架和粒度决策支持。

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引用次数: 0

Landslide impacts on built environment: Numerical analysis of the forces exerted by granular material collapsing on dry and submerged conditions 滑坡对建筑环境的影响：干燥和淹没条件下颗粒状物质崩塌力的数值分析

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2026-01-06 DOI: 10.1016/j.apor.2025.104902

Gabriel Barajas , Javier L. Lara , Alessandro Romano , Eduard Puig Montellà

Landslide-generated impacts represent a critical hazard for coastal and reservoir infrastructures, yet their underlying fluid dynamics remain poorly understood due to the complexity of turbulent, free-surface flows. In this work, OpenFOAM® is used to investigate sudden impacts on surfaces caused by granular landslides. First, three sets of experiments are used to validate the numerical framework: a dry granular flow impact on a wall in an inclined flume, a debris avalanche impacting a pier and a dam-break interaction of a fluid impact on a vertical cylinder. For each case, numerical predictions are compared with experiments in terms of impact forces, providing confidence that the solver can reproduce sudden loads caused by granular and fluid masses. Then, the validated numerical setup is used to study submerged landslide impacts on slender cylinders, capturing the interaction between the granular slide and the free surface, resolving large-scale vortical structures and their role in energy transfer and dissipation. Results highlight two distinct stages of the phenomenon: (i) the initial impact and jet formation, and (ii) turbulent dissipation and recirculation. The analysis provides quantitative insights into velocity fields, pressure distributions, and turbulence intensities, and identifies key mechanisms driving energy loss. These findings contribute to a deeper physical understanding of landslide–impacts and offer a basis for improved hazard assessment and engineering design of protective structures.

滑坡产生的影响对沿海和水库基础设施构成了严重的危害，但由于湍流、自由表面流动的复杂性，人们对其潜在的流体动力学知之甚少。在这项工作中，OpenFOAM®用于研究颗粒状滑坡对表面造成的突然影响。首先，用三组实验验证了数值框架：干颗粒流对倾斜水槽壁面的冲击，碎片雪崩对桥墩的冲击以及流体对垂直圆柱体的冲击溃坝相互作用。对于每一种情况，数值预测与实验在冲击力方面进行了比较，为求解器可以重现由颗粒和流体质量引起的突然载荷提供了信心。在此基础上，采用验证的数值模拟方法研究了滑坡体对细长圆柱体的冲击，捕捉了颗粒状滑坡体与自由表面的相互作用，解析了大尺度的螺旋结构及其在能量传递和耗散中的作用。结果强调了该现象的两个不同阶段：(i)初始撞击和射流形成阶段，以及（ii）湍流耗散和再循环阶段。该分析提供了对速度场、压力分布和湍流强度的定量见解，并确定了导致能量损失的关键机制。这些发现有助于加深对滑坡影响的物理认识，并为改进危害评估和防护结构的工程设计提供基础。

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引用次数: 0

A study on the separation method of radiation noise contributions from multiple ship equipment based on reverse transfer path analysis 基于反向传递路径分析的舰船多设备辐射噪声贡献分离方法研究

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2026-01-01 Epub Date: 2025-12-06 DOI: 10.1016/j.apor.2025.104890

Tao Peng , Rongwu Xu , Jiarui Zhang , Jinwei Liu , Zhenyu Yao

Accurately separating and quantifying the contributions of individual mechanical equipment from coupled noise in ships is critical for further reducing radiated noise from onboard machinery. Transfer Path Analysis (TPA) and Operational Transfer Path Analysis (OTPA) are widely adopted for vibration-noise transfer characterization; however, their efficiency and accuracy in shipboard noise testing scenarios remain limited. To address this challenge, this paper proposes a Reverse Transfer Path Analysis (RTPA) method based on pseudo-force and reciprocity testing principles. This method eliminates the need for machinery disassembly or installation of large-scale exciters, enabling in-situ measurements of equipment excitation forces and frequency response functions, thereby significantly improving testing efficiency. Validation through underwater noise experiments on a scaled ship model demonstrates the effectiveness of RTPA in decoupling machinery noise contributions. Results show excellent agreement with measured data: shaft-related tonal frequencies and amplitudes fully align with ground-truth values, and the broadband noise level error is only 3.1 dB, compared to a 10.3 dB error for the OTPA method. These findings confirm the enhanced accuracy and effectiveness of the RTPA method in resolving coupled noise separation challenges for shipboard machinery, offering robust support for vibration/noise reduction strategies and acoustic optimization in ship design.

准确地分离和量化船舶中单个机械设备对耦合噪声的贡献对于进一步降低船上机械的辐射噪声至关重要。传递路径分析（TPA）和操作传递路径分析（OTPA）被广泛用于振动-噪声传递表征；然而，它们在舰船噪声测试场景中的效率和准确性仍然有限。为了解决这一挑战，本文提出了一种基于伪力和互易测试原理的反向传递路径分析（RTPA）方法。该方法无需拆卸机械或安装大型激振器，可以现场测量设备激振力和频响函数，从而显著提高测试效率。通过船舶模型的水下噪声实验验证了RTPA解耦机械噪声贡献的有效性。结果显示与测量数据非常吻合：轴相关的音调频率和幅度与地真值完全一致，宽带噪声级误差仅为3.1 dB，而OTPA方法的误差为10.3 dB。这些研究结果证实了RTPA方法在解决船舶机械耦合噪声分离挑战方面的准确性和有效性，为船舶设计中的减振/降噪策略和声学优化提供了强有力的支持。

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引用次数: 0

A coupled Nonlinear Shallow Water Equations — Exner approach for wave–sediment interplay in hybrid coastal defense 混合海防中波沙相互作用的非线性耦合浅水方程- Exner方法

IF 4.4 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-12-01 Epub Date: 2025-10-16 DOI: 10.1016/j.apor.2025.104792

Hany Qoshirotur Rif’atin , Ikha Magdalena , Muhammad Syahril Badri Kusuma , Alamsyah Kurniawan

Coastal erosion, increasingly driven by human activities and climate change, poses escalating threats to shoreline stability and nearby communities. While coastal vegetation, especially mangroves, plays a crucial role in mitigating erosion, these ecosystems themselves are under threat from wave impacts and sediment loss. Grey infrastructure, such as breakwaters, is often proposed to enhance coastal resilience and protect vegetation. However, the interactions among wave dynamics, structural interventions, and sediment transport, which is crucial for vegetation survival, are frequently overlooked. This study develops a one-dimensional coupled hydrodynamic–morphodynamic model to simulate wave propagation and sediment evolution in coastal areas featuring hybrid coastal defense, which incorporates both green (mangrove) and grey (breakwater) protection strategies. The model combines the Nonlinear Shallow Water Equations (NSWE) for hydrodynamics with the Exner equation for morphodynamics, solved numerically using the Staggered Finite Volume Method. The NSWE is used due to its lower computational cost compared to other more complex models, yet it still deliver sufficient accuracy for simulating wave dynamics. Validation against diverse experimental datasets confirms the model’s accuracy in capturing wave and sediment dynamics. The validated model is then applied to investigate the effectiveness of multiple configurations of hybrid structure in reducing wave height and erosion. Additionally, sensitivity analyses explore the effects of several key parameters, offering insights to inform the development of more effective and adaptive coastal protection strategies. Further analysis is also conducted to observe how the erosion-related parameters change at field scale under storm conditions.

人类活动和气候变化日益加剧了海岸侵蚀，对海岸线稳定和附近社区构成了日益严重的威胁。虽然沿海植被，特别是红树林，在减缓侵蚀方面发挥着至关重要的作用，但这些生态系统本身也受到海浪影响和沉积物损失的威胁。灰色基础设施，如防波堤，经常被提议用来增强海岸的弹性和保护植被。然而，对植被生存至关重要的波浪动力学、结构干预和泥沙输运三者之间的相互作用却经常被忽视。本研究建立了一维水动力-形态动力耦合模型，以模拟具有混合海防的沿海地区的波浪传播和沉积物演变，其中包括绿色（红树林）和灰色（防波堤）保护策略。该模型结合了流体动力学的非线性浅水方程（NSWE）和形态动力学的Exner方程，采用交错有限体积法进行数值求解。与其他更复杂的模型相比，NSWE的计算成本更低，但它仍然提供足够的精度来模拟波浪动力学。对不同实验数据集的验证证实了该模型在捕获波浪和泥沙动力学方面的准确性。将验证模型应用于研究混合结构的多种构型对降低浪高和侵蚀的有效性。此外，敏感性分析探讨了几个关键参数的影响，为制定更有效和适应性更强的海岸保护策略提供了见解。进一步分析了暴雨条件下野外尺度上侵蚀相关参数的变化规律。

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引用次数: 0