Numerical and experimental optimisation of a tidal turbine (OPTIDE)

PhD / Long term visitor's project

Velocity field in the equatorial plane of a cross-flow tidal turbine and streamlines. Result of a 3D RANS simulation obtained by P.-L. Delafin at LEGI.
Velocity field in the equatorial plane of a cross-flow tidal turbine and streamlines. Result of a 3D RANS simulation obtained by P.-L. Delafin at LEGI.

Among hydrokinetic turbines which operate without extensive surrounding structure and can be placed directly in the currents, vertical-axis or cross-flow tidal turbines (CFTTs) are known to provide higher area-based power densities than their competitors. They operate independently of the inflow direction and promise to be robust and of a simple design.


Despite the numerous advantages of such systems, CFTTs have still not reached their full potential of application due to several limitations. Because of their particular design, CFTTs blades undergo continuously varying angles of attack in the stream, resulting in alternating hydrodynamic load. These load variations increase in particular for low rotational speeds. Although low rotor speeds would be advantageous for fish compatibility, as strike events become less probable, variable loads can lead to structural damage, such as fatigue failure and therefore represent a major concern. One key approach to overcome this issue is to balance the angle of attack by constantly adjusting the blades pitch during the cycle. The OPTIDE project aims to explore the effect of variable pitch blades on the functioning of CFTTs. At the turbine scale, it is of high interest to consider a systematic optimisation of the pitch motion law, taking into account two key points: the increase in the turbine hydrodynamic efficiency, and in counterpart, the energy costs for the pitch actuation. At a larger scale, the effect of variable pitch on the wake of the turbine must be considered in the perspective of tidal farm applications.


The OPTIDE project aims at learning about these points through experiments and numerical simulations. Experiments (flume tank tests at the Laboratory for Fluid Dynamics and Technical Flows) will play a key role in testing quickly a large number of pitching laws, enabling the use of an optimisation method based on genetic algorithms. State of the art instrumentation, customized and provided by the second project partner, the Laboratory of Electric Drive Systems, will generate data for the turbine performance and the velocity field in the turbine wake. Additionally, embedded strain sensors will give access to the blade stress at some specific locations and a digital twin will use these data as an input to predict the overall stress distribution within the blades based on a finite-element model of the turbine. This will help gaining a deeper understanding of the fluid / structure interaction for such application. Additional combined bending-torsion tests will provide information about the load cycles and the expected fatigue life of the structure. A determination of an optimised blade shape for the turbine and high-fidelity simulations (Computational Fluid Dynamics with OpenFOAM, performed at the LEGI) will provide detailed information of the entire flow field. The unusual coupling of experiments and simulations (simulations are generally used to reduce the number of experiments) will provide an efficient way to find optimal pitching laws and understand the underlying mechanisms leading to them.


The knowledge gained from the OPTIDE project is expected to provide a clearer view on the potential of variable pitch blades for industrial application in CFTT. Especially, it will show if it is worth pushing further in this direction considering high power density tidal farm installations.


Pierre-Luc Delafin (Project PI)

Stefan Hoerner (co-PI and visitor)
Karla Isabella Ruiz Hussmann (PhD student)



Institute of fluid dynamics and thermodynamics, and Laboratory of electric drive systems from the Otto-von-Guericke University of Magdeburg, Germany


Otto-von-Guericke University of Magdeburg
Deutsche Forschungsgemeinschaft DFG