Response of Point-Absorbing Wave Energy Conversion System in 50-Years Return Period Extreme Focused Waves

Katsidoniotaki, Eirini; Nilsson, Erik; Rutgersson, Anna; Engström, Jens; Göteman, Malin

doi:10.3390/jmse9030345

Cited by 17 publications

(13 citation statements)

References 49 publications

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“…Therefore, simply using phase-alignment to obtain the largest possible wave peak from a given spectra will not necessarily lead to the largest response. This is consistent with previous research into constrained SDWs for alternative applications and devices (Taylor et al, 1997;Hann et al, 2018), but NW remains a popular approach for assessing survivability of floating ORE devices (Ransley et al, 2017;Katsidoniotaki et al, 2021). If NW produces unreliable results (i.e., not extreme events), however, then alternative methods should be developed and used as standard practice.…”

Section: Hinge-anglesupporting

confidence: 85%

Laboratory investigation on short design wave extreme responses for floating hinged-raft wave energy converters

et al. 2022

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In offshore renewable energy design procedures, accurate predictions of extreme responses are required in order to design for survivability whilst minimising associated costs. At present, the established method for predicting extreme responses is to conduct a large number of long-duration simulations, which is practical only in cases where the structural behaviour is captured by a computationally efficient linear approach. Many applications, however, will require a nonlinear approach, which significantly increases the computational cost, and hence the time required to analyse a problem. Should high-fidelity numerical approaches be the appropriate analysis tool, the long-duration simulations are likely to be impractical and in many cases infeasible. Laboratory testing can be utilised to address this to some extent, but this still time-consuming and expensive from a financial perspective. Consequently, there has been considerable interest in the use of short design waves as an alternative method for speeding up the design process. Currently, standards advise that short design waves can be utilised in the design of fixed offshore structures, but application to floating offshore structures needs verification before it becomes an established procedure. This study considers application of single and constrained short design waves to a floating hinged-raft wave energy converter using a 1:50 scale physical modelling approach, and compares with equivalent irregular sea states. The single wave approaches considered here are “NewWave” and the “Most Likely Extreme Response” wave, which are derived from the frequency content of the wave spectrum and response spectrum, respectively. The constrained approach considered in this study is the “Conditional Random Response Wave,” where the Most Likely Extreme Response wave is embedded within a random short irregular background. Results show that the single wave approaches under-estimate the extreme loading for the hinge-angle and mooring system compared with the irregular and constrained approaches. The discrepancy between single and constrained waves implies that memory effects are non-negligible, and hence it is critical that they are accounted for when utilising short design waves for floating applications.

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Section: Hinge-anglesupporting

confidence: 85%

Laboratory investigation on short design wave extreme responses for floating hinged-raft wave energy converters

et al. 2022

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“…In OpenFOAM simulations, to produce the target irregular wave episode (e.g., analytical) at a specific location in the numerical wave tank (e.g., where the monopile foundation will be placed), we follow a wave calibration procedure 67 . Figure 4 shows the schematic depiction of the wave calibration, which is similar to the one presented in Windt et al 68 and previously has been applied by previous studies 69,70 …”

Section: High‐fidelity Cfd Modelingmentioning

confidence: 93%

“…67 Figure 4 shows the schematic depiction of the wave calibration, which is similar to the one presented in Windt et al 68 and previously has been applied by previous studies. 69,70 The target wave episode and the numerical wave obtained from the last iteration are compared through their density wave spectrum. Figure 5 compares four representative wave episodes.…”

Section: Numerical Wave Calibrationmentioning

confidence: 99%

Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling

Guth,

Katsidoniotaki,

Sapsis

2023

Wind Energy

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Accurately determining hydrodynamic force statistics is crucial for designing offshore engineering structures, including offshore wind turbine foundations, due to the significant impact of nonlinear wave–structure interactions. However, obtaining precise load statistics often involves computationally intensive simulations. Furthermore, the estimation of statistics using current practices is subject to ongoing discussion due to the inherent uncertainty involved. To address these challenges, we present a novel machine learning framework that leverages data‐driven surrogate modeling to predict hydrodynamic loads on monopile foundations while reducing reliance on costly simulations and facilitate the load statistics reconstruction. The primary advantage of our approach is the significant reduction in evaluation time compared to traditional modeling methods. The novelty of our framework lies in its efficient construction of the surrogate model, utilizing the Gaussian process regression machine learning technique and a Bayesian active learning method to sequentially sample wave episodes that contribute to accurate predictions of extreme hydrodynamic forces. Additionally, a spectrum transfer technique combines computational fluid dynamics (CFD) results from both quiescent and extreme waves, further reducing data requirements. This study focuses on reducing the dimensionality of stochastic irregular wave episodes and their associated hydrodynamic force time series. Although the dimensionality reduction is linear, Gaussian process regression successfully captures high‐order correlations. Furthermore, our framework incorporates built‐in uncertainty quantification capabilities, facilitating efficient parameter sampling using traditional CFD tools. This paper provides comprehensive implementation details and demonstrates the effectiveness of our approach in delivering reliable statistics for hydrodynamic loads while overcoming the computational cost constraints associated with classical modeling methods.

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“…The dimensions of the numerical wave tank are 3λ × 100 m × 2d m (L × W × H); the length parametric changes with the wave length, λ, and the height is a function of water depth, d. To avoid the wave reflections, the wave tank's length downstream of the buoy and the width are determined based on the sensitivity study presented by the authors [27]. The buoy is placed 1λ from the inlet boundary, providing enough space for the wave to propagate.…”

Section: Cfd Modelmentioning

confidence: 99%

“…The higher resolution region close to the water surface extended 2H below and above the water level, is used to properly capture the wave propagation, avoiding the excessive damping. The spatial discretization is equal to 17 CPH (cells per wave height) following the mesh convergence study presented in [27], preserving the spatial discretization error <0.6%. In the area close and around the buoy, the mesh is even more refined so that the hydrodynamic forces and the turbulence phenomena are well-captured.…”

Section: Cfd Modelmentioning

confidence: 99%

Offshore Measurements and Numerical Validation of the Mooring Forces on a 1:5 Scale Buoy

Engström

Shahroozi

Katsidoniotaki

et al. 2023

JMSE

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Wave energy conversion is a renewable energy technology with a promising potential. Although it has been developed for more than 200 years, the technology is still far from mature. The survivability in extreme weather conditions is a key parameter halting its development. We present here results from two weeks of measurement with a force measurement buoy deployed at Uppsala University’s test site for wave energy research at the west coast of Sweden. The collected data have been used to investigate the reliability for two typical numerical wave energy converter models: one low fidelity model based on linear wave theory and one high fidelity Reynolds-Averaged Navier–Stokes model. The line force data is also analysed by extreme value theory using the peak-over-threshold method to study the statistical distribution of extreme forces and to predict the return period. The high fidelity model shows rather good agreement for the smaller waves, but overestimates the forces for larger waves, which can be attributed to uncertainties related to field measurements and numerical modelling uncertainties. The peak-over-threshold method gives a rather satisfying result for this data set. A significant deviation is observed in the measured force for sea states with the same significant wave height. This indicates that it will be difficult to calculate the force based on the significant wave height only, which points out the importance of more offshore experiments.

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Response of Point-Absorbing Wave Energy Conversion System in 50-Years Return Period Extreme Focused Waves

Cited by 17 publications

References 49 publications

Laboratory investigation on short design wave extreme responses for floating hinged-raft wave energy converters

Laboratory investigation on short design wave extreme responses for floating hinged-raft wave energy converters

Statistical modeling of fully nonlinear hydrodynamic loads on offshore wind turbine monopile foundations using wave episodes and targeted CFD simulations through active sampling

Offshore Measurements and Numerical Validation of the Mooring Forces on a 1:5 Scale Buoy

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