Machine learning facilitates “turbulence tracking” in fusion reactors

A new approach sheds light on the behavior of turbulent structures that can affect the energy generated during fusion reactions, with implications for reactor design.

alternative energy artificial intelligence computer science and technology energy fusion machine machine learning nuclear science and engineering plasma science and fusion center renewable-energy research school of engineering school of science sustainability tracking