"Prediction and control of extreme fluid dynamics with artificial intelligence"

This cross-disciplinary project falls in the following five EPSRC research areas: Artificial intelligence technologies, Combustion engineering, Fluid Dynamics and Aerodynamics, Complexity Science, Numerical Analysis.
High-fidelity simulations of turbulent flows have increasingly been adopted by academia to understand the physics of turbulence (direct numerical simulation, DNS), and by industry (large-eddy simulation, LES) as design tools to minimize costly testing. Whereas the calculation of the statistics of turbulent flows can be accurate, the time and space accurate prediction of extreme events, such as violent turbulent bursts and auto-ignited spots of mixture, has not been achieved yet. No matter how accurate the simulation code is, the time and space prediction of extreme events is limited by the chaotic nature of reacting and non-reacting turbulence. This project will enable the prediction and physical understanding of extreme events by leveraging artificial intelligence and machine learning algorithms with dynamical systems' theory. An optimisation algorithm will be designed and trained to control extreme fluid dynamics, in particular in multi-physical problems that are relevant to energy harvesting and aeronautical propulsion.