Hydrodynamics for Subsea Systems

Tong, Feifei; Griffiths, Terry

doi:10.1007/978-981-10-6946-8_235

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The numerical models, including mesh setting and convergence tests, have been validated extensively to match the hydrodynamic forces with the physical testing in UWA's Large O-tube and published results by 3-D numerical simulations. These have been conducted for flow around sphere and cylinders, and some of these outcomes are reported in other publications including [13].…”

Section: Numerical Modelmentioning

confidence: 99%

Research updates on filter units for secondary stabilisation of offshore wind farm power cables

Pistani,

Griffits,

et al. 2024

J. Phys.: Conf. Ser.

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This paper presents an experimental and numerical campaign that was carried out to improve the understanding of the performances of filter units, or rock bags, when used as mean of secondary stabilisation for subsea power cables in offshore wind farms. The main parameters of influence are discussed. The capabilities of the experimental facility are presented as well as the experimental approach with a description of the cases tested. The numerical models are also described. Finally some of the findings about the main mechanisms of instability are presented.

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Section: Numerical Modelmentioning

confidence: 99%

Research updates on filter units for secondary stabilisation of offshore wind farm power cables

Pistani,

Griffits,

et al. 2024

J. Phys.: Conf. Ser.

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“…Underwater circumstances exhibit dynamic behaviors, characterized by the presence of quickly fluctuating conditions, including underwater currents, tides, and object maneuverings. In this situation, the adaptable nature of KF and its nonlinear versions is essential [16]. One of the primary constraints associated with the EKF and UKF methodologies is their underlying assumption of linearity.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Bayesian regularization backpropagation neuro computing paradigm for state features estimation of underwater passive object

Ali,

Bilal,

Alharbi

et al. 2024

Front. Phys.

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In underwater environments, the accurate estimation of state features for passive object is a critical aspect of various applications, including underwater robotics, surveillance, and environmental monitoring. This study presents an innovative neuro computing approach for instantaneous state features reckoning of passive marine object following dynamic Markov chains. This paper introduces the potential of intelligent Bayesian regularization backpropagation neuro computing (IBRBNC) for the precise estimation of state features of underwater passive object. The proposed paradigm combines the power of artificial neural network with Bayesian regularization technique to address the challenges associated with noisy and limited underwater sensor data. The IBRBNC paradigm leverages deep neural networks with a focus on backpropagation to model complex relationships in the underwater environment. Furthermore, Bayesian regularization is introduced to incorporate prior knowledge and mitigate overfitting, enhancing the model’s robustness and generalization capabilities. This dual approach results in a highly adaptive and intelligent system capable of accurately estimating the state features of passive object in real-time. To evaluate the efficacy of this intelligent computing approach, a controlled supervised maneuvering trajectory for underwater passive object is constructed. Real-time estimations of location, velocity, and turn rate for dynamic target are scrutinized across five distinct scenarios by varying the Gaussian observed noise’s standard deviation, aiming to minimize mean square errors (MSEs) between real and estimated values. The effectiveness of the proposed IBRBNC paradigm is demonstrated through extensive simulations and experimental trials. Results showcase its superiority over traditional nonlinear filtering methods like interacting multiple model extended Kalman filter (IMMEKF) and interacting multiple model unscented Kalman filter (IMMUKF), especially in the presence of noise, incomplete measurements and sparse data.

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Evolution Trends and Future Prospects in Artificial Marine Reef Research: A 28-Year Bibliometric Analysis

Bao,

Nikolaeva,

Xia

et al. 2024

Sustainability

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Under growing recognition of the need to restore marine ecosystems and promote the sustainable use of ocean resources, this research delves into an analysis of studies on artificial reefs in the marine environment spanning from 1996 to 2024 to explore how they have evolved in supporting biodiversity growth and fishery management while also promoting ecosystem sustainability over time. Using tools like CiteSpace 6.3. R1 and VOSviewer 1.6.18, a total of 586 research publications were examined to pinpoint authors, current trends in research, and emerging focal points. This study highlights the roles played by countries such as the United States, China, and Australia, as well as esteemed institutions, like NOAA and the Chinese Academy of Fisheries Sciences leading the field. In this field of study, there are topics like restoring the environment to its natural state and making fisheries more sustainable by creating habitats with diverse structures and elements; this shows how artificial reef research involves different areas of expertise working together for a common goal. The findings suggest a trend towards using tools such as ecofriendly materials and 3D printing to improve the design and ecological functionality of reefs. However, some challenges still exist, such as conducting assessments on the long-term effects on the environment and finding a balance between promoting biodiversity and meeting the needs of people in terms of economic aspects. This research highlights the importance of countries working together and adapting their strategies to ensure that artificial reefs play a role in protecting marine life and using ocean resources in a sustainable way. By charting out the existing knowledge landscape, this study lays the groundwork for research endeavors focused on tackling these obstacles and propelling the field forward.

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Hydrodynamics for Subsea Systems

Cited by 3 publications

References 14 publications

Research updates on filter units for secondary stabilisation of offshore wind farm power cables

Research updates on filter units for secondary stabilisation of offshore wind farm power cables

Intelligent Bayesian regularization backpropagation neuro computing paradigm for state features estimation of underwater passive object

Evolution Trends and Future Prospects in Artificial Marine Reef Research: A 28-Year Bibliometric Analysis

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