Linear potential flow (LPF) models remain the tools-of-the-trade in marine and ocean engineering despite their well-known assumptions of small amplitude waves and motions. As of now, nonlinear simulation tools are still too computationally demanding to be used in the entire design loop, especially when it comes to the evaluation of numerous irregular sea states. In this paper we aim to enhance the performance of the LPF models by introducing a hybrid LPF-ML (machine learning) approach, based on identification of nonlinear force corrections. The corrections are defined as the difference in hydrodynamic force (viscous and pressure-based) between high-fidelity CFD and LPF models. Using prescribed chirp motions with different amplitudes, we train a long short-term memory (LSTM) network to predict the corrections. The LSTM network is then linked to the MoodyMarine LPF model to provide the nonlinear correction force at every time-step, based on the dynamic state of the body and the corresponding forces from the LPF model. The method is illustrated for the case of a heaving sphere in decay, regular and irregular waves – including passive control. The hybrid LPF model is shown to give significant improvements compared to the baseline LPF model, even though the training is quite generic.
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.
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 review article presents a summary of the main categories of models developed for modeling cavitation, a multiphase phenomenon in which a fluid locally experiences phase change due to a drop in ambient pressure. The most common approaches to modeling cavitation along with the most common modifications to said approaches due to other effects of cavitating flows are identified and categorized. The application of said categorization is demonstrated through an analysis of selected cavitation models. For each of the models presented, the various assumptions and simplifications made by the authors of the model are discussed, and applications of the model to simulating various aspects of cavitating flow are also presented. The result of the analysis is demonstrated via a visualization of the categorizations of the highlighted models. Using the preceding discussion of the various cavitation models presented, the review concludes with an outlook toward future improvements in the modeling of cavitation.
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.
High-fidelity models become more and more used in the wave energy sector. They offer a fully nonlinear simulation tool that in theory should encompass all linear and nonlinear forces acting on a wave energy converter (WEC). Studies using high-fidelity models are usually focusing on validation of the model. However, a validated model does not necessarily provide reliable solutions. Solution verification is the methodology to estimate the numerical uncertainties related to a simulation. In this work we test four different approaches: the classical grid convergence index (GCI); a least-squares version (LS-GCI); a simplified version of the least-square method (SLS-GCI); and the ITTC recommended practice. The LS-GCI requires four or more solutions whereas the other three methods only need three solutions. We apply these methods to four different high-fidelity models for the case of a heaving sphere. We evaluate the numerical uncertainties for two parameters in the time domain and two parameters in the frequency domain. It was found that the GCI and ITTC were hard to use on the frequency domain parameters as they require monotonic convergence which sometimes does not happen due to the differences in the solutions being very small. The SLS-GCI performed almost as well as the SL-GCI method and will be further investigated.
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%.
We numerically simulate the hydrodynamic response of a floating offshore wind turbine (FOWT) using CFD. The FOWT under consideration is a slack-moored 1:70 scale model of the UMaine VolturnUS-S semisubmersible platform. This set-up has been experimentally tested in the COAST Laboratory Ocean Basin at the University of Plymouth, UK. The test cases under consideration are (i) static equilibrium load cases, (ii) free decay tests and (iii) two focused wave cases with different wave steepness. The FOWT is modeled using a two-phase Navier-Stokes solver inside the OpenFOAM-v2006 framework. The catenary mooring is computed by dynamically solving the equations of motion for an elastic cable using the MoodyCore solver. The results of the static and decay tests are compared to the experimental values with only minor differences in motions and mooring forces. The focused wave cases are also shown to be in good agreement with measurements. The use of a one-way fluid-mooring coupling results in slightly higher mooring forces, but does not influence the motion response of the FOWT significantly.
The design of wave energy converters should rely on numerical models that are able to estimate accurately the dynamics and loads in extreme wave conditions. A high-fidelity CFD model of a 1:30 scale point-absorber is developed and validated on experimental data. This work constitutes beyond the state-of-the-art validation study as the system is subjected to 50-year return period waves. Additionally, a new methodology that addresses the well-known challenge in CFD codes of mesh deformation is successfully applied and validated. The CFD model is evaluated in different conditions: wave-only, free decay, and wave–structure interaction. The results show that the extreme waves and the experimental setup of the wave energy converter are simulated within an accuracy of 2%. The developed high-fidelity model is able to capture the motion of the system and the force in the mooring line under extreme waves with satisfactory accuracy. The deviation between the numerical and corresponding experimental RAOs is lower than 7% for waves with smaller steepness. In higher waves, the deviation increases up to 10% due to the inevitable wave reflections and complex dynamics. The pitch motion presents a larger deviation, however, the pitch is of secondary importance for a point-absorber wave energy converter.