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

An Analytical Expression for the Electric Field and Particle Tracing in Modelling of Be Erosion Experiments at the JET ITER-like Wall

A new analytical approximation for the electric potential profile in the presence of an oblique magnetic field and the analytical solution for the particle motion just before the impact with a plasma-facing surface are presented. These approximations are in good agreement with fluid solutions and the corresponding PIC simulations. These expressions were applied to provide effective physical erosion yields for Be, which have in a second step been used in ERO code simulations of spectroscopy at Be limiters of the JET ITER-like wall. These new analytical expressions lead to an increase of the effective physical sputtering yields of Be by deuteron impact up to 30% in comparison with earlier pure numerical simulations. (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

Ion cyclotron resonance heating for tungsten control in various JET H-mode scenarios

Ion cyclotron resonance heating (ICRH) in the hydrogen minority scheme provides central ion heating and acts favorably on the core tungsten transport. Full wave modeling shows that, at medium power level (4 MW), after collisional redistribution, the ratio of power transferred to the ions and the electrons vary little with the minority (hydrogen) concentration n H/n e but the high-Z impurity screening provided by the fast ions temperature increases with the concentration. The power radiated by tungsten in the core of the JET discharges has been analyzed on a large database covering the 2013-2014 campaign. In the baseline scenario with moderate plasma current (I p = 2.5 MA) ICRH modifies efficiently tungsten transport to avoid its accumulation in the plasma centre and, when the ICRH power is increased, the tungsten radiation peaking evolves as predicted by the neo-classical theory. At higher current (3-4 MA), tungsten accumulation can be only avoided with 5 MW of ICRH power with high gas injection rate. For discharges in the hybrid scenario, the strong initial peaking of the density leads to strong tungsten accumulation. When this initial density peaking is slightly reduced, with an ICRH power in excess of 4 MW,very low tungsten concentration in the core (∼10-5) is maintained for 3 s. MHD activity plays a key role in tungsten transport and modulation of the tungsten radiation during a sawtooth cycle is correlated to the fishbone activity triggered by the fast ion pressure gradient

Improved ERO modelling for spectroscopy of physically and chemically assisted eroded beryllium from the JET-ILW

Physical and chemical assisted physical sputtering were characterised by the Be I and Be II line and BeD band emission in the observation chord measuring the sightline integrated emission in front of the inner beryllium limiter at the torus midplane. The 3D local transport and plasma-surface interaction Monte-Carlo modelling (ERO code [18]) is a key for the interpretation of the observations in the vicinity of the shaped solid Be limiter. The plasma parameter variation (density scan) in limiter regime has provided a useful material for the simulation benchmark. The improved background plasma parameters input, the new analytical expression for particle tracking in the sheath region and implementation of the BeD release into ERO has helped to clarify some deviations between modelling and experiments encountered in the previous studies [4,5]. Reproducing the observations provides additional confidence in our ‘ERO-min’ fit for the physical sputtering yields for the plasma-wetted areas based on simulated data

Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions

© 2022, The Author(s), under exclusive licence to Springer Nature Limited.Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.N