ITER fast ion confinement in the presence of the European test blanket module

This paper addresses the confinement of thermonuclear alpha particles and neutral beam injected deuterons in the 15 MA Q = 10 inductive scenario in the presence of the magnetic perturbation caused by the helium cooled pebble bed test blanket module using the vacuum approximation. Both the flat top phase and plasma ramp-up are studied. The transport of fast ions is calculated using the Monte Carlo guiding center orbit-following code ASCOT. A detailed three-dimensional wall, derived from the ITER blanket module CAD data, is used for evaluating the fast ion wall loads. The effect of the test blanket module is studied for both overall confinement and possible hot spots. The study indicates that the test blanket modules do not significantly deteriorate the fast ion confinement

ITER fast ion confinement in the presence of the European test blanket module

This paper addresses the confinement of thermonuclear alpha particles and neutral beam injected deuterons in the 15 MA Q = 10 inductive scenario in the presence of the magnetic perturbation caused by the helium cooled pebble bed test blanket module using the vacuum approximation. Both the flat top phase and plasma ramp-up are studied. The transport of fast ions is calculated using the Monte Carlo guiding center orbit-following code ASCOT. A detailed three-dimensional wall, derived from the ITER blanket module CAD data, is used for evaluating the fast ion wall loads. The effect of the test blanket module is studied for both overall confinement and possible hot spots. The study indicates that the test blanket modules do not significantly deteriorate the fast ion confinement

Disruption prediction with artificial intelligence techniques in tokamak plasmas

In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures