Peter Huse Gaarde-Hansen and Christoffer Olesen Mæng, Turbulence reconstruction using machine learning, Bachelor project

Description

This project will investigate the utility of machine learning for the reconstruction of turbulence at unmeasured positions. The investigations will include wind-tunnel experiments to create a dataset upon which the methods will be tested. The machine learning techniques will be compared with existing, physics-based turbulence reconstruction methods. Further investigations using pressure-tap measurements on the wing or extra additions to the inflow may be included to the project, depending on time constraints.

Period	3 Feb 2020 → 8 Jun 2020