In June 2025, Dr. Tristan Revaz completed his Ph.D., presenting research that advances the understanding of wind turbine wake behavior and power efficiency using large-eddy simulations and analytical modelling.
In his Ph.D. thesis entitled “Understanding Wind Turbine Flows and Power Efficiency: Numerical and Theoretical Studies,” Dr. Revaz advanced the understanding of wind turbine aerodynamics and performance using large-eddy simulations. He developed and validated several numerical tools for wind turbine modelling, including a coupled LES–BEM framework for airfoil characterization and optimized actuator-disk LES implementations. He then investigated how base-flow characteristics—such as terrain-induced pressure-gradient effects and incoming turbulence intensity—shape wake behavior and turbine power efficiency, revealing a clear relationship between wake dynamics and performance. Building on these findings, he developed analytical models that account for pressure-gradient effects and turbulence characteristics to improve predictions of turbine wakes and power in complex terrain, demonstrating markedly enhanced accuracy compared to classical approaches.
