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High levels of turbulence have been proven to substantially increase the blade loadings on tidal turbines, outlining the need of properly characterizing turbulence parameters in tidal energy sites. The presence of long surface gravity waves may cause a significant bias on the estimation of these parameters, which requires wave-turbulence decomposition methods that are currently missing from guidelines. Here, three techniques of decomposing wave and turbulence are tested: the stopband filter (SB), moving average filter (MA), and synchrosqueezing wavelet transform (SWT). The study site, Banks Strait, Tasmania, is a 16 km wide channel that presents high potential for tidal energy generation. Wave peak periods at the study site were found to vary mostly between 7 and 12 s, with maximum exceeding 15 s. Turbulence intensities (TI), turbulent kinetic energy (TKE), and integral scales are quantified. Our results indicate differences between the estimates obtained from each method. The MA highly underestimates turbulence, resulting in TI values which were nearly 50% lower than those obtained from other decomposition methods. While TI and TKE estimated from the SB and the SWT techniques are quite similar, integral length scales are considerably underestimated by the SB. These findings reveal that the SWT is a more reliable method because of the more accurate estimates of turbulence parameters and indicate the need of establishing guidelines which address wave-turbulence decomposition in tidal stream energy site assessments. Despite having shown to be quite a versatile technique, further investigation of its applicability in data from other prospective tidal energy sites is necessary to fully assess the generality of the SWT technique.

A laboratory experiment was conducted inside a wind wave tank to investigate the wave induced turbulence. In this experiment, the wave surface elevation and velocity beneath the water surface were measured simultaneously to investigate the relation between the wave status and wave induced turbulence. The profile of the turbulent dissipation rate and Reynolds stress were calculated using experimental data. The effect of the wave status on turbulence is investigated with regard to the wind wave, swell, and mixed wave conditions. It was depicted that the turbulence decreased with increasing depth from the water surface and that the turbulence that was induced by a wave with larger wavelength and wave height is much stronger for the same wave status. Finally, we observed that the wind wave is more effective in activating the wave induced turbulence. [ABSTRACT FROM AUTHOR]

Abstract: Several methods have been developed for the estimation of the turbulent Reynolds stress in wavy aquatic environment. They are based on different physical assumptions and often give discrepant results. It is practically difficult to quantify the uncertainties in these estimations. Using high‐resolution velocity measurements of acoustic Doppler velocimeter (ADV) from a coastal benthic layer subject to moderate wave influence (the ratio of rms wave orbital velocity to current magnitude was 0.23–0.92), this study tests a Synchrosqueezed Wavelet Transform (SWT)‐based method and three existing methods (i.e., the Coherence, Cospectra, and Ensemble Empirical Mode Decomposition [EEMD] methods) for wave‐turbulence decomposition. In particular, we evaluate the performance of different methods for objective estimation of the turbulent Reynolds stress. Power spectra and cospectra analysis is conducted to quantify the uncertainties in the estimations. The results suggest that the Coherence method tends to overestimate the Reynolds stress due to incomplete removal of wave motions from the observed velocity records; the Cospectra method performs poorly because the empirical model does not fit the observed cospectra well; both the EEMD and SWT methods underestimate the Reynolds stress, as they tend to attribute turbulent fluctuations at frequencies in the vicinity of the wave frequencies to wave motions. In general, the SWT method performs best inducing lowest uncertainty in the Reynolds stress estimation. For the data set analyzed in this study, the estimations with the Coherence, Cospectra, EEMD, and SWT methods account for 70%, 50%, 51%, and 60% of the total covariance of horizontal and vertical velocities, respectively. [ABSTRACT FROM AUTHOR]

Accurate estimations for the bed shear stress are essential to predict the erosion and deposition processes in estuaries and coasts. This study used high-frequency in situ measurements of water depths and near-bed velocities to estimate bed shear stress on an open intertidal flat in the Yangtze Delta, China. To determine the current-induced bed shear stress ( τ c ) the in situ near-bed velocities were first decomposed from the turbulent velocity into separate wave orbital velocities using two approaches: a moving average (MA) and energy spectrum analysis (ESA). τ c was then calculated and evaluated using the log-profile (LP), turbulent kinetic energy (TKE), modified TKE (TKEw), Reynolds stress (RS), and inertial dissipation (ID) methods. Wave-induced bed shear stress ( τ w ) was estimated using classic linear wave theory. The total bed shear stress ( τ cw ) was determined based on the Grant–Madsen wave–current interaction model (WCI). The results demonstrate that when the ratio of significant wave height to water depth ( H s / h ) is greater than 0.25, τ cw is significantly overestimated because the vertical velocity fluctuations are contaminated by the surface waves generated by high winds. In addition, wind enhances the total bed shear stress as a result of the increases in both τ w and τ c generated by the greater wave height and reinforcing of vertical turbulence, respectively. From a comparison of these various methods, the TKEw method associated with ESA decomposition was found to be the best approach because: (1) this method generates the highest mean index of agreement; (2) it uses vertical velocities that are less affected by Doppler noise; and (3) it is less sensitive to the near-bed stratification structure and uncertainty in bed location and roughness. [ABSTRACT FROM AUTHOR]

Tidal energy turbines are significantly impacted by surface gravity waves and high turbulence levels, which lead to increased blade loads and consequent device fatigue. Accurately describing turbulence quantities is a key factor to improve numerical models and ensure the minimum necessary device longevity. The application of an appropriate wave-turbulence decomposition technique substantially improves estimates and must be debated by the tidal energy community. This work analyses two wave-turbulence decomposition techniques: i) linear wave theory and ii) Synchrosqueezing Wavelet Transform (SWT) based on physical modelling. The experiments were conducted in a towing tank and the physical model used Froude scaling to simulate wave heights and frequencies based on field measurements from a tidal energy candidate site in Australia. Turbulence was generated using a grid with 47 mm openings replicating turbulence intensities of 17%, 23% and 25%. Both decomposition techniques present limitations in wave frequencies above 0.7 Hz. Our results suggest that the SWT technique is more versatile and more efficient under various conditions. Restrictions to the linear wave theory method are discussed with regards to ADCP geometry and possible non-linearity. The variability obtained from the wave-turbulence decomposition techniques emphasizes the importance of establishing guidelines for turbulence characterization in tidal energy sites. • Grid-generated turbulence is used in interaction with surface waves in a towing tank. • Impact of wave-turbulence decomposition on tidal energy site assessments is emphasized. • Wave-turbulence decomposition plays an important role in turbulence characterization. • SWT wave-turbulence decomposition technique proves to be satisfactorily versatile. • SWT decomposition is suitable in wave frequencies often observed in tidal energy sites. [ABSTRACT FROM AUTHOR]

High levels of turbulence have been proven to substantially increase the blade loadings on tidal turbines, outlining the need of properly characterizing turbulence parameters in tidal energy sites. The presence of long surface gravity waves may cause a significant bias on the estimation of these parameters, which requires wave-turbulence decomposition methods that are currently missing from guidelines. Here, three techniques of decomposing wave and turbulence are tested: the stopband filter (SB), moving average filter (MA), and synchrosqueezing wavelet transform (SWT). The study site, Banks Strait, Tasmania, is a 16 km wide channel that presents high potential for tidal energy generation. Wave peak periods at the study site were found to vary mostly between 7 and 12 s, with maximum exceeding 15 s. Turbulence intensities (TI), turbulent kinetic energy (TKE), and integral scales are quantified. Our results indicate differences between the estimates obtained from each method. The MA highly underestimates turbulence, resulting in TI values which were nearly 50% lower than those obtained from other decomposition methods. While TI and TKE estimated from the SB and the SWT techniques are quite similar, integral length scales are considerably underestimated by the SB. These findings reveal that the SWT is a more reliable method because of the more accurate estimates of turbulence parameters and indicate the need of establishing guidelines which address wave-turbulence decomposition in tidal stream energy site assessments. Despite having shown to be quite a versatile technique, further investigation of its applicability in data from other prospective tidal energy sites is necessary to fully assess the generality of the SWT technique. [ABSTRACT FROM AUTHOR]