A crucial component for unmanned underwater vehicles (UUVs), including remotely operated vehicles (ROVs) and autonomous underwater vehicles (AUVs), are the thrusters, which, in addition, are sensitive to damage during operations in harsh environments. This paper presents a study on the impact of incipient faults on the performance of thruster propellers used in offshore operations. The study evaluates the reduction in propeller performance due to wear and tear under realistic working conditions. The study employs a combination of experimental data analysis and signal processing techniques, including fast Fourier transforms and harmonics analysis, to identify faults and assess their severity. The results show that worn propellers can be identified through 5th-order harmonics and rotational velocity changes. The paper concludes with a proposal for future research using a model-based approach to enhance fault detection capabilities further.
Simulating the free decay motion and wave radiation from a heaving semi-submerged sphere poses significant computational challenges due to its three-dimensional complexity. By leveraging axisymmetry, we reduce the problem to a two-dimensional simulation, significantly decreasing computational demands while maintaining accuracy. In this paper, we exploit axisymmetry to perform a large ensemble of Computational Fluid Dynamics (CFDs) simulations, aiming to evaluate and maximize both accuracy and efficiency, using the Reynolds Averaged Navier–Stokes (RANS) solver interFOAM, in the opensource finite volume CFD software OpenFOAM. Validated against highly accurate experimental data, extensive parametric studies are conducted, previously limited by computational constraints, which facilitate the refinement of simulation setups. More than 50 iterations of the same heaving sphere simulation are performed, informing efficient trade-offs between computational cost and accuracy across various simulation parameters and mesh configurations. Ultimately, by employing axisymmetry, this research contributes to the development of more accurate and efficient numerical modeling in ocean engineering.
We present a hybrid linear potential flow - machine learning (LPF-ML) model for simulating weakly nonlinear wave-body interaction problems. In this paper we focus on using hierarchical modeling for generating training data to be used with recurrent neural networks (RNNs) in order to derive nonlinear correction forces. Three different approaches are investigated: (i) a baseline method where data from a Reynolds averaged Navier Stokes (RANS) model is directly linked to data from an LPF model to generate nonlinear corrections; (ii) an approach in which we start from high-fidelity RANS simulations and build the nonlinear corrections by stepping down in the fidelity hierarchy; and (iii) a method starting from low-fidelity, successively moving up the fidelity staircase. The three approaches are evaluated for the simple test case of a heaving sphere. The results show that the baseline model performs best, as expected for this simple test case. Stepping up in the fidelity hierarchy very easily introduces errors that propagate through the hierarchical modeling via the correction forces. The baseline method was found to accurately predict the motion of the heaving sphere. The hierarchical approaches struggled with the task, with the approach that steps down in fidelity performing somewhat better of the two.
Physical wave basin tests with a focus on uncertainty estimation have been conducted on a fixed sphere subjected to wave loads at Aalborg University as part of the effort of the OES Wave Energy Converters Modeling Verification and Validation (formerly, OES Task 10) working group to increase credibility of numerical modeling of WECs.
The present note defines an idealized test case formulated to accurately represent the physical tests in a simple way. The test case consists of a fixed, rigid sphere half submerged in water subjected to regular waves of three different levels of linearity. The objective of the present note is to allow for numerical tests of the idealized test case.
From the process control point of view, any reliable and online Oil-in-Water (OiW) measurement could provoke a brand new control paradigm for produced water treatment. However, the real-time OiW monitoring is still an open and ad-hoc situation in recent decades. The fundamental issue, ie, the OiW measurement is methodology dependent, leads to numerous challenges, such as (i) how to verify the reliability and accuracy of a specific methodology/instrument; (ii) how to handle and interpret the measured data in a most objective manner; and (iii) how to keep a cost-effective on-site calibration and maintenance under the harsh offshore conditions etc. The paper reports our latest achievements and observations in usage of fluorescence- and microscopybased OiW monitoring technologies for advanced Produced Water Treatment (PWT) control and evaluation, particularly by focusing on the de-oiling hydrocyclone installations.
Climate change is affecting the oceans with increased sea levels, ocean acidification and extreme weather affecting coastal ecosystems. This necessitates a new model for climate and marine law, because existing law and policy are insufficient to tackle adaptation and mitigation impacts upon the marine environment. Presently, we do not know what it takes to integrate and balance climate legislation and governance when faced with unknown problems. The concept of Blue Economy is new and originates from the United Nations Conference on Sustainable Development. This chapter explores how one can best build new knowledge that can integrate climate law and marine governance. It does so by proposing the creation of a nexus between ecosystem-based regulations and marine spatial planning in order to create a new paradigm for effective and inclusive Blue Economy, using a systemic multi-regulatory framework (Global, Regional and National).
The project "IEA OES Task 10 Phase III - WEC Modelling" is a publicly-funded research project under the Danish Energy Agency EUDP grant with Journal no. 134232-510153. As part of the initial period of the project, a selection of three test cases has been defined under WP2. The present report forms the deliverable for Milestone "M1: Case studies defined".
This work presents the verification and validation of the freely available simulation tool MoodyMarine, developed to help meet some of the demands for early stage development of MRE devices. MoodyMarine extends the previously released mooring module MoodyCore (Discontinuous Galerkin Finite Elements) with linear radiation-diffraction bodies, integrated pre-processing workflows and a graphical user interface. It is a C++ implementation of finite element mooring dynamics and Cummins equations for floating bodies with weak nonlinear corrections. A newly developed nonlinear Froude-Krylov implementation is verified in the paper, and MoodyMarine is compared to CFD simulations for two complex structures: a slack-moored floating offshore wind turbine and a self-reacting point-absorber with hybrid mooring.
Savonius hydrokinetic turbines (SHTs), categorized as emerging cyclic-type wave energy converters (WECs), have demonstrated notable potential in achieving elevated energy conversion efficiency and consistent power output. This performance is particularly observed when operating under the initial phase-locked strategy (IPLS), marking a significant advancement in the realm of wave energy harvesting. However, a thorough exploration of the influences stemming from wave conditions and turbine design remains an area that warrants further investigation for advancing the performance of SHT-WECs under the proper operational strategy. This study undertakes an exhaustive analysis of geometric parameters, encompassing turbine diameter, blade number, and thickness. An experiment-validated numerical model based on the unsteady two-phase Reynolds-averaged Navier-Stokes equations is adopted in the research. Comprehensive investigations include analyzes of flow fields around the turbine, pressure distributions on blade surfaces, and dynamic torque variations. These analyzes serve to elucidate the variation rules of hydrodynamic characteristics and their influential mechanisms. The results highlight the notable impact of the proposed "relative-short wavelength impact" on the performance of SHT-WECs operating under IPLS conditions. Notably, no significant impact is observed when the relative wavelength exceeds 17. Optimal performance is achieved with the thinnest and two-bladed turbine configuration. Moreover, optimizing the turbine diameter significantly enhances SHT-WEC conversion efficiency, with the attained maximum value reaching approximately 18.6%. This study offers a concise guideline for designing turbine diameters in alignment with specific wave conditions.
Large and remote offshore wind farms (OWFs) usually use voltage source converter (VSC) systems to transmit electrical power to the main network. Submarine high-voltage direct current (HVDC) cables are commonly used as transmission links. As they are liable to insulation breakdown, fault location in the HVDC cables is a major issue in these systems. Exact fault location can significantly reduce the high cost of submarine HVDC cable repair in multi-terminal networks. In this paper, a novel method is presented to find the exact location of the DC faults. The fault location is calculated using extraction of new features from voltage signals of cables' sheaths and a trained artificial neural network (ANN). The results obtained from a simulation of a three-terminal HVDC system in power systems computer-aided design (PSCAD) environment show that the maximum percentage error of the proposed method is less than 1%.