For the first time, researchers at ETH Zurich have successfully automated the modelling of turbulence. Their project relies on fusing reinforcement learning algorithms with turbulent flow simulations on the CSCS supercomputer “Piz Daint”.
The modelling and simulation of turbulent flows is crucial for designing cars and heart valves, predicting the weather, and even retracing the birth of a galaxy. The Greek mathematician, physicist and engineer Archimedes occupied himself with fluid mechanics some 2,000 years ago, and to this day, the complexity of fluid flows is still not fully understood. The physicist Richard Feynman counted turbulence among the most important unsolved problems in classical physics, and it remains an active topic for engineers, scientists and mathematicians alike.
Engineers have to consider the effects of turbulent flows when building an aircraft or a prosthetic heart valve. Meteorologists need to account for them when they forecast the weather, as do astrophysicists when simulating galaxies. Consequently, researchers from these communities have been modelling turbulence and performing flow simulations for more than 60 years.
Source: “ETH researchers compute turbulence with artificial intelligence”, Simone Ulmer, Zurich ETH News
