Wind velocity field approximation: Modelling and visualization on real datasets.
INSA Rouen Normandie
Energy and Environment
Approximation of wind velocity field from sparse datasets, taking into account the topography, is a crucial step in order to build wind turbine farm.
Challenges and goals
- Regular approximation of the wind velocity field.
- Optimal visualization of the wind field simulation.
Mathematical and computational methods
The problem of vector field approximation from sparse data emerges in a wide range of fields such as: motion control, computer vision, geometrical analysis, geometrical design, analysis of acoustic or electromagnetic waves, as well as in geophysics, medical imaging, fluid mechanics and so on... Many different approaches have been introduced to solve each specific problem occurring in the above fields of investigation to fit the vector field dataset. In this work, we use a regularized least-square problem defined on a space of potentials.
Results and Benefits
We have developed cutting-edge technologies for rigorous wind velocity field approximation from sparse datasets.
The underlying mathematical techniques form the cornerstone of very challenging collaborations between LMI INSA Rouen and Energy industry.