Buoy Motion Research Articles

Hydrodynamic performance characteristics of small-scale in-situ buoys with critical motion requirements

As the accuracy of high-precision oceanographic measurement instruments increases, the operational requirements for buoy motion become critical. This study focuses on the small-scale in-situ buoy, optimizing buoy configuration to ensure stability and performance. Aiming at the special structure which consists of a large floating column and several small tube connectors, a method for evaluating the hydrodynamic performance is proposed which combines potential flow theory with Morison equation. And the method validity is confirmed using experimental data. The performances analysis of different type buoy with catenary or taut mooring system are developed. According to the critical motion requirements for the long-term stability, the cylindrical type buoy equipped with a catenary mooring system is regarded as the most stable and economical choice, exhibiting a surge motion response of 4.07 m, a heave motion response of 2.89 m, and a pitch motion response of 9.37°. Furthermore, the anchor chain acts as an elastic damper which can mitigate the transient impact of the environmental loads, greatly limiting the amplitude of the longitudinal and heaving motions. And the maximum mooring line tension is 249.28 kN, which is significantly lower than other schemes. The evaluation method offers a technical support for engineering applications.

A Machine Learning Approach to Correct Turbulence Intensity measured by Floating Lidars

In this work we introduce a supervised Machine Learning (ML) model to correct the Turbulence Intensity (TI) measured by Floating LiDAR Systems (FLS) in offshore environment. The model was developed using data from 46 EOLOS-FLS200 validation campaigns (≈ 4.6 years) carried out at three reference sites in the North Sea. It is based on Gradient Boosting Decision Tree (GBDT) and accounts for wind characteristics, atmospheric conditions, buoy motion, and wave features. Numerical analyses pronounced a consistent improvement in both coefficient of determination (R 2) and Mean Bias Error yielded by the ML-corrected TI. In addition, TI estimates in accordance with the state-of-the-art best practices were successfully obtained, even when evaluating the ML model in a site out of the training dataset, which demonstrates the model’s robustness.

Applying motion compensation to offshore wind lidar reconstructed wind measurements

Floating lidar systems present an effective and advantageous solution for offshore wind speed measurements, providing wind speed and direction data at multiple heights with easy deployment to provide widespread wind information around an area. One of the causes of apprehension, however, concerns buoy motion which induces overestimations of turbulence intensity and potentially imprecise measurements of horizontal wind speed. This research aims to reduce this uncertainty by applying motion compensation to three wind field reconstruction techniques (scalar, vector, and hybrid) to assess the amelioration on horizontal wind speed and turbulence intensity; especially how motion compensation can improve scalar and hybrid outputs. A three-month dataset of a floating lidar system (FLS) was compared to a nearby fixed lidar. The results demonstrate that motion compensation provides an improvement for horizontal wind speed measurement but inflates the overestimation of turbulence intensity from the floating lidar system. Though scalar reconstruction measurements provide slightly more accurate data compared to hybrid reconstructed measurements, motion compensation helps limit the bias disparity; ergo, applying motion compensation reduces the differences in bias for scalar and hybrid reconstructed measurements. This study results in two conclusions. Basic motion compensation provides a notable amelioration for horizontal wind speed FLS measurements, yet further research must be conducted to find a suitable method to improve turbulence intensity. Additionally, the scalar reconstruction method still slightly outperforms hybrid reconstruction in offshore measurement results, but motion compensation aids in limiting the differences between the two.

Theoretical evaluation of a hybrid buoyancy-compressed air energy storage system

Energy storage plays a pivotal role in the emerging green economy. This study, for the first time, presents the theoretical evaluation of a buoyancy power generator combining with the compressed air energy storage (CAES-BPG) system. A theoretical model that satisfies conservation laws and does not involve any adjustable parameters is developed for the calculation of system efficiency and power generation capacity. To accurately predict drag acting on the buoy, the low Reynolds number κ-ω SST model with a locally refined mesh (y+~1) is applied to fully resolve the viscosity affected regions including the viscous sublayers, whilst the surrounding flow is modelled by LES. The refined mesh moves passively with the buoy and does not change, whilst mesh in other regions undergoes smoothing and remeshing to accommodate the buoy's motion. Correlations of drag coefficients are then developed as a function of buoy shape, Reynolds number, and vessel-to-buoy size ratio. The aerofoil shape yielded a substantially smaller drag coefficient compared to the square, hex, and bullet shapes. System efficiency showed independency on buoy volume and shell material but decreased as the water level in the vessel increased, reaching 64 % for a water level of 1.5 m. Similarly, as the water level increased, the system output power decreased. The output power increased as the buoy volume increased, reaching ~22 kW for a buoy volume of 2 m3 at a water level of 1.5 m. This CAES-BPG system is highly automatic and fully green, and can operate continuously once compressed air is connected, showing great potential for implementation as an energy storage / utilisation system of small to medium capacities.

Experimental Evaluation of the Motion-Induced Effects for Turbulent Fluctuations Measurement on Floating Lidar Systems

This study examines how motion influences turbulent velocity fluctuations utilizing measurements obtained from a wind lidar profiler. Onshore tests were performed using a WindCube v2.1 lidar, which was mobile and mounted on a hexapod to simulate buoy motion. Additionally, a fixed WindCube v2.1 lidar was used as a reference during these tests. To assess the motion-induced effects on velocity fluctuations measured by floating lidar systems, the root-mean-square error (RMSE) of velocity fluctuations obtained from the fixed and mobile lidars was calculated. A comprehensive wind dataset spanning 22.5 h was analyzed, with a focus on regular motions involving single-axis rotations and combinations of rotations around multiple axes. The investigation of single-axis rotations revealed that the primary influencing factor on the results was the alignment between the tilt direction of the mobile lidar and the wind direction. The highest RMSE values occurred when the tilt of the mobile lidar leans in the wind direction, resulting in pitch motion, whereas the lowest RMSE values were observed when the tilt of the mobile lidar leans perpendicular to the wind direction, resulting in roll motion. Moreover, the addition of motion around extra axes of rotation was found to increase RMSE.

Exploring representative samples for modeling of wave buoy motion behavior

To collect sufficient data to describe buoy motion behavior in extreme environment conditions is intractable. The conventional data-driven models constructed with randomly selected and limited training samples are unable to perform adequately for exhibiting complex dynamic characteristics. In this work, an active sample exploring strategy is developed to build a reliable prediction model with limited samples. First, an evaluated index is designed to depict both the data distribution characteristics and estimation uncertainty of all test data using a probabilistic model. The representative data are then captured and integrated into the initial training set based on this index, and the updated uncertainty information is used as the criterion to judge the exploring termination. Finally, the initial training set is supplemented to enhance the model performance. Experimental and comparative results demonstrate the superiority of the proposed sample exploring strategy.

Stereo vision based systems for sea-state measurement and floating structures monitoring

Using computer vision techniques such as stereo vision systems for sea state measurement or for offshore structures monitoring can improve the measurement fidelity and accuracy with no significant additional cost. In this paper, two experiments (in-lab/open-sea) are conducted to study the performance of stereo vision system to measure the water wave surface elevation and rigid body heaving motion. For the in-lab experiment, regular water waves are generated in a wave tank for different frequencies and wave heights, where the water surface is scanned by the stereo vision camera installed on the top of the tank. Surface elevation inferred by the stereo vision is verified by an installed stationary side camera that records the water surface through the tank transparent side window, water surface elevation measured by the side camera recordings is extracted using edge detection algorithm. During the in-lab experiment a heaving buoy is installed to test the performance of Visual Simultaneous Localization and Mapping (VSLAM) algorithm to monitor the buoy heave motion. The VSLAM algorithm fuses a buoy onboard stereo vision recordings with an embedded Inertial Measurement Unit (IMU) to estimate the 6-DOF of a rigid body. The Buoy motion VSLAM measurements are verified by a KLT tracking algorithm implemented on the video recordings of the stationary side camera. The open-sea experiment is implemented in Lake Somerville, Texas. The stereo vision system is installed to measure the water surface elevation and directional spectrum of the wind generated irregular waves. The open-sea wave measurements by the stereo vision are verified by a Sofar commercial wave buoys deployed in the testing location.

A preliminary study of a novel wave energy converter of a Scotch Yoke mechanism-based power take-off

This work proposes a novel concept to harvest power from ocean waves using a Scotch Yoke mechanism to transmit the heave motion of the buoy into the rotation of an off-the-shelf rotary generator. The novel transmission mechanism is proposed to tackle some of the main obstacles of ocean waves energy harvesters associated with the reliance on resonance and the high expenses related to the large device dimensions and permanent magnet linear generators. The Scotch Yoke mechanism converts the linear wave motion of a harmonic nature into rotary generator motion, coinciding with the nature of ocean waves. A mathematical model is constructed relating the hydrodynamics of the float to the non-linear resistive forces of the power take-off. Simulations are conducted for two different devices, including a typical large-scale-up wave energy converter device and a relatively small scaled-down wave energy converter device that can be placed close to the shore. The simulation results showcase that the large scale device can have a peak harvesting efficiency of up to 42%, while the small scale device can have a peak harvesting efficiency of up to 34%. This is of great importance as the small device can be used with an off-the-shelf rotary generator, and can be placed close to the shoreline further lowering the cost of manufacturing, installation, and maintenance allowing easier access to the device. Also, to validate the concept, a small scaled-down device has been fabricated, and dry-tested. The tested power take-off is proven to be able to harvest energy from linear harmonic oscillating buoy motions with a peak efficiency of 49% (not including the hydrodynamic efficiency).

A numerical and experimental study of a buoy interacting with waves

PurposeThis paper aims to report the study of a fluid buoy system that includes wave effects, with particular emphasis on validating the numerical results with experimental data.Design/methodology/approachA fluid–solid coupled algorithm is proposed to describe the motion of a rigid buoy under the effects of waves. The Navier–Stokes equations are solved with the open-source finite volume package Code Saturne, in which a free-surface capture technique and equations of motion for the solid are implemented. An ad hoc experiment on a laboratory scale is built. A buoy is placed into a tank partially filled with water; the tank is mounted into a shake table and subjected to controlled motion that promotes waves. The experiment allows for recording the evolution of the free surface at the control points using the ultrasonic sensors and the movement of the buoy by tracking the markers by postprocessing the recorded videos. The numerical results are validated by comparison with the experimental data.FindingsThe implemented free-surface technique, developed within the framework of the finite-volume method, is validated. The best-obtained agreement is for small amplitudes compatible with the waves evolving under deep-water conditions. Second, the algorithm proposed to describe rigid-body motion, including wave analysis, is validated. The numerical body motion and wave pattern satisfactorily matched the experimental data. The complete 3D proposed model can realistically describe buoy motions under the effects of stationary waves.Originality/valueThe novel aspects of this study encompass the implementation of a fluid–structure interaction strategy to describe rigid-body motion, including wave effects in a finite-volume context, and the reported free-surface and buoy position measurements from experiments. To the best of the authors’ knowledge, the numerical strategy, the validation of the computed results and the experimental data are all original contributions of this work.

Oceanographic wave buoy motion as a 3D-vector field: Spectra, linear components and bound harmonics

This study analyses time history data measured by a widely used type of oceanographic buoy. The motion of the buoy is recorded as a three-component displacement vector with one vertical and two horizontal components. Focusing on the average shapes of the large events in the time series, we investigate the linear and nonlinear structure of the displacements and their inherent relationships. All three displacements show clear evidence of both linear and second-order contributions. Two types of nonlinear contributions are identified: the difference term representing slow oscillation on the mooring system, and the sum term oscillating at roughly twice the frequency of the linear waves. These terms are small vertically but larger horizontally. We examine the coupled structure of the vertical and horizontal motions with a conditioning analysis. The averaged time histories associated with large waves are found to obey a simple reciprocal relationship, and the average shape of the motion in space associated with large waves in the sea-state resembles that in a localised steep wave-group. The power spectrum of the vertical motion can be transformed into those in the horizontal plane. This work demonstrates that, as well as providing accurate spectral information of the sea state, oceanographic wave buoys can provide internally consistent time series for the vector displacement field with little observable distortion from the mooring system.

Influence of Six-Degree-of-Freedom Motion of a Large Marine Data Buoy on Wind Speed Monitoring Accuracy

In order to quantitatively analyze the data measurement accuracy of ocean buoys under normal and extreme sea conditions, in this study, we simulated the six-degree-of-freedom motion response of self-designed ocean buoys under different sea conditions based on a separated vortex simulation and the fluid volume method and analyzed the impact of the unsteady motion of buoys on data measurement. The results indicate that under normal sea conditions, the deviation between the numerical method used in this paper and the experimental results is less than 10%. The heaving motion of a buoy is most sensitive to changes in wave conditions. The fluctuation intensity of buoy motion is modulated by the height and wavelength of waves. When the wave height and wavelength are similar to the overall geometric size of a buoy, the wave characteristics of the buoy’s heave, yaw, and pitch motion are significant. In addition, under extreme sea conditions, the movement of the buoy can also cause a deviation in the measured velocity in the transverse flow direction, but the overall deviation is less than 10%. In extreme sea conditions, the wind speed measurement results should be corrected to improve the measurement accuracy of a buoy.

Comparison of physics-based and machine learning methods for phase-resolved prediction of waves measured in the field

Phase-resolved predictions of surface waves can be used to optimize a wide variety of marine applications. In this paper, we compare predictions obtained using two independent methods for field data, with horizons sufficient to control wave energy converters. The first method is physics-based prediction. In this method, a set of optimal representative angles, obtained using an optimization algorithm given time histories of a wave buoy motion in 3D, are used for forward propagation based on linear wave theory. The second method is a machine learning method using an Artificial Neural Network (ANN) which requires longer records for training. Field measurements were obtained from the Southern Ocean of Albany, WA. The field data were collected by an upwave ‘detection’ array of 3 Sofar Spotter wave buoys and a downwave ‘prediction’ point coincident with a Datawell Waverider-4. All buoys were soft-moored, and data were collected over 3 months in 2022. Selected intervals during this period are presented in the paper to compare and contrast the predictions made by the two different methods. We find that some wave fields can be predicted well over more than a period in advance, all that is required for active control of a wave power take-off in a renewable energy application. In contrast, highly spread sea states remain a challenge. The methods are also compared in terms of the complexity and time required for making predictions. Further discussions are made on the applicability of the results to other locations.

Wave Excitation Force Estimation for a Multi-DoF WEC via a Cubature Kalman Filter: Improved Design and Results

In this paper, we develop a multiple degree-of-freedom (multi-DoF) wave excitation force estimator based on the square-root cubature Kalman filter (SCKF) [1] combined with an online empirical covariance matching technique for a CETO-like, submerged wave energy converter (WEC) device with three PTOs.
 Though wave excitation force estimation is required by many advanced WEC control approaches, the literature is still quite scarce for multi-DoF devices. Indeed, there are several difficulties in designing a multi-DoF excitation force estimator, especially when the full motion of the WEC is considered. The high dimension of the underlying dynamic system leads to difficulties in on-line implementation and in estimator parameter-tuning. Moreover, nonlinearities may significantly deteriorate estimation performance if a linearized model is used by the estimator to reduce computation time. Papers [2-4] present solutions to multi-DoF wave excitation force estimation, ranging from (extended) Kalman filters to feedforward neural networks, but only up to three DoFs, the surge, heave and pitch directions. In [5], results for a CETO-like WEC are presented for all the six DoFs, based on a CKF wave estimator, which uses a linear state-space model. Undesirable large estimation errors on the yaw direction were observed for several sea states, mainly caused by the model errors introduced by linearizing the kinematics linking buoy motion to PTOs motions. Moreover, even though the CKF is known to be relatively easy to calibrate, guessing covariance matrices of the system and measurement model noises remains troublesome.
 In this paper, we propose to use the SCKF, together with an empirical online covariance matching to over overcome the difficulty of parameter tuning. In our estimator, a nonlinear dynamic system of dimension 72 is used to predict the system dynamics at the cubature points, and the 6-dimensional excitation force is estimated. In addition, we show that a careful system state scaling can substantially reduce estimation errors on the yaw direction, even when using the linearized dynamic system. Moreover, thanks to the moderate computation complexity of the SCKF, and its parallelizability, online implementation can be achieved by taking slightly larger sampling time step, at the price of a small degradation in performance.
 REFERENCES
 [1] I. Arasaratnam and S. Haykin. “Cubature kalman filters”. In: IEEE Transactions on automatic control 54.6 (2009).
 [2] Ling, B. A., 2015. “Real-time estimation and prediction of wave excitation forces for wave energy control applications”. Master’s thesis, Oregon State University.
 [3] Hillis, A., Yardley, J., Plummer, A., and Brask, A., 2020. “Model predictive control of a multi-degree-of-freedom wave energy converter with model mismatch and prediction errors”. Ocean Engineering, 212, p. 107724.
 [4] Bonfanti, M., Hillis, A., Sirigu, S. A., Dafnakis, P., Bracco, G., Mattiazzo, G., and Plummer, A., 2020. “Real-time wave excitation forces estimation: An application on the ISWEC device”. Journal of Marine Science and Engineering, 8(10).
 [5] Nguyen, H.-N., Tona, P., Mérigaud, A., Cocho, M., Pichard, A. “Wave Excitation Force Estimation for a Multi-DoF WEC via a Cubature Kalman Filter: Design and Preliminary Results”, In Proc. of OMAE 2021, virtual, online.

A robotized 6-DOF dry test rig for wave power

Wave power has the potential to contribute significantly to sustainability by reducing our global dependence on fossil fuels. Due to harsh conditions and high costs associated with offshore testing, lab experiments are favourable for resource-efficient validation and optimization in developing Wave Energy Converter (WEC) technologies. The limited scale and availability of existing wave tanks, and the limited flexibility of existing dry test rigs does however put significant restraints on such experiments. In this paper we introduce an alternative novel robotized dry test rig concept for wave power, evaluate its performance and discuss its potential. A full-scale robotized dry test rig demonstrator is constructed and used for experiments with a WEC prototype device. High motion flexibility and accuracy is thereby validated, also for repeating recorded wave and buoy motions. Compared to other dry test rigs, no special components were used and the motion trajectories were defined in full 6-Degrees-Of-Freedom. Two real-time hydrodynamic motion response methods are also demonstrated in the test rig, enabling emulation of actual offshore operation as well as development of advanced WEC control strategies. With a larger industrial robot manipulator, the introduced test rig concept could achieve realistic scaled force and power experiments with most point absorber WECs.

Prediction of Chinese-lantern submarine hose tension variation in extreme sea states based on data-driven methods

To predict the variation of Chinese-lantern type submarine hose tension in extreme sea states is of great significance for the monitoring, operation and lifetime assessment of catenary anchor leg mooring (CALM) systems. In this research, the machine learning algorithm in radial basis function (RBF) neural network and the deep learning algorithm in long short-term memory (LSTM) neural network model were used to predict the variation of submarine hose tension respectively, and the prediction performance of the two algorithms on the time-series variation of submarine hose tension was evaluated. During the neural network construction, the six-degree-of-freedom (6-DOF) motion of CALM buoy is taken as the training parameter, while the historical tension variation data is also integrated for the correction of the prediction results. The training data are collected by hydrodynamic coupling simulation of the established CALM system with submarine hoses. Different parameter values selection of the neural network model is investigated to determine the optimal structure of the RBF and LSTM neural network models, including spread, initial learning rate, number of nodes in the hidden layer and batch size. Since the direction of environmental loads has a large effect on the response of the submarine hose, four combinations of wind, wave and currents under 100-year self-existing sea state are considered in the research. Through the case study and sensitivity analysis, it is demonstrated that the non-linear relationship between 6-DOF motion and hose tension is varied for different environmental load directions and LSTM neural network is suitable for predicting the variation of Chinese-lantern type submarine hose tension in CALM systems under different combinations of extreme sea states.

ENGINEERING PORTABLE UNDERWATER LAMP AS AN AUXILIARY GEAR FOR PURSE SEINE

Lights are common supporting tool in purse seine fishing in Indonesia. Currently, lamps on purse seines use mercury and metal halide (MH) which require very high electrical power. Therefore, there is a need for an effective underwater light technology alternative with low electric power. The aim of this research is to design a portable underwater lamp (PUL) which can be controlled remotely to support fishing operations. The design engineering process in creating the PUL includes light and buoy construction, temperature testing, light distribution, waterproofing, and motion testing. The results show that the PUL design enables the tools to be controlled remotely. The average temperature of the lamp on the PUL is 40 ⁰C, this temperature is lower than the MH lamp which reaches 250 ⁰C. The light spreads evenly at an angle of 360⁰ to the horizontal and 180° to the vertical. Meanwhile, the results of the lamp motion test showed that the lamp was watertight and highly stable.
 Keywords: Light emitting diode, Remote control, Waterproof, Electric Power.

Analysis method of WEC sub-system for hybrid wind-wave energy system based on reconstructed displacements

The structural response and modal information of hybrid wind-wave energy system are important evaluation indicators for its design and damage diagnosis, which are crucial for its development. In this paper, a displacement drift term removal method based on Chebyshev polynomials is developed based on the structural acceleration. The problem of difficult displacement measurement at sea is solved, and the displacement is used in the modal parameter identification of the structure, which improves the modal identification accuracy of the hybrid wind-wave energy system. The influence of the motion and number of buoys on the dynamic response and dynamic characteristics of the structure is discussed. The research results show that the identification results of modal parameters using displacement are more accurate than acceleration, and with the increase of the number of wave energy devices, the frequency of each order of the structure decreases. The displacement of the structure increases with the wave height, at a rate that depends on the number of buoys. The results show that the method developed in this paper can be applied to the impact analysis aspects of wave energy devices in hybrid wind-wave energy system, providing theoretical references for its design and development.

Analysis of Motion Characteristics of General Mobile Buoy

This thesis proposes a new type of general mobile buoy used in the South China Sea. The free motion of the buoy in still water is analyzed theoretically, and the theoretical estimate of the buoy natural period is obtained. A three-dimensional model is established to simulate the buoy, and the buoy motion amplitude response Rao curve is obtained. The results show that it can meet the requirement that the motion angle is always less than 15° in the range of 3~20 s in the wave period under the level 2 sea state.

Evaluation of a GNSS for wave measurement and directional wave spectrum analysis

Wave buoys are important devices to monitor and analyze wave data for ocean and coastal engineering. A GNSS wave buoy is briefly introduced in the paper, which has high resolution to measure the buoy motion by vertical, north-south and west-east displacements and independent velocities in above three directions. Based on the displacements and velocities, statistical results, frequency spectra and directional spectra are analyzed, and results based on the displacements are compared with that from Waverider with a distance less than 6m deployed in the special sea water with the GNSS buoy. Wave profiles comparison show that GNSS buoy presented slightly large significant wave height and mean wave height due to its high sampling frequency, and resulted in smaller mean wave period than that from Waverider. Statisticaly, between the analyzing result of the GNSS and wave rider, the maximum error of wave height is about 5.5%; and the maximum difference of wave period is about 0.5s, when sampling frequency is similar. The energy spectra were basically consistent from these two devices. The peaks of directional spectra were similar but the spreading angle was smaller from GNSS. Results mean the GNSS device presents almost similar wave information to that from Waverider.

Use of a Compliant Tether to Decouple Observation Buoy Motion for Auxiliary Wave Power

Abstract With the growth of the Blue Economy, the volume of data collection within the ocean environment has been rapidly increasing. Larger numbers of oceanographic, meteorological, and floating Light Detection And Ranging (LiDAR) buoys have been collecting high fidelity measurements while pushing against power budget limits. Power limitations lead to infrequent transmission of reduced data sets or recording data to local storage that must be physically collected when the buoy is serviced. Triton Systems, Inc. and its partners are developing a retrofittable wave energy converter (WEC) to provide auxiliary power to these observation buoys to increase mission duration and power budget, improve reliability, and reduce the need for service trips. One of the greatest challenges has been developing a method to interface Triton's WEC with these buoys without impacting measurement fidelity. This is especially critical for inertial wave and LiDAR wind measurements collected with sensors that could be adversely affected by additional buoy dynamics introduced by an integrated WEC. To address this, Triton and EOM Offshore developed a compliant tether to pair an observation buoy with a floating WEC while decoupling relative motion. Based on EOM's proven stretch hose technology, this compliant tether transmits power and data between the buoy-WEC system. Modeling shows that the system has the potential to minimally adversely affect oceanographic, meteorological, wind resource characterization, and other measurements, with future testing scheduled to validate modeling efforts.