scholarly journals Ocean Current Mapping with Indigenous Drifting Buoys

2020 ◽  
Vol 118 (11) ◽  
pp. 1778
Author(s):  
R. Srinivasan ◽  
Shijo Zacharia ◽  
V. Gowthaman ◽  
Tata Sudhakar ◽  
M. A. Atmanand
Keyword(s):  
Ocean Current ◽  
Drifting Buoys

scholarly journals Validation of FOAM near-surface ocean current forecasts using Lagrangian drifting buoys

Ocean Science ◽  
2012 ◽  
Vol 8 (4) ◽  
pp. 551-565 ◽  
Author(s):  
E. W. Blockley ◽  
M. J. Martin ◽  
P. Hyder
Keyword(s):  
Surface Current ◽  
Surface Velocity ◽  
Ocean Current ◽  
Near Surface ◽  
Surface Ocean ◽  
Forecasting System ◽  
Ocean Forecasting ◽  
Assimilation Scheme ◽  
Drifting Buoys

Abstract. In this study, the quality of near-surface current forecasts from the FOAM ocean forecasting system is assessed using the trajectories of Lagrangian drifting buoys. A method is presented for deriving pseudo-Eulerian estimates of ocean currents from the positions of Surface Velocity Program drifters and the resulting data are compared to velocities observed by the global tropical moored buoy array. A quantitative analysis of the global FOAM velocities is performed for the period 2007 and 2008 using currents derived from over 3000 unique drifters (providing an average of 650 velocity observations per day). A potential bias is identified in the Southern Ocean which appears to be caused by wind-slip in the drifter dataset as a result of drogue loss. The drifter-derived currents are also used to show how the data assimilation scheme and a recent system upgrade impact upon the quality of FOAM current forecasts.

scholarly journals Validation of FOAM near-surface ocean current forecasts using Lagrangian drifting buoys

2012 ◽  
Vol 9 (2) ◽  
pp. 1705-1740
Author(s):  
E. W. Blockley ◽  
M. J. Martin ◽  
P. Hyder
Keyword(s):  
Surface Current ◽  
Surface Velocity ◽  
Ocean Current ◽  
Near Surface ◽  
Surface Ocean ◽  
Forecasting System ◽  
Ocean Forecasting ◽  
Assimilation Scheme ◽  
Drifting Buoys

Abstract. In this study, the quality of near-surface current forecasts from the FOAM ocean forecasting system is assessed using the trajectories of Lagrangian drifting buoys. A method is presented for deriving pseudo-Eulerian estimates of ocean currents from the positions of Surface Velocity Program drifters and the resulting data are compared to velocities observed by the global tropical moored buoy array. A quantitative analysis of the global FOAM velocities is performed for the period 2007 and 2008 using currents derived from over 3000 unique drifters (providing an average of 650 velocity observations per day). A potential bias is identified in the Southern Ocean which appears to be caused by wind-slip in the drifter dataset as a result of drogue loss. The drifter-derived currents are also used to show how the data assimilation scheme and a recent system upgrade impact upon the quality of FOAM current forecasts.

scholarly journals Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 747
Author(s):  
Mai The Vu ◽  
Tat-Hien Le ◽  
Ha Le Nhu Ngoc Thanh ◽  
Tuan-Tu Huynh ◽  
Mien Van ◽  
...  
Keyword(s):  
Control System ◽  
Motion Control ◽  
Optimal Allocation ◽  
Position Control ◽  
Sliding Mode ◽  
Underwater Vehicle ◽  
Ocean Current ◽  
Model Uncertainties ◽  
Control Module ◽  
Dynamic Sliding Mode

Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, in this study, a nonlinear dynamics and robust positioning control of the over-actuated autonomous underwater vehicle (AUV) under the effects of ocean current and model uncertainties are presented. First, a motion equation of the over-actuated AUV under the effects of ocean current disturbances is established, and a trajectory generation of the over-actuated AUV heading angle is constructed based on the line of sight (LOS) algorithm. Second, a dynamic positioning (DP) control system based on motion control and an allocation control is proposed. For this, motion control of the over-actuated AUV based on the dynamic sliding mode control (DSMC) theory is adopted to improve the system robustness under the effects of the ocean current and model uncertainties. In addition, the stability of the system is proved based on Lyapunov criteria. Then, using the generalized forces generated from the motion control module, two different methods for optimal allocation control module: the least square (LS) method and quadratic programming (QP) method are developed to distribute a proper thrust to each thruster of the over-actuated AUV. Simulation studies are conducted to examine the effectiveness and robustness of the proposed DP controller. The results show that the proposed DP controller using the QP algorithm provides higher stability with smaller steady-state error and stronger robustness.

Modeling, simulation, and equilibrium analysis of tethered coaxial dual-rotor ocean current turbines

2021 ◽  
Vol 243 ◽  
pp. 113929
Author(s):  
Rodney Metoyer ◽  
Punnag Chatterjee ◽  
Kelsey Elfering ◽  
Matthew Bryant ◽  
Kenneth Granlund ◽  
...  
Keyword(s):  
Equilibrium Analysis ◽  
Ocean Current ◽  
Modeling Simulation

scholarly journals Numerical Study of an Oscillating-Wing Wingmill for Ocean Current Energy Harvesting: Fluid-Solid-Body Interaction with Feedback Control

2020 ◽  
Vol 9 (1) ◽  
pp. 23
Author(s):  
David Balam-Tamayo ◽  
Carlos Málaga ◽  
Bernardo Figueroa-Espinoza
Keyword(s):  
Energy Harvesting ◽  
Numerical Study ◽  
Angle Of Attack ◽  
Ocean Current ◽  
Control Synthesis ◽  
Dimensionless Number ◽  
Control Law ◽  
Loop Control ◽  
Power Extraction ◽  
Current Energy

The performance and flow around an oscillating foil device for current energy extraction (a wingmill) was studied through numerical simulations. OpenFOAM was used in order to study the two-dimensional (2D) flow around a wingmill. A closed loop control law was coded in order to follow a reference angle of attack. The objective of this control law is to modify the angle of attack in order to enhance the lift force (and increase power extraction). Dimensional analysis suggests a compromise between the generator (or damper) stiffness and actuator/control gains, so a parametric study was carried out while using a new dimensionless number, called B, which represents this compromise. It was found that there is a maximum on the efficiency curve in terms of the aforementioned dimensionless parameter. The lessons that are learned from this fluid-structure and feedback coupling are discussed; this interaction, combined with the feedback dynamics, may trigger dynamic stall, thus decreasing the performance. Moreover, if the control strategy is not carefully selected, then the energy spent on the actuator may affect efficiency considerably. This type of simulation could allow for the system identification, control synthesis, and optimization of energy harvesting devices in future studies.

Disturbance learning controller design for unmanned surface vehicle using LSTM technique of recurrent neural network

2021 ◽  
pp. 1-11
Author(s):  
Sang-Ki Jeong ◽  
Dea-Hyeong Ji ◽  
Ji-Youn Oh ◽  
Jung-Min Seo ◽  
Hyeung-Sik Choi
Keyword(s):  
Neural Network ◽  
Control System ◽  
Flow Velocity ◽  
Recurrent Neural Network ◽  
Pid Controller ◽  
Short Term Memory ◽  
Ocean Currents ◽  
Ocean Current ◽  
Movement Speed ◽  
Marine Research

In this study, to effectively control small unmanned surface vehicles (USVs) for marine research, characteristics of ocean current were learned using the long short-term memory (LSTM) model algorithm of a recurrent neural network (RNN), and ocean currents were predicted. Using the results, a study on the control of USVs was conducted. A control system model of a small USV equipped with two rear thrusters and a front thruster arranged horizontally was designed. The system was also designed to determine the output of the controller by predicting the speed of the following currents and utilizing this data as a system disturbance by learning data from ocean currents using the LSTM algorithm of a RNN. To measure ocean currents on the sea when a small USV moves, the speed and direction of the ship’s movement were measured using speed, azimuth, and location (latitude and longitude) data from GPS. In addition, the movement speed of the fluid with flow velocity is measured using the installed flow velocity measurement sensor. Additionally, a control system was designed to control the movement of the USV using an artificial neural network-PID (ANN-PID) controller [12]. The ANN-PID controller can manage disturbances by adjusting the control gain. Based on these studies, the control results were analyzed, and the control algorithm was verified through a simulation of the applied control system [8, 9].

Advances in ocean current turbine blade design

2021 ◽  
Author(s):  
Hassan Mahfuz ◽  
Nicholas Asseff ◽  
Mohammad Wasim Akram ◽  
Fang Zhou ◽  
Takuya Suzuki ◽  
...  
Keyword(s):  
Turbine Blade ◽  
Ocean Current ◽  
Blade Design ◽  
Turbine Blade Design ◽  
Current Turbine

Spatio-Temporal Deep Learning for Ocean Current Prediction Based on HF Radar Data

2019 ◽  
Author(s):  
Nathachai Thongniran ◽  
Peerapon Vateekul ◽  
Kulsawasd Jitkajornwanich ◽  
Siam Lawawirojwong ◽  
Panu Srestasathiern
Keyword(s):  
Deep Learning ◽  
Radar Data ◽  
Hf Radar ◽  
Ocean Current ◽  
Spatio Temporal

scholarly journals Long-term ocean acidification trends in coastal waters around Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hiroshi Ishida ◽  
Ryosuke S. Isono ◽  
Jun Kita ◽  
Yutaka W. Watanabe
Keyword(s):  
Pacific Ocean ◽  
Ocean Acidification ◽  
Sea Of Japan ◽  
Ocean Current ◽  
The Sea Of Japan ◽  
Marginal Seas ◽  
The Pacific ◽  
Activity Measurements ◽  
The Pacific Ocean

AbstractThis study examines long-term ocean pH data to evaluate ocean acidification (OA) trends at two coastal research institutions located on the Sea of Japan and the Pacific Ocean. These laboratories are located away from the influences of large rivers and major industrial activity. Measurements were performed daily for the past 30 years (1980s–2010s). The average annual ocean pH for both sites showed generally negative trends. These trends were – 0.0032 and – 0.0068 year–1 (p < 0.001) at the Sea of Japan and Pacific Ocean sites, respectively. The trends were superimposed onto approximately 10-year oscillations, which appear to synchronize with the ocean current periodicity. At the Sea of Japan site, the ocean pH in the summer was higher, and the rate of OA was higher than during other seasons. Our results suggest that seasonality and ocean currents influence OA in the coastal areas of open oceans and can affect the coastal regions of marginal seas.

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