Applied Ocean Research最新文献_第4页

Adaptive informative path planning for active reconstruction of spatio-temporal water pollution dispersion using Unmanned Surface Vehicles

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-14 DOI: 10.1016/j.apor.2025.104458

Song Ma , Cunjia Liu , Christopher M. Harvey , Richard Bucknall , Yuanchang Liu

Real-time pollution monitoring is critical for marine environmental management, where accurate tracking and reconstruction of pollutant dispersion are essential to mitigate ecological impacts. This paper introduces an adaptive informative path planning (IPP) framework designed to address the challenges of reconstructing spatio-temporally varying dynamic environments, focusing on pollutant dispersion in marine environments. The framework combines a Finite Element Analysis (FEA)-based pollutant dispersion model with a recursive Bayesian estimator to capture spatio-temporal dynamics in complex marine environments accurately. Two information-based utility functions are developed to quantify and reduce system state uncertainty, enabling more effective and targeted data collection by Unmanned Surface Vehicles (USVs). Monte Carlo Tree Search (MCTS)-based path planning strategies are employed in the proposed framework with thorough comparative studies against the myopic path planning methods. The proposed framework is rigorously evaluated across three scenarios, investigating its performance under different starting positions and pollutant source terms. The testing scenarios, which reflects real-world conditions such as oil spills and chemical leaks, help assess the robustness and adaptability of the framework. A sensitivity analysis is conducted to guide the fine tuning of the path planning strategy. Comparative studies highlight the superior performance of the proposed framework, with the combination of expected information gain (EIG)-based utility and MCTS consistently achieving the lowest reconstruction error and demonstrating enhanced robustness in dynamic and uncertain environments. These results establish the framework as a significant advancement in autonomous environmental monitoring, offering a new solution for dynamic pollution tracking and management.

{"title":"Adaptive informative path planning for active reconstruction of spatio-temporal water pollution dispersion using Unmanned Surface Vehicles","authors":"Song Ma , Cunjia Liu , Christopher M. Harvey , Richard Bucknall , Yuanchang Liu","doi":"10.1016/j.apor.2025.104458","DOIUrl":"10.1016/j.apor.2025.104458","url":null,"abstract":"<div><div>Real-time pollution monitoring is critical for marine environmental management, where accurate tracking and reconstruction of pollutant dispersion are essential to mitigate ecological impacts. This paper introduces an adaptive informative path planning (IPP) framework designed to address the challenges of reconstructing spatio-temporally varying dynamic environments, focusing on pollutant dispersion in marine environments. The framework combines a Finite Element Analysis (FEA)-based pollutant dispersion model with a recursive Bayesian estimator to capture spatio-temporal dynamics in complex marine environments accurately. Two information-based utility functions are developed to quantify and reduce system state uncertainty, enabling more effective and targeted data collection by Unmanned Surface Vehicles (USVs). Monte Carlo Tree Search (MCTS)-based path planning strategies are employed in the proposed framework with thorough comparative studies against the myopic path planning methods. The proposed framework is rigorously evaluated across three scenarios, investigating its performance under different starting positions and pollutant source terms. The testing scenarios, which reflects real-world conditions such as oil spills and chemical leaks, help assess the robustness and adaptability of the framework. A sensitivity analysis is conducted to guide the fine tuning of the path planning strategy. Comparative studies highlight the superior performance of the proposed framework, with the combination of expected information gain (EIG)-based utility and MCTS consistently achieving the lowest reconstruction error and demonstrating enhanced robustness in dynamic and uncertain environments. These results establish the framework as a significant advancement in autonomous environmental monitoring, offering a new solution for dynamic pollution tracking and management.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"156 ","pages":"Article 104458"},"PeriodicalIF":4.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419348","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}

引用次数: 0

A hybrid strategy for numerical simulations of fluid-structure interaction problems in ocean engineering

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104433

Xin Liao, Chan Ghee Koh, Yean Khow Chow

A hybrid strategy combining the advantages of the meshless Consistent Particle Method (CPM) and the mesh-based Finite Element Method (FEM) is proposed in this paper to solve fluid-structure interaction problems. Water is modelled by CPM, whereas deformable structure is solved by FEM. Unlike some traditional particle methods that require a kernel function in computing spatial derivatives, CPM utilizes Taylor series expansion and avoids the use of artificial values of physical parameters (such as artificial viscosity and sound speed). The interaction between water and structure is achieved by a partitioned approach for its flexibility and ease of implementation. To ensure compatibility between CPM and FEM solutions at the fluid-structure interface, an iteration scheme of enforcing pressure Poisson equation (PPE) is proposed. The accuracy and stability of the proposed hybrid strategy are validated through three benchmark examples: water column on an elastic plate, sloshing of sunflower oil interacting with an elastic baffle, and a dam break with an elastic gate. Comparisons between CPM-FEM results with published experimental and numerical results demonstrate the effectiveness and advantages of the proposed hybrid strategy.

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引用次数: 0

Numerical study of lateral soil resistance to pipe movement in sandy slopes

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104419

Hongkuan Yang , Lizhong Wang , Zhenming Lei , Shengjie Rui , Zhenyu Liu , Zhen Guo

The lateral pipe-soil interaction in sloping ground is numerically simulated, with a modified Mohr-Coulomb model adopted to capture the state-dependent behavior of dense sand. The numerical model is first validated by previous physical tests in level ground. Then, both peak and residual lateral resistance are investigated in nonpositive slopes (pipeline moves relatively outwards the slope), while only the former is focused in opposite cases. The effects of burial depth ratio, interface roughness and slope angle on soil resistances are specially discussed. It is found that in terms of the failure mechanisms, increasing the slope angle implies to some extent an increase of burial depth ratio in level ground. A positive slope usually provides higher soil resistance than a negative slope for a given burial depth ratio as the normalized normal pipe-soil contact stress on the pulling side increases with the slope angle. The difference in peak resistance between the perfectly smooth and generally rough pipeline is amplified in positive slopes, which is associated with the transition of the failure mechanisms. Finally, a preliminary methodology to evaluate the soil resistances in sloping ground is presented, based on the improved implicit limit equilibrium method for level ground and newly proposed slope effect coefficients.

{"title":"Numerical study of lateral soil resistance to pipe movement in sandy slopes","authors":"Hongkuan Yang , Lizhong Wang , Zhenming Lei , Shengjie Rui , Zhenyu Liu , Zhen Guo","doi":"10.1016/j.apor.2025.104419","DOIUrl":"10.1016/j.apor.2025.104419","url":null,"abstract":"<div><div>The lateral pipe-soil interaction in sloping ground is numerically simulated, with a modified Mohr-Coulomb model adopted to capture the state-dependent behavior of dense sand. The numerical model is first validated by previous physical tests in level ground. Then, both peak and residual lateral resistance are investigated in nonpositive slopes (pipeline moves relatively outwards the slope), while only the former is focused in opposite cases. The effects of burial depth ratio, interface roughness and slope angle on soil resistances are specially discussed. It is found that in terms of the failure mechanisms, increasing the slope angle implies to some extent an increase of burial depth ratio in level ground. A positive slope usually provides higher soil resistance than a negative slope for a given burial depth ratio as the normalized normal pipe-soil contact stress on the pulling side increases with the slope angle. The difference in peak resistance between the perfectly smooth and generally rough pipeline is amplified in positive slopes, which is associated with the transition of the failure mechanisms. Finally, a preliminary methodology to evaluate the soil resistances in sloping ground is presented, based on the improved implicit limit equilibrium method for level ground and newly proposed slope effect coefficients.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"155 ","pages":"Article 104419"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176386","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}

引用次数: 0

Wave (from) polarized light learning (WPLL) method: High resolution spatio-temporal measurements of water surface waves in laboratory setups

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104457

Noam Ginio , Michael Lindenbaum , Barak Fishbain , Dan Liberzon

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address this challenge, we propose the Wave (from) Polarized Light Learning (WPLL), a learning based remote sensing method for laboratory implementation, capable of inferring surface elevation and slope maps in high resolution. The method uses the polarization properties of the light reflected from the water surface. The WPLL uses a deep neural network (DNN) model that approximates the water surface slopes from the polarized light intensities. Once trained on simple monochromatic wave trains, the WPLL is capable of producing high-resolution reconstruction of the 2D water surface slopes and elevation in a variety of irregular wave fields. The method's robustness is demonstrated by showcasing its high wavenumber/frequency response, its ability to reconstruct wave fields propagating in arbitrary angles relative to the camera optical axis, and its computational efficiency. This developed methodology is a cost-effective near-real time remote sensing tool for laboratory water surface waves measurements, setting the path for upscaling to open sea application for research, monitoring, and short-time forecasting.

{"title":"Wave (from) polarized light learning (WPLL) method: High resolution spatio-temporal measurements of water surface waves in laboratory setups","authors":"Noam Ginio , Michael Lindenbaum , Barak Fishbain , Dan Liberzon","doi":"10.1016/j.apor.2025.104457","DOIUrl":"10.1016/j.apor.2025.104457","url":null,"abstract":"<div><div>Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address this challenge, we propose the Wave (from) Polarized Light Learning (WPLL), a learning based remote sensing method for laboratory implementation, capable of inferring surface elevation and slope maps in high resolution. The method uses the polarization properties of the light reflected from the water surface. The WPLL uses a deep neural network (DNN) model that approximates the water surface slopes from the polarized light intensities. Once trained on simple monochromatic wave trains, the WPLL is capable of producing high-resolution reconstruction of the 2D water surface slopes and elevation in a variety of irregular wave fields. The method's robustness is demonstrated by showcasing its high wavenumber/frequency response, its ability to reconstruct wave fields propagating in arbitrary angles relative to the camera optical axis, and its computational efficiency. This developed methodology is a cost-effective near-real time remote sensing tool for laboratory water surface waves measurements, setting the path for upscaling to open sea application for research, monitoring, and short-time forecasting.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"155 ","pages":"Article 104457"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378953","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}

引用次数: 0

Full-scale field investigations and numerical analyses of grouting effect for large-diameter steel-concrete composite piles in offshore wind turbines

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104437

Lin-fang Xu , Zhi-hui Wan , Guo-liang Dai , Tao Hu , Feng Zhou , Chun-hui Bao

The bearing behaviors of post-grouted piles for offshore wind turbines are significantly affected by the grouting effect, especially in heavily weathered granite, which has attracted considerable attention in the academic community. This paper presents field static load tests on a large-diameter steel-concrete composite pile for offshore wind turbine foundations in deeply weathered granite formations. The influence of combined end-and-side grouting on the bearing behaviors of large-diameter steel-concrete composite piles in heavily weathered granite was thoroughly investigated through core drilling and CT scanning. Furthermore, numerical simulations were employed to conduct a parametric analysis of the combined post-grouting of large-diameter steel-concrete composite piles in heavily weathered granite formations, systematically studying the influence of grouting pressure and grouting volume on the bearing properties of post-grouted piles. The results indicated that compared to that before combined grouting, the bearing capacity of large-diameter steel-concrete piles is effectively enhanced after combined grouting. Core drilling clearly revealed the distribution of cement grout around and below the pile, indicating that the influence range of cement grout in heavily weathered granite formations extends from 0.5D below the pile tip to 5.3D above the pile tip. CT scanning results confirmed that cement grout could form cementation in heavily weathered granite, validating the effectiveness of combined post-grouting in such formations. The findings can serve as a reference for evaluating the grouting effect of post-grouted piles and contribute to advancing the application of post-grouted piles in heavily weathered rock formations.

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引用次数: 0

Flow memory effect on viscous hydrodynamic loads of a remotely operated vehicle undergoing drift motions

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104461

Ruinan Guo , Yingfei Zan , Duanfeng Han , Zhongming Li , Fuxiang Huang , Yaogang Sun , Nan Sun

The hydrodynamic loads on a remotely operated vehicle (ROV) undergoing oblique motions are studied experimentally and numerically. A novel convolution-based method for calculating the flow memory effect response function of the viscous hydrodynamic loads is presented. The nonlinear effect of the drift angle on the hydrodynamic loads is investigated through steady drift tests, and the flow separation that occurs around the ROV is measured using the Reynolds-averaged Navier–Stokes (RANS) turbulence model. The effect of coupling longitudinal and lateral velocities is examined using frequency analysis of the loads measured in impulse motion response tests. By analyzing the hysteresis loops of the hydrodynamic loads in one apparent period, the flow memory effect is identified, whereby the ROV has two different hydrodynamic force magnitudes when it reaches the same speed at different times in one period. The existence of the flow memory effect associated with hydrodynamic loads is explained by the response functions. All convolutions related to the longitudinal, lateral, and coupling velocity at the beginning of the motion contribute to the memory effect. When the ROV drifts stably, the memory effect is solely induced by the convolution related to the coupling velocity.

{"title":"Flow memory effect on viscous hydrodynamic loads of a remotely operated vehicle undergoing drift motions","authors":"Ruinan Guo , Yingfei Zan , Duanfeng Han , Zhongming Li , Fuxiang Huang , Yaogang Sun , Nan Sun","doi":"10.1016/j.apor.2025.104461","DOIUrl":"10.1016/j.apor.2025.104461","url":null,"abstract":"<div><div>The hydrodynamic loads on a remotely operated vehicle (ROV) undergoing oblique motions are studied experimentally and numerically. A novel convolution-based method for calculating the flow memory effect response function of the viscous hydrodynamic loads is presented. The nonlinear effect of the drift angle on the hydrodynamic loads is investigated through steady drift tests, and the flow separation that occurs around the ROV is measured using the Reynolds-averaged Navier–Stokes (RANS) turbulence model. The effect of coupling longitudinal and lateral velocities is examined using frequency analysis of the loads measured in impulse motion response tests. By analyzing the hysteresis loops of the hydrodynamic loads in one apparent period, the flow memory effect is identified, whereby the ROV has two different hydrodynamic force magnitudes when it reaches the same speed at different times in one period. The existence of the flow memory effect associated with hydrodynamic loads is explained by the response functions. All convolutions related to the longitudinal, lateral, and coupling velocity at the beginning of the motion contribute to the memory effect. When the ROV drifts stably, the memory effect is solely induced by the convolution related to the coupling velocity.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"155 ","pages":"Article 104461"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388275","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}

引用次数: 0

Submarine pipeline corrosion rate prediction model based on high-dimensional mapping augmentation and residual update gradient forest

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104432

Hongbing Liu , Zhenhao Zhu , Jingyang Zhang , Qiushuang Zheng , Ankui Xie , Xianqiang Qu

Pipelines play a crucial role in the transportation of oil and gas, corrosion is a prevalent issue in submarine pipelines, and accurately predicting the corrosion rate is crucial for ensuring their safe operation. In light of the challenges posed by the scarcity and imbalance of corrosion data samples, this study develops a data-driven hybrid model for pipeline corrosion prediction. Firstly, grey relational analysis is employed to validate the nonlinear relationship between corrosion factors and corrosion rate. Subsequently, this study innovatively combines Kernel Principal Component Analysis (KPCA) with Variational Autoencoder (VAE) to capture the nonlinear relationships within the data and augment the sample size. The proposed Residual Update Gradient Forest (RUGF) model is then utilized to predict the augmented data. Finally, through SHapley Additive exPlanations (SHAP) and Fourier Amplitude Sensitivity Test (FAST), this study demonstrates that the model effectively identifies key principal components and provides explanations for the prediction results. Case studies reveal that the proposed model exhibits robust generalization capabilities and significantly outperforms classical regression algorithms, achieving highly accurate predictions of corrosion rate in Submarine pipeline.

{"title":"Submarine pipeline corrosion rate prediction model based on high-dimensional mapping augmentation and residual update gradient forest","authors":"Hongbing Liu , Zhenhao Zhu , Jingyang Zhang , Qiushuang Zheng , Ankui Xie , Xianqiang Qu","doi":"10.1016/j.apor.2025.104432","DOIUrl":"10.1016/j.apor.2025.104432","url":null,"abstract":"<div><div>Pipelines play a crucial role in the transportation of oil and gas, corrosion is a prevalent issue in submarine pipelines, and accurately predicting the corrosion rate is crucial for ensuring their safe operation. In light of the challenges posed by the scarcity and imbalance of corrosion data samples, this study develops a data-driven hybrid model for pipeline corrosion prediction. Firstly, grey relational analysis is employed to validate the nonlinear relationship between corrosion factors and corrosion rate. Subsequently, this study innovatively combines Kernel Principal Component Analysis (KPCA) with Variational Autoencoder (VAE) to capture the nonlinear relationships within the data and augment the sample size. The proposed Residual Update Gradient Forest (RUGF) model is then utilized to predict the augmented data. Finally, through SHapley Additive exPlanations (SHAP) and Fourier Amplitude Sensitivity Test (FAST), this study demonstrates that the model effectively identifies key principal components and provides explanations for the prediction results. Case studies reveal that the proposed model exhibits robust generalization capabilities and significantly outperforms classical regression algorithms, achieving highly accurate predictions of corrosion rate in Submarine pipeline.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"155 ","pages":"Article 104432"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176769","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}

引用次数: 0

A physics-based model for clear-water scour development around a pile foundation in clayey soils

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104436

Pei-Qing Zhao , Wen-Gang Qi , Bo Liu , Fu-Ping Gao

Significant advancements have been made in understanding local scour around pile foundations in non-cohesive soils; however, the scour phenomenon in clay soils remains relatively unexplored. Existing formulas for predicting scour development in clay soils around pile foundations often rely on empirical fittings to experimental data, rendering them limited by specific experiment conditions and prone to scale effects. To address this gap, this study proposes a physics-based model for clear-water scour development around a pile foundation in clay soils under both steady and unsteady flow conditions. By integrating a scaling expression for shear stress based on the phenomenological theory of turbulence (PTT) and incorporating a general sediment transport model, an ordinary differential equation (ODE) is derived to characterize the temporal variation in scour depth following the principle of sediment mass conservation. This ODE inherently considers all significant dimensional parameters influencing the scouring process, thereby effectively addressing potential scale-related issues. The predictions of the analytical solutions for the proposed ODE closely align with previously observed scour depth development curves around pile foundations in clay soils. Additionally, the model can be applied to scenarios with unsteady flow velocities, such as waterway floods and tidal currents.

{"title":"A physics-based model for clear-water scour development around a pile foundation in clayey soils","authors":"Pei-Qing Zhao , Wen-Gang Qi , Bo Liu , Fu-Ping Gao","doi":"10.1016/j.apor.2025.104436","DOIUrl":"10.1016/j.apor.2025.104436","url":null,"abstract":"<div><div>Significant advancements have been made in understanding local scour around pile foundations in non-cohesive soils; however, the scour phenomenon in clay soils remains relatively unexplored. Existing formulas for predicting scour development in clay soils around pile foundations often rely on empirical fittings to experimental data, rendering them limited by specific experiment conditions and prone to scale effects. To address this gap, this study proposes a physics-based model for clear-water scour development around a pile foundation in clay soils under both steady and unsteady flow conditions. By integrating a scaling expression for shear stress based on the phenomenological theory of turbulence (PTT) and incorporating a general sediment transport model, an ordinary differential equation (ODE) is derived to characterize the temporal variation in scour depth following the principle of sediment mass conservation. This ODE inherently considers all significant dimensional parameters influencing the scouring process, thereby effectively addressing potential scale-related issues. The predictions of the analytical solutions for the proposed ODE closely align with previously observed scour depth development curves around pile foundations in clay soils. Additionally, the model can be applied to scenarios with unsteady flow velocities, such as waterway floods and tidal currents.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"155 ","pages":"Article 104436"},"PeriodicalIF":4.3,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176757","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}

引用次数: 0

Reduced order modeling of wave energy systems via sequential Bayesian experimental design and machine learning

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104439

Eirini Katsidoniotaki , Stephen Guth , Malin Göteman , Themistoklis P. Sapsis

Marine energy technologies face significant challenges in ensuring their survivability under extreme ocean conditions. Quantifying extreme load statistics on marine energy structures is essential for reliable structural design; however, this is a challenging task due to the scarcity of high-quality data and the inherent uncertainties associated with predicting rare events. While computational fluid dynamics (CFD) simulations can accurately capture the nonlinear dynamics and loads in extreme wave–structure interactions, providing high-fidelity data, extracting statistical information through these models is computationally impractical. This study proposes a reduced-order modeling framework for marine energy systems, enabling efficient analysis across diverse scenarios, and facilitating the quantification of extreme load statistics with significantly reduced computational cost. Specifically, a hybrid reduced-order or surrogate model for a wave energy converter is developed to map extreme sea states and design parameters to the resulting loads in the mooring system. The term ”hybrid” refers to the combination of Gaussian Process Regression (GPR) and Long Short-Term Memory (LSTM) neural networks. The model is developed using two distinct approaches: (1) a baseline approach that relies on existing CFD data for training and validation, and (2) an active learning approach that strategically selects the most informative CFD samples from regions of the input space associated with extreme mooring loads. This procedure iteratively refines the model while minimizing prediction uncertainty, making it particularly effective for real-world applications where obtaining each sample requires substantial time and resources. The developed model demonstrates its exceptional ability to efficiently predict complex load time series, including instantaneous peaks, at speeds significantly faster than traditional modeling methods. Subsequently, the model is utilized to effectively evaluate Monte Carlo samples, providing accurate estimates of the probability of extreme mooring loads. Understanding the expected extreme loads is essential during the design phase of marine energy systems, enabling cost reduction by optimizing strength margins, refining overly conservative safety factors, and enhancing overall system reliability.

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引用次数: 0

Cooperative event-triggered control for the multi-USVs via the formation reconstruction

IF 4.3 2区工程技术 Q1 ENGINEERING, OCEAN

Applied Ocean Research

Pub Date : 2025-02-01 DOI: 10.1016/j.apor.2025.104440

Guoqing Zhang , Chengqian Shi , Jiqiang Li , Xianku Zhang

In this paper, a robust neural cooperative path following control algorithm is designed for multi-unmanned surface vehicles (USVs) to address the problems of the wreck avoidance by an utilization of the formation reconstruction mechanism and event-triggered rule. For this purpose, an artificial potential field (APF) guidance principle is developed, where can guide a local avoidance obstacle effect without affecting the global path following operation by designing a formation reconstruction mechanism. The major feature is that the problems of the local minimum and unattainable destination for the traditional APF are settled by presenting a velocity coordination strategy, ensuring a cooperative performance of the USVs while encountering the wreck obstacles. For the control module, a novel dynamic event-triggered rule is proposed by introducing a feedback function of output error, which can avoid the restriction of the fixed threshold parameters. Owning to this merit, the actuation frequency of the control law and adaptive neural parameter is reduced for saving a limited transmission resource usage. Further, the actuator failures caused by the potential factors, see for example saturation, delay and hysteresis are discussed by employing the two adaptive law, where the unknown gain-functions are free.

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引用次数: 0