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Control of Extreme Events in Turbulent Flows with Scientific Machine Learning

CORDIS · observation · Publication date unknown

Control of Extreme Events in Turbulent Flows with Scientific Machine Learning Climate change and the race to decarbonise our society is making extreme events in fluids more prevalent. These are rare events where the flow suddenly takes extreme states far from its normal state. These can be found in any flow systems, such as in the atmosphere with atmospheric blocking causing extreme heatwaves, or in our oceans with rogue waves (waves of extreme heights) capable of capsizing boats, or in engineering flows in hydrogen-based clean combustors with flashback events where the flame suddenly moves back into the injection system. Currently, we cannot accurately predict such extreme events due to several roadblocks. First, the chaotic nature of these turbulent flows makes them hard to predict: any infinitesimal perturbation leads to drastically different evolutions (the butterfly effect). Second, extreme events originate from complex nonlinear interactions

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recordType

award

status

SIGNED

region

EU

value

1499068

unit

EUR