Eimear Curran

Machine Learning for Sensing and Control of Dynamic Stall in Realistic Conditions

Project Summary

This project aims to develop an understanding of how machine learning can predict and control dynamic stall on aircraft wings to improve vehicle performance and control. This research firstly focuses on how can dynamic stall be reliably detected with the use of machine learning in realistic environments. This will then develop into how can we design effective strategies to mitigate and control the effects of dynamic stall.

Research Interests

Machine Learning, Aerodynamics

Background

MEng Aerospace Engineering, University of Bath

Supervisors

Dr Sam Bull

Dr Tom Fincham Haines

Dr Ariadne Justi Bertolin

Eimear Curran