Benjamin Sanderse (associate professor in CASA and group leader at CWI in Amsterdam) has been awarded an ERC Consolidator Grant. This personal grant of 2 million euros will be used to tackle a problem that defeats even supercomputers: reliably predicting turbulent flows.
Existing turbulence models are typically derived from physics, based on simple assumptions about how small eddies behave on average, or are data-driven by using machine learning on highly detailed simulations or measurements. These latter models are promising, but require vast amounts of data, are difficult to interpret, and offer no firm guarantees of stability or physical correctness.
In the new project – named SYMBIOSIS – a radical middle way is proposed centered around the key concept of entropy. Entropy is a measure of the direction of processes and indicates what is physically admissible while at the same time it can quantify how much uncertainty there is in a prediction and enables a probabilistic view on turbulence.