1. Artificial Neural Network (ANN) modeling of the pulsed heat load during ITER CS magnet operation
- Author
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Antonio Froio, Roberto Zanino, L. Savoldi Richard, Roberto Bonifetto, Stefano Carli, and Arnaud Foussat
- Subjects
Materials science ,Artificial neural network ,Nuclear engineering ,Artificial Neural Networks ,Nuclear fusion ,ITER ,Superconducting magnets ,Central Solenoid ,Pulsed heat load ,General Physics and Astronomy ,Solenoid ,Plasma ,Magnet ,General Materials Science ,Transient (oscillation) ,Heat load - Abstract
Artificial Neural Networks (ANNs) are applied to the development of a simplified transient model of the ITER Central Solenoid (CS), aiming at predicting the evolution of the pulsed heat load from the CS to the LHe bath during plasma operation. The ANNs are trained using the thermal–hydraulic evolution in the CS, computed with the 4C code, due to AC losses. The capability of the ANN model to predict the heat load to the LHe bath is successfully demonstrated in the case of different transients, among which a nominal plasma operating scenario. The gain in speed of the simplified model with respect to the 4C code results is by order of magnitudes, with a small loss of accuracy.
- Published
- 2014
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