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physics.flu-dyn2022
Modelling spatiotemporal turbulent dynamics with the convolutional autoencoder echo state network
Alberto Racca, Nguyen Anh Khoa Doan, Luca Magri
The spatiotemporal dynamics of turbulent flows is chaotic and difficult to predict. This makes the design of accurate and stable reduced-order models challenging. The overarching o…
physics.flu-dyn2022★ 2 cited
Data-driven prediction and control of extreme events in a chaotic flow
Alberto Racca, Luca Magri
An extreme event is a sudden and violent change in the state of a nonlinear system. In fluid dynamics, extreme events can have adverse effects on the system's optimal design and op…
physics.flu-dyn2022
Statistical prediction of extreme events from small datasets
Alberto Racca, Luca Magri
We propose Echo State Networks (ESNs) to predict the statistics of extreme events in a turbulent flow. We train the ESNs on small datasets that lack information about the extreme e…