Marine Structures最新文献

Deterministic real-time prediction of ship roll motion with quantified uncertainty based on machine learning 基于机器学习的船舶横摇运动量化不确定性的确定性实时预测

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-29 DOI: 10.1016/j.marstruc.2025.103946

Limin Huang , Hangyu Chen , Yejia Feng , Gaoxiang Sun , Hao Jiang , Xuewen Ma

{"title":"Deterministic real-time prediction of ship roll motion with quantified uncertainty based on machine learning","authors":"Limin Huang , Hangyu Chen , Yejia Feng , Gaoxiang Sun , Hao Jiang , Xuewen Ma","doi":"10.1016/j.marstruc.2025.103946","DOIUrl":"10.1016/j.marstruc.2025.103946","url":null,"abstract":"<div><div>Real-time prediction of the ship motion in advance can effectively enhance the safety and efficiency of maritime operations. However, the current prediction methods mainly focus on the motion time series forecasting without considering the uncertainty existing in measured motions. In this paper, a novel prediction method combined with the confidence interval forecasting of the motion is proposed. The method integrates the probability prediction module into the time-series prediction model. The normal distribution and student’s T-distribution are considered and the long short-term memory (LSTM) neural network is selected as the time-series prediction model. A set of measured full-scale ship roll motion of Yukun Ship is used to verify the prediction performance. The results demonstrate that the proposed method can effectively predict the confidence intervals of future ship motions, especially for extreme motions. This approach circumvents the issue of reduced accuracy over longer prediction periods, which is commonly existed in traditional time-series prediction models due to the influence of non-stationary characteristics of the data. Particularly, at the confidence level of 99 %, the prediction results could cover >90 % of the motion time series for future 12 s, which can significantly ensure the safety of offshore operations.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103946"},"PeriodicalIF":5.1,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven topology-fiber shape optimization method for CFRP-winding buckle arrestor based on MG-cGAN 基于MG-cGAN的cfrp绕扣避雷器数据驱动拓扑光纤形状优化方法

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-26 DOI: 10.1016/j.marstruc.2025.103947

Jianxing Yu , Zihang Jin , Yang Yu , Zhongzhen Sun , Ruilong Gao , Ruoke Sun

{"title":"Data-driven topology-fiber shape optimization method for CFRP-winding buckle arrestor based on MG-cGAN","authors":"Jianxing Yu , Zihang Jin , Yang Yu , Zhongzhen Sun , Ruilong Gao , Ruoke Sun","doi":"10.1016/j.marstruc.2025.103947","DOIUrl":"10.1016/j.marstruc.2025.103947","url":null,"abstract":"<div><div>To enhance the performance of deep-sea pipeline CFRP-winding buckle arrestors, this paper innovatively proposes a CFRP arrestor through joint topology-fiber shape optimization (TFSO). For the high cost of traditional joint optimization, a Multi-Generator conditional Generative Adversarial Network (MG-cGAN) is proposed to enable rapid TFSO prediction without iteration under limited high-cost TFSO dataset. Considering CFRP arrestor’s structural characteristics, the Bi-directional Evolutionary Structural Optimization (BESO) and Nondominated Sorting Genetic Algorithm III (NSGA-III) methods are sequentially employed for topology optimization (TO) and fiber shape optimization (FSO) to yield an improved structure form. Next, MG-cGAN method is used to construct a TFSO prediction model. In offline phase, TO and FSO prediction models are developed using Enhanced Structural Optimization Prediction Residual Network (ESOP-ResNet) based on single-form optimization results. In online phase, a TFSO prediction model is developed by combining TO and FSO predictions, with the model outputs treated as fake and limited serial TFSO results treated as real for adversarial training. Case studies demonstrate that the jointed optimized CFRP arrestor achieves a 25 % increase in arresting efficiency while reducing 40 % volume. Furthermore, MG-cGAN, coupled with ESOP-ResNet, significantly enhances optimization efficiency while maintaining high prediction accuracy, avoiding the substantial cost of constructing large TFSO result datasets.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103947"},"PeriodicalIF":5.1,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Probabilistic demand models and analytical fragility quantification for ship hulls under ultimate bending conditions 船体在极限弯曲条件下的概率需求模型和分析脆性量化

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-24 DOI: 10.1016/j.marstruc.2025.103944

Aws Idris, Mohamed Soliman

{"title":"Probabilistic demand models and analytical fragility quantification for ship hulls under ultimate bending conditions","authors":"Aws Idris, Mohamed Soliman","doi":"10.1016/j.marstruc.2025.103944","DOIUrl":"10.1016/j.marstruc.2025.103944","url":null,"abstract":"<div><div>Fragility analysis is a key performance assessment approach that quantifies the structural performance under a wide spectrum of possible hazard intensities. Fragility profiles can be established for a particular vessel using simulation techniques. However, simulation-based fragility assessment of ship hulls is computationally intensive, and its applicability is limited to the investigated vessel. In contrast, analytical fragility models provide a computationally efficient alternative allowing for wider applicability to cover a particular class of vessels. This paper proposes a novel framework for developing analytical fragility profiles for hulls of a specific vessel class considering ultimate bending conditions. The framework includes the development of probabilistic demand models needed to estimate the statistical characteristics of the engineering demand parameters based on the ship main particulars and hazard intensity measures. Nonlinear regression analysis, using constrained nonlinear optimization algorithms, is conducted to estimate the parameters of the proposed models. The framework is demonstrated on tankers, where probabilistic demand measures for five double-hull tankers are quantified while accounting for uncertainties in the applied loads and their combination factors. The capacity thresholds, representing the maximum demand a vessel can withstand before reaching a specific damage state, are then quantified probabilistically. Analytical fragility profiles are then established and validated against simulation-based fragility results obtained using artificial neural network-assisted finite element simulation. The results show that the developed probabilistic demand models can effectively estimate the statistical descriptors of the demand measure, and the established framework provides a highly computationally efficient alternative to simulation-based fragility assessment.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103944"},"PeriodicalIF":5.1,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Damage-based strength reduction factor for seismic design of structures subjected to offshore ground motions 基于损伤的强度折减系数在近海地震动结构抗震设计中的应用

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-23 DOI: 10.1016/j.marstruc.2025.103945

Bali Liu , Hao Tian , Jinjun Hu , Changhai Zhai

{"title":"Damage-based strength reduction factor for seismic design of structures subjected to offshore ground motions","authors":"Bali Liu , Hao Tian , Jinjun Hu , Changhai Zhai","doi":"10.1016/j.marstruc.2025.103945","DOIUrl":"10.1016/j.marstruc.2025.103945","url":null,"abstract":"<div><div>This paper focuses on damage-based strength reduction factor (SRF) of single-degree-of freedom (SDOF) systems subjected to an ensemble of 892 offshore ground-motion records from the Kyoshin network in the Japan Sagami Bay Region. Damage-based SRF spectra are statistically developed considering both the offshore ground-motion characteristics (such as seafloor stations, magnitude, epicentral distance, significant duration and mean period) and structural parameters (including initial period, damage level, postyield stiffness ratio, ultimate ductility factor and hysteretic behavior). The differences in damage-based SRF spectra under offshore and onshore ground-motion records are also investigated. The results showed that the effects caused by offshore ground motions on the estimation of damage-based SRF are negligible, while the influence caused by the ultimate ductility factor can reach up to approximately 50 %. Analytical estimates of damage-based SRFs for mean level, 10th percentile values and 90th percentile values in terms of period, damage index, and ultimate ductility factor are proposed for the aseismic design of offshore structures.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103945"},"PeriodicalIF":5.1,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study of bearing capacity and failure envelopes of SEPLA under combined loading 复合荷载作用下SEPLA的承载力及破坏包络研究

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-15 DOI: 10.1016/j.marstruc.2025.103938

Jiang Tao Yi , Zhi Hao Ye , Qian Qian Cheng , Chao Fan Liu , Yu Ping Li , Kai Yao , Si Yu Li , Tong Shen

{"title":"Study of bearing capacity and failure envelopes of SEPLA under combined loading","authors":"Jiang Tao Yi , Zhi Hao Ye , Qian Qian Cheng , Chao Fan Liu , Yu Ping Li , Kai Yao , Si Yu Li , Tong Shen","doi":"10.1016/j.marstruc.2025.103938","DOIUrl":"10.1016/j.marstruc.2025.103938","url":null,"abstract":"<div><div>The suction embedded plate anchor (SEPLA) has gained prominence as an effective anchoring solution for offshore floating platforms, owing to its precise installation capabilities and superior load-bearing efficiency. Most existing literature primarily focuses on SEPLA's uniaxial bearing capacities under vertical (V), horizontal (H), or moment (M) loading. However, during the keying process or under extreme environmental conditions, SEPLA is often subjected to complex combinations of vertical, horizontal, and moment (VHM) loads, which is the primary motivation for this study. Using the coupled Euler-Lagrange (CEL) method, this study conducts a comprehensive large deformation finite element analysis of SEPLA under various combinations of vertical, horizontal, and moment loads, both pairwise and simultaneously. The study aims to determine the failure envelopes for load-bearing capacity under different loading combinations. A parametric analysis of these failure envelopes under various combined loading planes is performed. The results show that the anchor embedment depth, even after normalization, significantly influences the shape of the failure envelope, while the effects of anchor shape and interfacial friction are largely eliminated through normalization. A closed-form equation is developed to approximate the three-dimensional failure surface that dictates SEPLA’s bearing capacities under combined VHM loading. The findings of this research contribute to expanding the database for plate anchor bearing capacity under combined loading and provide a rational framework for estimating SEPLA's load-bearing capacity in design applications.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103938"},"PeriodicalIF":5.1,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bearing capacity of helical pile group foundation in clay over silty sand 粉质砂上黏土螺旋桩群基础承载力研究

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-12 DOI: 10.1016/j.marstruc.2025.103941

Yuxuan Wu , Mi Zhou , Xiangfeng Guo , Xihong Zhang , Jinhui Li

{"title":"Bearing capacity of helical pile group foundation in clay over silty sand","authors":"Yuxuan Wu , Mi Zhou , Xiangfeng Guo , Xihong Zhang , Jinhui Li","doi":"10.1016/j.marstruc.2025.103941","DOIUrl":"10.1016/j.marstruc.2025.103941","url":null,"abstract":"<div><div>Recognized as a growing priority in offshore foundation engineering, helical piles demonstrate exceptional operational stability and lifecycle cost advantages, solidifying their role in modern marine infrastructure development. However, limited knowledge regarding the bearing capacity and failure mechanisms of helical pile group foundations under multi-directional loads in layered soils poses significant challenges for design and optimization of offshore wind platforms and other marine structures. This paper investigates the bearing capacity and failure mechanisms of the helical pile group foundation embedded in layered clay-over-silty-sand soil profiles using numerical simulation. The numerical model is validated against previously exhibiting published data before conducting a parameterized study. Key findings demonstrate that group configurations significantly enhance horizontal capacity compared to single piles, while clay-over-silty-sand stratification induces distinct delamination-type failure mechanisms of the soil around helical pile, contrasting with the global plastic flow observed in uniform clay. The study establishes the normalized bearing capacity envelopes for vertical-horizontal-moment (<em>VHM)</em> loading cases and provides algebraic equations to facilitate conservative design practices. These results offer valuable insights into optimizing the design of the helical pile group foundations for offshore wind platforms and other marine applications.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103941"},"PeriodicalIF":5.1,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A joint optimization by the combination of BPNN and NSGA-III for the polyester mooring system 基于BPNN和NSGA-III的聚脂系泊系统联合优化

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-12 DOI: 10.1016/j.marstruc.2025.103942

Fasuo Yan , Yuqing Du , Yuyang Wang , Wei Wang , Dagang Zhang

{"title":"A joint optimization by the combination of BPNN and NSGA-III for the polyester mooring system","authors":"Fasuo Yan , Yuqing Du , Yuyang Wang , Wei Wang , Dagang Zhang","doi":"10.1016/j.marstruc.2025.103942","DOIUrl":"10.1016/j.marstruc.2025.103942","url":null,"abstract":"<div><div>The design of a mooring system includes multiple variables such as the line’s span and number, orientation, segmentation, materials, counterweights, load conditions, and the requirements like dynamic performance, structural safety, and economic costs. Traditional optimization methods, relying on extensive analysis with professional tools, usually performed inefficiently after large scale computation and long-time post processing. In this study, a surrogate-assisted framework combining Back Propagation Neural Network (BPNN) models and the Non-dominated Sorting Genetic Algorithm III (NSGA-III) is proposed to the optimization of polyester mooring systems. An optimization model considering the common requirements of mooring system design was established and three independent surrogate models were developed for each objective among maximum tension, platform displacement and cable lines’ weight. Then, the NSGA-III was integrated with the surrogate models to select excellent combinations within the feasible sample space. The joint optimization by the combination of BPNN and NSGA-III was validated through a design case of polyester mooring system for a Floating Production Unit (FPU). As a result, it showed reliable prediction accuracy with errors below 5 % and time saving with 80 % less than normal operations. The results show that the proposed framework offers an efficient and accurate solution for mooring system optimization.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103942"},"PeriodicalIF":5.1,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ship bow impact force in head-on collision 船艏正面碰撞时的冲击力

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-12 DOI: 10.1016/j.marstruc.2025.103940

Shengming Zhang , Preben Terndrup Pedersen

引用次数: 0

Static load-bearing capacity of tubular K-joints reinforced with collar plates under axial loading 轴向载荷作用下带接箍板的k形管节点静承载力研究

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-11 DOI: 10.1016/j.marstruc.2025.103929

Hossein Nassiraei , Hamid Reza Chavoshi , Pooya Rezadoost

{"title":"Static load-bearing capacity of tubular K-joints reinforced with collar plates under axial loading","authors":"Hossein Nassiraei , Hamid Reza Chavoshi , Pooya Rezadoost","doi":"10.1016/j.marstruc.2025.103929","DOIUrl":"10.1016/j.marstruc.2025.103929","url":null,"abstract":"<div><div>This study investigates the static load-bearing performance of tubular K-joints (TKJs) reinforced with collar plates under axial loading. A detailed finite element model was developed incorporating 3D solid elements, weld geometry, contact nonlinearity, and both material and geometric nonlinear behavior. The model was validated against available experimental data, demonstrating excellent agreement. A comprehensive parametric study was then carried out on 128 tubular joints reinforced with collar plate (RTJs) to evaluate the influence of key dimensionless geometric parameters—such as brace-to-chord diameter ratio (<em>β</em>), chord slenderness ratio (<em>γ</em>), gap-to-chord diameter ratio (<em>ζ</em>), collar thickness ratio (<em>δ</em> = collar thickness to chord thickness), collar length ratio (<em>ω</em> = collar length to brace diameter), and brace inclination (<em>θ</em>)—on joint performance. Results show that the effectiveness of the reinforcement strongly dependent on geometry. Additionally, a nonlinear regression model based on yield volume theory was proposed to predict the reinforcement index (Φ), defined as the capacity ratio between RTJs and their unreinforced counterparts. The proposed formula provides a reliable tool for the design and evaluation of collar-reinforced tubular joints under axial loading.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103929"},"PeriodicalIF":5.1,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial neural network model to assist in design of ship stiffened plates considering ultimate strength 考虑极限强度的船舶加筋板设计中的人工神经网络模型

IF 5.1 2区工程技术

Marine Structures Pub Date : 2025-09-11 DOI: 10.1016/j.marstruc.2025.103939

Im-jun Ban , Sang-jin Oh , Minjoon Kim , Jeong-Hyeon Kim , Sung-chul Shin

{"title":"Artificial neural network model to assist in design of ship stiffened plates considering ultimate strength","authors":"Im-jun Ban , Sang-jin Oh , Minjoon Kim , Jeong-Hyeon Kim , Sung-chul Shin","doi":"10.1016/j.marstruc.2025.103939","DOIUrl":"10.1016/j.marstruc.2025.103939","url":null,"abstract":"<div><div>The ship structure is exposed to combined loading conditions during operational exposure to waves due to the hull weight, cargo weight, and other loads. Because the primary structural members of the ship structure are stiffened plates, securing structural safety during the ship design stage is critical. However, in the current design method, the results are inaccurate and inefficient in terms of the required time or cost owing to the poor preparation of the physical model or assumptions regarding the boundary conditions. To resolve this, the present study performs a structural analysis on 3000 stiffened plates with included initial imperfections and subjected to axial compression, which causes the buckling loads on the ship. Deep learning database is constructed based on the finite element analysis results. Then, deep learning model is developed to propose an effective method for predicting the ultimate strength of the stiffened plates. The prediction results of the deep learning method showed similarity with the FE analysis results. During the initial design stage, the structural designer can use this model to determine the geometrical properties of the stiffened plate within a reasonable time and cost. In addition, these results can potentially be used in the reverse engineering of vessels.</div></div>","PeriodicalId":49879,"journal":{"name":"Marine Structures","volume":"106 ","pages":"Article 103939"},"PeriodicalIF":5.1,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145046687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0