EETimes - Machine Learning Improves Fusion Modeling

Researchers at MIT are employing machine learning techniques to better understand turbulent plasma phenomena in fusion devices. According to MIT News, a new deep learning framework was developed that leverages artificial neural networks to represent a reduced turbulence theory. The research is described in two papers, published in Physical Review E and Physics of Plasmas. If researchers hope to control fusion for energy production, they need a better understanding of the turbulent motion of ions and electrons in plasmas moving through fusion reactors. The field lines of toroidal structures known as tokamaks force the plasma particles; the intent is to confine them long enough to produce significant net energy gains, but that's a challenge with extraordinarily high temperatures but also small spaces.