Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Fluid Pressure over Flat Plate of Variable Width01:02

Fluid Pressure over Flat Plate of Variable Width

2.0K
When a flat plate is submerged in a fluid, the fluid exerts pressure on the plate. This pressure can lead to many different phenomena, including drag and buoyancy. To understand the behavior of the fluid over a flat plate of variable width, it is essential to analyze the distribution of the pressure exerted.
The pressure distribution on the plate can be calculated by determining the force that acts on a differential area strip of the plate. Thus, the magnitude of the force is equal to the...
2.0K
Fluid Pressure over Flat Plate of Constant Width01:05

Fluid Pressure over Flat Plate of Constant Width

2.3K
When a body is submerged in water, it experiences fluid pressure acting normal on its surface and distributed over its area. For better design structures, it is crucial to determine the magnitude and location of the resultant force acting on the surface. In the case of a rectangular plate of constant width submerged in water, the pressure increases with depth, resulting in a linearly varying trapezoidal pressure distribution from the upper to the lower edge of the plate.
The resultant force...
2.3K
Laminar and Turbulent Flow01:07

Laminar and Turbulent Flow

10.4K
Fluid dynamics is the study of fluids in motion. Velocity vectors are often used to illustrate fluid motion in applications like meteorology. For example, wind—the fluid motion of air in the atmosphere—can be represented by vectors indicating the speed and direction of the wind at any given point on a map. Another method for representing fluid motion is a streamline. A streamline represents the path of a small volume of fluid as it flows. When the flow pattern changes with time, the...
10.4K
Steady, Laminar Flow Between Parallel Plates01:17

Steady, Laminar Flow Between Parallel Plates

713
Understanding steady, laminar flow between parallel plates is essential for analyzing and designing flow in narrow rectangular channels, commonly found in various water conveyance and drainage systems. The Navier-Stokes equations govern fluid motion and are generally challenging to solve due to their nonlinearity. However, simplifications are possible in certain cases, like the steady laminar flow between parallel plates. For this scenario, we assume steady, incompressible, laminar flow.
713
Steady, Laminar Flow in Circular Tubes01:23

Steady, Laminar Flow in Circular Tubes

909
Hagen-Poiseuille flow describes a viscous fluid's steady, incompressible flow through a cylindrical tube with a constant radius R. This flow profile is often applied to understand fluid transport in narrow channels, such as capillaries. It serves as a foundational example of laminar flow. In this model, cylindrical coordinates (r,θ,z) are used to describe the radial (r), angular (θ), and axial (z) dimensions within the tube. For Hagen-Poiseuille flow, the velocity profile is purely axial,...
909
Fluid Pressure over Curved Plate of Constant Width01:12

Fluid Pressure over Curved Plate of Constant Width

1.8K
When a curved plate of constant width is submerged in a liquid, the pressure acting normal to the plate varies continuously both in magnitude and direction. Calculating the magnitude and location of the resultant force at a point is often challenging for such cases. One of the methods to determine the resultant force and its location involves separately calculating the horizontal and vertical components of the resultant force. This complex calculation can be simplified by representing the...
1.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Design and stability analysis of a new six-floater oscillating water column-based floating offshore wind turbine platform.

Scientific reports·2024
Same author

A regressive machine-learning approach to the non-linear complex FAST model for hybrid floating offshore wind turbines with integrated oscillating water columns.

Scientific reports·2023
Same author

Sensors Data Analysis in Supervisory Control and Data Acquisition (SCADA) Systems to Foresee Failures with an Undetermined Origin.

Sensors (Basel, Switzerland)·2021
Same author

A Modelization of the Propagation of COVID-19 in Regions of Spain and Italy with Evaluation of the Transmission Rates Related to the Intervention Measures.

Biology·2021
Same author

On the Use of Entropy Issues to Evaluate and Control the Transients in Some Epidemic Models.

Entropy (Basel, Switzerland)·2020
Same author

Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator.

Sensors (Basel, Switzerland)·2018

Related Experiment Video

Updated: Dec 27, 2025

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
08:54

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

9.0K

ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements.

Fares M'zoughi1, Izaskun Garrido1, Aitor J Garrido1

  • 1Automatic Control Group-ACG, Department of Automatic Control and Systems Engineering, Faculty of Engineering of Bilbao, Institute of Research and Development of Processes-IIDP, University of the Basque Country-UPV/EHU, Po Rafael Moreno no3, 48013 Bilbao, Spain.

Sensors (Basel, Switzerland)
|March 4, 2020
PubMed
Summary

Artificial neural networks (ANN) improve oscillating water column (OWC) power generation by predicting waves to prevent turbine stalling. This intelligent airflow control enhances energy output in varying sea conditions.

Keywords:
Wells turbineacoustic doppler current profilerairflow controlartificial neural networkoscillating water columnpower generationstalling behaviorwave energy

More Related Videos

Induction of Microstreaming by Nonspherical Bubble Oscillations in an Acoustic Levitation System
08:19

Induction of Microstreaming by Nonspherical Bubble Oscillations in an Acoustic Levitation System

Published on: May 9, 2021

2.6K
Assembly and Characterization of an External Driver for the Generation of Sub-Kilohertz Oscillatory Flow in Microchannels
08:32

Assembly and Characterization of an External Driver for the Generation of Sub-Kilohertz Oscillatory Flow in Microchannels

Published on: January 28, 2022

2.7K

Related Experiment Videos

Last Updated: Dec 27, 2025

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
08:54

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

9.0K
Induction of Microstreaming by Nonspherical Bubble Oscillations in an Acoustic Levitation System
08:19

Induction of Microstreaming by Nonspherical Bubble Oscillations in an Acoustic Levitation System

Published on: May 9, 2021

2.6K
Assembly and Characterization of an External Driver for the Generation of Sub-Kilohertz Oscillatory Flow in Microchannels
08:32

Assembly and Characterization of an External Driver for the Generation of Sub-Kilohertz Oscillatory Flow in Microchannels

Published on: January 28, 2022

2.7K

Area of Science:

  • Renewable Energy Engineering
  • Marine Renewable Energy
  • Control Systems

Background:

  • Oscillating water column (OWC) wave energy converters are susceptible to power loss from turbine stalling caused by extreme wave events.
  • Effective airflow control strategies are crucial for mitigating stalling and optimizing energy extraction in OWC systems.
  • Predictive control methods can enhance the operational efficiency of OWC devices.

Purpose of the Study:

  • To develop and evaluate an artificial neural network (ANN) based airflow control strategy for OWC plants.
  • To enable the OWC system to anticipate incoming waves and proactively adjust turbine airflow velocity.
  • To improve the overall power generation efficiency of OWC devices by preventing stalling.

Main Methods:

  • Training an artificial neural network (ANN) using real-world surface elevation data of incoming waves.
  • Implementing an ANN-based control scheme to predict wave behavior and generate optimal airflow speed references.
  • Utilizing an air valve within the OWC capture chamber to regulate airflow velocity based on ANN outputs.
  • Conducting comparative analyses between the ANN-controlled OWC system and an uncontrolled OWC system under various sea states.
  • Validating the system's performance using measured wave input data and power output from the NEREIDA wave power plant.

Main Results:

  • The ANN-based airflow control effectively distinguishes between different wave types, identifying those likely to cause stalling.
  • The proposed control strategy successfully adjusted airflow velocity to mitigate the stalling phenomenon.
  • Comparative studies demonstrated significant power generation improvements in the ANN-controlled OWC system versus the uncontrolled system.
  • Performance validation using NEREIDA wave power plant data confirmed the effectiveness of the ANN control strategy.

Conclusions:

  • Artificial neural networks offer a powerful tool for predictive airflow control in OWC systems.
  • The developed ANN-based strategy enhances OWC power generation by preventing stalling and optimizing turbine operation.
  • This approach represents a significant advancement in improving the efficiency and reliability of wave energy conversion technology.