Applied Ocean Research最新文献

{"title":"An improved direct forcing immersed boundary method for floating body simulations in waves","authors":"Ahmet Soydan,&nbsp;Widar W. Wang,&nbsp;Hans Bihs","doi":"10.1016/j.apor.2025.104523","DOIUrl":"10.1016/j.apor.2025.104523","url":null,"abstract":"<div><div>This paper introduces a novel direct forcing immersed boundary method tailored to simulate nonlinear interactions between ocean waves and arbitrarily complex free-floating structures. Within an open-source hydrodynamic framework, we couple the fluid–structure interaction (FSI) algorithm with the two-phase flow solver through forcing at the fluid–solid interface. We substantially enhance this coupling process by altering the density interpolation method, significantly reducing the interface smearing region, which improves both the stability and accuracy of the fluid flow in the vicinity of the floating objects. The tracking of the fluid–solid interface in the Eulerian domain is based on a level set function, thus avoiding the need for dynamically moving or overset meshes and greatly simplifying the mesh generation process. Rigid body dynamics are implemented using Euler parameters and Hamiltonian mechanics, allowing for arbitrarily large motions of the floating body. The presented approach is tested and validated with several 2D and 3D problems, including a full-scale simulation of a floating semi-submersible offshore wind turbine in waves. All numerical results demonstrate the accuracy and robustness of the new method, highlighting its potential as an outstanding alternative to existing numerical approaches for realistic floating-body simulations in waves.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104523"},"PeriodicalIF":4.3,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of thrust bearing parameters in shafting-shell coupling system from frequency response function with artificial neural networks","authors":"Cong Zhang ,&nbsp;Yaqi Tian ,&nbsp;Yifan Xie ,&nbsp;Lei Yang","doi":"10.1016/j.apor.2025.104528","DOIUrl":"10.1016/j.apor.2025.104528","url":null,"abstract":"<div><div>The thrust bearing is a critical component for power transmission and vibration coupling between the propulsion shafting and the shell of the underwater vehicle. Identifying thrust bearing parameters is crucial for studying the vibration and diagnosing bearing faults of the underwater vehicle. In this study, key information was extracted from the frequency response function (FRF) of the shafting-shell coupling system, and then the artificial neural network (ANN) was used to predict the stiffness and damping of the thrust bearing. The dataset used to train the ANN came from the analytical dynamic model of the shafting-shell system. This analytical approach offers high computational efficiency, making it feasible to generate a substantial amount of training data within a reasonable timeframe. In the analytical dynamic model, the shell was modeled using the Flügge theory, while the shafting system was modeled using the Euler-Bernoulli beam theory. The bearings were simplified as a spring-damping system to represent the connection between the shafting system and the shell. This study employed two ANN algorithms: Backpropagation Neural Network (BP) and Genetic Algorithm-optimized Backpropagation Neural Network (GABP). The results indicate that both BP and GABP effectively predict the stiffness and damping of thrust bearings. Moreover, GABP demonstrates more stable prediction results with smaller prediction errors. The proposed method for predicting thrust bearing parameters leverages features from the FRF to train the ANN, which provides good robustness, maintaining effective results even when the signal-to-noise ratio of the FRF is reduced. The thrust bearing parameter prediction model was validated through experiment, confirming the effectiveness of using ANNs to predict bearing parameters in shafting-shell coupling systems from FRF. This study realizes efficient prediction of bearing parameters, providing a reference for vibration reduction, operational state monitoring, and fault diagnosis of underwater vehicles.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104528"},"PeriodicalIF":4.3,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An evaluation method for pipeline corrosion risk index weighting in beach and sea oil fields based on combined weighting with improved hierarchical analysis and Bayesian networks","authors":"Wenbin Wang,&nbsp;Shibin Jiang,&nbsp;Jianguo Liu,&nbsp;Gan Cui","doi":"10.1016/j.apor.2025.104522","DOIUrl":"10.1016/j.apor.2025.104522","url":null,"abstract":"<div><div>Coastal oil and gas pipelines are prone to corrosion due to complex environmental factors, while traditional risk assessment methods often suffer from subjective bias and oversimplified, one-sided weighting strategies. To address these limitations, this study proposes a risk evaluation model based on game theory, combining an improved analytic hierarchy process (AHP) and a Bayesian network for composite weighting. First, a coastal pipeline corrosion leakage risk indicator system is constructed. Next, a gray relational analysis-improved AHP model is introduced for hierarchical weighting. A Bayesian network model is constructed using the T-S fuzzy fault tree, and probability weighting is performed through hierarchical importance analysis. Finally, based on game theory, the above two weightings are combined to calculate the composite weight. Additionally, to verify the model's applicability, a corrosion risk assessment for a coastal pipeline was conducted. The results indicated that the model could effectively mitigates the over-reliance on expert subjective judgment and fragmented analysis of risk factors in corrosion risk assessment for coastal oil and gas pipelines, Critical factors such as high sand content and external coating failure were identified as dominant risks, which were overlooked in conventional models. The evaluation results were generally consistent with the actual situation.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104522"},"PeriodicalIF":4.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of wave characteristics in the Northern Yellow sea based on field observations","authors":"Hongyuan Shi ,&nbsp;Huaiyuan Xue ,&nbsp;Longsheng Li ,&nbsp;Chao Zhan ,&nbsp;Zaijin You","doi":"10.1016/j.apor.2025.104527","DOIUrl":"10.1016/j.apor.2025.104527","url":null,"abstract":"<div><div>With the increasing frequency of extreme weather events driven by global climate change, a comprehensive analysis of wave characteristics under extreme meteorological conditions is essential for improving the safety of maritime transportation. Previous research has predominantly focused on wave characteristics during typhoons, while studies on wave characteristics under frequent cold wave climates in mid- to high-latitude regions are still lacking. In this study, we used half-year wave data (March to September 2023) for the Northern Yellow Sea. We conducted a statistical analysis of wave characteristic values in this sea area and investigated the relationship between various characteristic wave heights, the mean wave height, and the significant wave height. A detailed analysis of the wave height, wave period, and wave spectrum during a typical cold wave event in April was performed to describe the wave characteristics and their variations in this area under extreme meteorological conditions. The results showed that the wave height distribution in this region exhibited a Weibull distribution, which fitted better than the Rayleigh and Gumbel distributions, especially in cases with high wave heights. The distribution of the wave period diverged as the spectral width increased, and the Sunfu and Gumbel distributions achieved better fitting under wide-spectrum conditions. The joint distribution of the wave height and period exhibited an inclined triangular pattern; however, discrepancies remained when compared with theoretical models, particularly for large wave heights and extended periods. Additionally, during cold wave events, the wave characteristics in the region exhibited a double-peaked spectrum as a result of the interaction between low-frequency swells and high-frequency wind waves. Our research results provide a reference for maritime navigation safety in this sea area.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104527"},"PeriodicalIF":4.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatigue damage assessment of steel catenary risers in the touchdown zone accounting for soil remoulding and reconsolidation effects","authors":"Hossein Janbazi,&nbsp;Hodjat Shiri","doi":"10.1016/j.apor.2025.104526","DOIUrl":"10.1016/j.apor.2025.104526","url":null,"abstract":"<div><div>The design of steel catenary risers (SCRs) is mainly affected by fatigue performance in the touchdown zone (TDZ), where the riser cyclically interacts with the seabed. This cyclic motion leads to seabed soil softening and remoulding. However, over an extended period of riser operations, the seabed soil undergoes a drainage because of small motion amplitudes of the floating vessel during calm weather or a limited contact with the seabed due to vessel relocation. This may cause recovery of the soil strength associated with excess pore pressure dissipation resulting in an extra fatigue damage accumulation in the TDZ. In the current study, a global SCR analysis has been conducted using a series of coded springs along the TDZ to model advanced SCR-seabed interactions. The instantaneous undrained shear strength of the soil is determined by using a recently developed effective stress framework. The effects of soil remolding and consolidation were integrated during both the dynamic motion of the SCR and intervening pause periods within the critical-state soil mechanics. The model updates the SCR-soil interaction spring at every time increment of dynamic analysis, calculating the cross-section stress range while taking into account the overall configuration of the riser on the seabed. The study showed that the consolidation may result in an increased fatigue damage of about 23 %, which is currently neglected by the existing non-linear SCR-soil interaction models.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104526"},"PeriodicalIF":4.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flexible content-aware image synthesis for maritime tasks with diffusion models","authors":"Zhenfeng Xue ,&nbsp;Yuanqi Hu ,&nbsp;Ankang Lu ,&nbsp;Zhuo Chen ,&nbsp;Ying Zang ,&nbsp;Zhonghua Miao","doi":"10.1016/j.apor.2025.104511","DOIUrl":"10.1016/j.apor.2025.104511","url":null,"abstract":"<div><div>Maritime environmental perception suffers greatly from data lack due to the high cost of data collection at sea. In this paper, a novel image synthesis method is proposed to automatically generate target images with diverse foreground and background. Specifically, foreground images for various poses are generated using a diffusion model, presenting different modalities of the detected target. The environment conditions of the background images are flexibly adjusted by inputting semantic prompts to another diffusion model. Then a 3D affine diffusion model is proposed for effective fusion of foreground and background. This module calculates the size and position of the foreground image within the background image through affine transformation, and utilizes the excellent image fusion ability of the diffusion model to achieve high-quality image synthesis. As a result, a set of dynamically variable foreground and background images are generated to increase the pose and weather diversity of maritime object detection samples. Extensive experiments are conducted to verify the effectiveness of image synthesis algorithms, and this method can also serve downstream tasks, effectively improving the accuracy of maritime environmental perception algorithms. The code is available at <span><span>https://github.com/xuezhen2018/flexible_content_aware_image_synthesis</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104511"},"PeriodicalIF":4.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innovative prognostic methodology for pipe defect detection leveraging acoustic emissions analysis and computational modeling integration","authors":"Ahmad Braydi ,&nbsp;Pascal Fossat ,&nbsp;Mohsen Ardabilian ,&nbsp;Olivier Bareille","doi":"10.1016/j.apor.2025.104521","DOIUrl":"10.1016/j.apor.2025.104521","url":null,"abstract":"<div><div>Pipelines play a crucial role in transporting essential resources such as water, oil, and gas across industrial, urban, and environmental infrastructures. Clogging remains a persistent challenge, potentially resulting in catastrophic failures, operational disruptions, increased maintenance costs, and serious safety risks. This study presents a novel prognostic and health monitoring approach that utilizes bubble-induced acoustic emissions to detect and characterize pipeline blockages. An analytical model is developed to capture the acoustic signatures of detaching bubbles, revealing features highly sensitive to clogging. Finite element simulations using Abaqus further investigate how different clogging conditions affect acoustic wave propagation. These insights drive the development of a machine learning-based predictive maintenance strategy, validated on real-world datasets. The results demonstrate exceptional accuracy, with most classifiers achieving 100% detection rates for clogging presence, shape, and severity. Additionally, model generalization tests show that machine learning algorithms adapt more effectively to varying clogging thickness than clogging shape. This research paves the way for a highly accurate, non-destructive monitoring solution, enhancing predictive maintenance and ensuring the reliability of industrial pipelines.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104521"},"PeriodicalIF":4.3,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Water impact of V-shaped wedge at constant velocity: Influence of deadrise angle and stiffness panels","authors":"Bilel Meziane ,&nbsp;Aboulghit El Malki Alaoui ,&nbsp;Alain Nême ,&nbsp;Bruno Leblé ,&nbsp;Dany Bellanger","doi":"10.1016/j.apor.2025.104494","DOIUrl":"10.1016/j.apor.2025.104494","url":null,"abstract":"<div><div>In this paper, we report the results of our experimental investigation regarding the strain and pressure distribution on a wedge upon entering water. Slamming experiments were conducted on a hydraulic test-rig, enabling a constant velocity throughout the process. The influence of the deadrise angle and stiffness on the hydroelastic behavior of three aluminum wedges, with a deadrise angle of <span><math><mrow><msup><mn>30</mn><mo>∘</mo></msup><mo>,</mo><mspace></mspace><msup><mn>45</mn><mo>∘</mo></msup><mspace></mspace><mi>a</mi><mi>n</mi><mi>d</mi><mspace></mspace><msup><mn>60</mn><mo>∘</mo></msup></mrow></math></span> is studied. First, an investigation is made on whether a change in deadrise angle influences the behavior of the wedge with regards to panel strength and velocity. Second, the direct influence of the deadrise angle is shown. Finally, a general study of maximum pressure and jet velocity dependency on the aforementioned input parameters is made.</div><div>For the stiffest panels, the pressure coefficient <span><math><msub><mi>C</mi><mi>p</mi></msub></math></span> values vary very little and are quite similar to those in the case of rigid wedge. Indeed, at a constant velocity, it has been demonstrated that <em>Cp</em> depends only on the shape of the solid body. As the stiffness decreases, <span><math><msub><mi>C</mi><mi>p</mi></msub></math></span> increases for all deadrise angles. The main result is that for all angles and velocities studied, a decrease in stiffness leads to an increase in normalized slamming pressure. This leads to a safety factor of 2 considering the design of stiffened panels subjected to slamming with pressure coefficients of rigid panels. The results presented allow their use to validate numerical studies of hydro-elastic impact problems.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104494"},"PeriodicalIF":4.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical investigation on underwater explosion shock wave and cavitation characteristics in heterogeneous fluid","authors":"Wenbin Wu,&nbsp;Yuntao Lei,&nbsp;Guo-Qing Chen,&nbsp;Junrong Wang","doi":"10.1016/j.apor.2025.104516","DOIUrl":"10.1016/j.apor.2025.104516","url":null,"abstract":"<div><div>Due to the combined action of the oceanic climate and environmental factors, there often exist the sound speed thermocline regions in the real ocean environment. The abrupt change of the sound speed would affect the amplitude and propagation trajectory of underwater explosion (UNDEX) loading. However, the effects of the fluid heterogeneity on the UNDEX loading are not fully understood. In this study, based on the local discontinuous Galerkin (LDG) method, the axisymmetric calculation model for the UNDEX loading in the heterogeneous fluid is established. Unlike the previously developed UNDEX loading models in the homogeneous fluid, the influence of the sound speed gradient is considered in the LDG governing equation. The continuity conditions about the dynamic pressure and flux are adopted to compute the numerical fluxes at the sound speed discontinuous interface, which can ensure the energy conservation property. By comparing with the standing wave and traveling wave benchemarks and UNDEX shock wave propagation case, the effectiveness of the present model in solving wave propagation problems is validated. Using this model, the effects of the sound speed discontinuous interface and sound speed gradient on the UNDEX loading and cavitation characteristics near the free surface are investigated. It can be found that the UNDEX incident shock wave would form the reflection and refraction phenomenon at the sound speed discontinuous interface. With the increase of the fluid sound speed, the pressure peak of the incident wave would decrease and the cavitation effects would be weakened. In the heterogeneous fluid with the sound speed gradient of -10 s^-1, the first pressure peak at the test point would increase by 8.45% and the cavitation duration would increase by 16.67% compared with the homogeneous fluid case.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104516"},"PeriodicalIF":4.3,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-term significant wave height prediction using adaptive variational mode decomposition and error-compensation model","authors":"Junheng Pang,&nbsp;Sheng Dong","doi":"10.1016/j.apor.2025.104519","DOIUrl":"10.1016/j.apor.2025.104519","url":null,"abstract":"<div><div>Significant wave height (Hs) is a critical parameter for the design of offshore structures and marine construction planning. Recently, pre-processing techniques have been extensively employed to enhance the performance of Hs predictions. Although variational mode decomposition (VMD) has been proven as an effective tool, it is not parameter-adaptive, and manual parameter selection introduces significant uncertainty. To address this issue, an adaptive VMD method, termed GAVMD, is developed, integrating the grey wolf optimizer (GWO), attention entropy (AE), and VMD. Furthermore, the gated recurrent unit (GRU) and extreme learning machine (ELM) are combined into an error-compensation model (GRU-ELM) to perform prediction tasks. By integrating GAVMD with the error-compensation model, a novel hybrid model, GAVMD-GRU-ELM, is proposed for Hs prediction. To validate the proposed model, two single models, ELM and GRU, as well as two hybrid models, VMD-GRU and GAVMD-GRU, are adopted as baselines. The experimental results demonstrate that while single models perform adequately for 3-h predictions, they fall short for 6-h forecasts. In contrast, hybrid models consistently achieve accurate predictions, benefiting from VMD or GAVMD, with GAVMD showing superior improvement compared to VMD. In all prediction scenarios, GAVMD-GRU-ELM outperforms the other models, indicating that the error-compensation model effectively enhances forecast accuracy.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"158 ","pages":"Article 104519"},"PeriodicalIF":4.3,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}