Author/Authors :
Zehetbauer، نويسنده , , Th and Pautasso، نويسنده , , G and Tichmann، نويسنده , , C and Egorov، نويسنده , , S and Lorenz، نويسنده , , A and Mertens، نويسنده , , V and Neu، نويسنده , , G and Raupp، نويسنده , , G and Treutterer، نويسنده , , W and Zasche، نويسنده , , D، نويسنده ,
Abstract :
A neural network for prediction of disruptions has been developed at ASDEX Upgrade with the goal to mitigate or avoid these. The novel idea is to compute the remaining time-to-disruption to indicate the stability level of the discharge. The neural network has been specified, trained and then implemented within the real-time plasma control system. The current version of the system terminates the discharge with an impurity pellet when the computed time-to-disruption falls below a threshold of 80 ms. Routine operation shows that disruptions are recognized reliably. Vessel currents and forces are considerably reduced. The system will be enhanced to avoid disruptions with a soft landing initiated in time.
