Machine learning techniques were used to train a model that optimizes the safe rampdown of fusion energy reactors. New research from the DIII-D National Fusion Facility.
Research
Following experiments at the DIII-D National Fusion Facility, an improved model achieves better accuracy in describing particle behaviors in fusion environment.
New research shows how to improve predictive modelling of power exhaust in fusion reactors. Experiments performed at the DIII-D National Fusion Facility and led by the Fusion team at ORNL.
A big project is coming to fruition! Combining our fusion energy experiment with a dedicated data network and supercomputing facilities is enabling new methods to solve research challenges faster than ever.
Machine learning techniques predict optimum fusion energy scenarios faster than ever before. Research from the DIII-D National Fusion Facility.
Figuring out how tungsten moves through a fusion energy device is important in order to design reactors. Research at the DIII-D National Fusion Facility developed a new approach to modeling that can make it easier to get accurate predictions.