Investigating Atmospheric Turbulence in the Near Wake of Wind Turbines Using a UAV-Based Platform

Position Start Date: Subject to Availability
Application Deadline: Open Until Filled

Description:

The accurate measurement of atmospheric turbulence in complex environments such as wind turbine wakes remains a major challenge for the wind energy community. In the WiRE Laboratory at EPFL, we employ advanced airborne sensing technologies to explore new pathways in wind energy research.

This project will leverage an existing multirotor UAV-based measurement platform, capable of acquiring high-resolution time series of the three components of the wind velocity vector and temperature in the atmospheric boundary layer (ABL). The UAV integrates a fast-response multihole pressure probe, an inertial measurement unit, and a thermocouple, enabling unprecedented measurement accuracy and spatial flexibility.

Building upon prior successful applications of the platform [example: https://journals.ametsoc.org/view/journals/atot/36/6/jtech-d-17-0220.1.xml], the current project will extend the application of the UAV to investigate turbulent structures in the near wake region of utility-scale wind turbines. The goal is to deepen our understanding of the spatial and temporal characteristics of ABL turbulence downstream of turbine rotors.

Your responsibilities:

  • Conduct UAV-based atmospheric measurements near full-scale wind turbines
  • Perform synchronized data acquisition and quality control
  • Analyze wind velocity and temperature time series using existing reconstruction methodologies
  • Collaborate with the WiRE Lab team to interpret turbulence characteristics and spatial patterns

Learning outcomes:

  • Practical experience with a cutting-edge UAV-based turbulence measurement platform
  • Advanced skills in data acquisition and postprocessing of high-frequency atmospheric measurements
  • Exposure to field operations in complex terrain and wind energy research environments
  • Development of independent research and scientific communication skills

Experience with coding (e.g., LabVIEW, Matlab) and a solid background in fluid mechanics and/or atmospheric science will be a plus.

To express interest and obtain more information about the project, please contact:

Dr. Amr Khedr
Email: [email protected]

(Please include in cc the lab supervisor Prof. Fernando Portè-Agel at [email protected])