Data-driven profile prediction for DIII-D.
- Resource Type
- Article
- Authors
- Abbate, J.; Conlin, R.; Kolemen, E.
- Source
- Nuclear Fusion. Apr2021, Vol. 61 Issue 4, p1-12. 12p.
- Subject
- *REAL-time control
*FORECASTING
*PHYSICISTS
*ACTUATORS
- Language
- ISSN
- 0029-5515
A new, fully data-driven algorithm has been developed that uses a neural network to predict plasma profiles on a scale of τE into the future given an actuator trajectory and the plasma state history. The model was trained and tested on DIII-D data from the 2013–2018 experimental campaigns. The model runs in tens of milliseconds and is very simple to use. This makes it a potentially useful tool for operators and physicists when planning plasma scenarios. It is also fast enough to be used for real-time model-predictive control. [ABSTRACT FROM AUTHOR]