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

    Activity: Examinations and supervisionSupervisor activities


    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.
    Period3 Feb 20208 Jun 2020