Numerical analysis of wave–structure interaction of regular waves with surface-piercing inclined plates

The Mocean wave energy converter consists of two sections, hinged at a central location, allowing the device to convert energy from the relative pitching motion of the sections. In a simplified form, the scattering problem for the device can be modelled as monochromatic waves incident upon a thin, inclined, surface-piercing plate of length $$L'$$ L ′ in a finite depth $$d'$$ d ′ of water. In this paper, the flow past such a plate is solved using a Boundary Element Method (BEM) and Computational Fluid Dynamics (CFD). While the BEM solution is based on linear potential flow theory, CFD directly solves the Navier–Stokes equations. Problems of this type are known to exhibit near-perfect reflection (indicated by a reflection coefficient $$|R|\approx 1$$ | R | ≈ 1 ) of waves at specific wavenumbers $$k'$$ k ′ . In this paper, we show that the resonant motion of the fluid induces large hydrodynamic forces on the plate. Furthermore, we argue that this low-frequency resonance resembles Helmholtz resonance, and that Mocean’s device being able to tune to these low frequencies does not act like an attenuator. For the case where the water is deep ($$d'>\lambda '/2$$ d ′ > λ ′ / 2 , where $$\lambda '=2\pi /k'$$ λ ′ = 2 π / k ′ ), we find excellent agreement between our simulations and previous semi-analytical studies on the value of the resonant wave periods in deep water. We also find excellent agreement between the excitation forces on the plate computed using the BEM model, analytical results, and CFD for large inclination angles ($$\alpha > 45^\circ $$ α > 45 ∘ ). For $$\alpha \le 15^\circ $$ α ≤ 15 ∘ , both methods show the same trend, but the CFD predicts a significantly smaller peak in the excitation force compared with BEM, which we attribute to non-linear effects such as the non-linear Froude–Krylov force

Total wave power absorption by a multi-float wave energy converter and a semi-submersible wind platform with a fast far field model for arrays

Wave energy converters absorb wave power by mechanical damping for conversion into electricity and multi-float systems may have high capture widths. The kinetic energy of the floats causes waves to be radiated, generating radiation damping. The total wave power absorbed is thus due to mechanical and radiation damping. A floating offshore wind turbine platform also responds dynamically and damping plates are generally employed on semi-submersible configurations to reduce motion, generating substantial drag which absorbs additional wave power. Total wave power absorption is analysed here by linear wave diffraction–radiation–drag models for a multi-float wave energy converter and an idealised wind turbine platform, with response and mechanical power in the wave energy case compared with wave basin experiments, including some directional spread wave cases, and accelerations compared in the wind platform case. The total power absorption defined by capture width is input into a far field array model with directional wave spreading. Wave power transmission due a typical wind turbine array is only reduced slightly (less than 5% for a 10 × 10 platform array) but may be reduced significantly by rows of wave energy converters (by up to about 50%).

Seaweed ingress of cooling water intakes with predictions for Torness power station

Seaweed ingress into the cooling water intakes of nuclear power stations has caused several disruptions to electricity supply. Seaweed is transported by tidal and wave-induced currents after dislodgement from the sea bed following stormy conditions but ingress will be shown to be not only determined by wave conditions. An integrated model system has been developed to predict such ingress and applied at the Torness power station in Scotland where the mass of seaweed recovered was measured for some ingress cases. Prior to each case, seaweed is assumed initially to be distributed in areas surveyed within the surrounding coastal domain with a mass per unit area based on local measurements. Criteria for dislodgement are based on near-bed velocity. Six cases where the mass of ingress was measured and two cases with no ingress have been modelled and predicted by adjusting a dislodgement factor (a multiplier on the threshold velocity) within a relatively narrow range.

Digital twins of the mooring line tension for floating offshore wind turbines to improve monitoring, lifespan, and safety

The number of installed floating offshore wind turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system’s integrity, extending the lifespan of the components, and maintaining FOWTs safely at scale. Effectively and efficiently addressing these challenges would unlock the wide-scale deployment of FOWTs. In this work, we focus on one of the most critical components of the FOWTs, the Mooring Lines (MoLs), which are responsible for fixing the structure to the seabed. The primary mechanical failure mechanisms in MoLs are extreme load and fatigue, both of which are functions of the axial tension. An effective solution to detect long-term drifts in the mechanical response of the MoLs is to develop a Digital Twin (DT) able to accurately predict the behaviour of the healthy system to compare with the actual one. Moreover, we will develop another DT able to accurately predict the near future axial tension as an effective tool to improve the lifespan of the MoLs and the safety of FOWT maintenance operations. In fact, by changing the FOWT operational settings, according to the DT prediction, operators can increase the lifespan of the MoLs by reducing the stress and, additionally, in the case where FOWT operational maintenance is in progress, the prediction from the DT can serve as early safety warning to operators. Authors will leverage operational data collected from the world’s first commercial floating-wind farm [the Hywind Pilot Park (https://www.equinor.com/en/what-we-do/floating-wind/hywind-scotland.html.)] in 2018, to investigate the effectiveness of DTs for the prediction of the MoL axial tension for the two scenarios depicted above. The DTs will be developed using state-of-the-art data-driven methods, and results based on real operational data will support our proposal.

Fast nonlinear Froude–Krylov force calculation for prismatic floating platforms: a wave energy conversion application case

Computationally fast and accurate mathematical models are essential for effective design, optimization, and control of wave energy converters. However, the energy-maximising control strategy, essential for reaching economic viability, inevitably leads to the violation of linearising assumptions, so the common linear models become unreliable and potentially unrealistic. Partially nonlinear models based on the computation of Froude–Krylov forces with respect to the instantaneous wetted surface are promising and popular alternatives, but they are still too slow when floaters of arbitrary complexity are considered; in fact, mesh-based spatial discretisation, required by such geometries, becomes the computational bottle-neck, leading to simulations 2 orders of magnitude slower than real-time, unaffordable for extensive iterative optimizations. This paper proposes an alternative analytical approach for the subset of prismatic floating platforms, common in the wave energy field, ensuring computations 2 orders of magnitude faster than real-time, hence 4 orders of magnitude faster than state-of-the-art mesh-based approaches. The nonlinear Froude–Krylov model is used to investigate the nonlinear hydrodynamics of the floater of a pitching wave energy converter, extracting energy either from pitch or from an inertially coupled internal degree of freedom, especially highlighting the impact of state constraints, controlled/uncontrolled conditions, and impact on control parameters’ optimization, sensitivity and effectiveness.