We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model QuaLiKiz. The database covers a wide range of realistic tokamak core parameters. Physical features such as the existence of a critical gradient for the onset of turbulent transport were integrated into the neural network training methodology. We have coupled QLKNN to the tokamak modelling framework JINTRAC and rapid control-oriented tokamak transport solver RAPTOR. The coupled frameworks are demonstrated and validated through application to three JET shots covering a representative spread of H-mode operating space, predicting turbulent transport of energy and particles in the plasma core. JINTRAC-QLKNN and RAPTOR-QLKNN are able to accurately reproduce JINTRAC-QuaLiKiz T i,e and n e profiles, but 3 to 5 orders of magnitude faster. Simulations which take hours are reduced down to only a few tens of seconds. The discrepancy in the final source-driven predicted profiles between QLKNN and QuaLiKiz is on the order 1%-15%. Also the dynamic behaviour was well captured by QLKNN, with differences of only 4%-10% compared to JINTRAC-QuaLiKiz observed at mid-radius, for a study of density buildup following the L-H transition. Deployment of neural network surrogate models in multi-physics integrated tokamak modelling is a promising route towards enabling accurate and fast tokamak scenario optimization, Uncertainty Quantification, and control applications.

Predictability of burning plasmas is a key issue for designing and building credible future fusion devices. In this context, an important effort of physics understanding and guidance is being carried out in parallel to the ongoing JET experimental campaigns in H, D and T by performing analyses and modelling towards an improvement of the understanding of DT physics for the optimization of the JET-DT neutron yield and fusion born alpha particle physics. Extrapolations to JET-DT from recent experiments using the maximum power available have been performed including some of the most sophisticated codes and a broad selection of models. There is a general agreement that 11-15MW of fusion power can be expected in DT for the hybrid and baseline scenarios. On the other hand, in high beta, torque and fast ion fraction conditions, isotope effects could be favourable leading to higher fusion yield. It is shown that alpha particles related physics, such as TAE destabilization or fusion power electron heating, could be studied in ITER relevant JET-DT plasmas.

The present paper offers an overview of the potential of ion cyclotron resonance heating (ICRH) or radio frequency (RF) heating for the DEMO machine. It is found that various suitable heating schemes are available. Similar to ITER and in view of the limited bandwidth of about 10M Hz that can be achieved to ensure optimal functioning of the launcher, it is proposed to make core second harmonic tritium heating the key ion heating scheme, assisted by fundamental cyclotron heating 3 He in the early phase of the discharge; for the present design of DEMO-with a static magnetic field strength of B o = 5.855T-that places the T and 3 He layers in the core for f = 60M Hz and suggests to center the bandwidth around that main operating frequency. In line with earlier studies for hot, dense plasmas in large-size magnetic confinement machines it is shown that good single pass absorption is achieved but that the size as well as operating density and temperature of the machine cause the electrons to absorb a non-negligible fraction of the power away from the core when core ion heating is aimed at. Current drive and alternative heating options are briefly discussed and a dedicated computation is done for the traveling wave antenna, proposed for DEMO in view of its compatibility with substantial antenna-plasma distances. The various tasks that ICRH can fulfill are briefly listed. Finally, the impact of transport and the sensitivity of the obtained results to changes in the machine parameters is commented on.

Auxiliary heating is essential to initiate fusion in future tokamaks. In particular, ion heating tends to maximize the alpha power generation by increasing the thermal ion temperature. In order to simulate the plasma heating by Ion Cyclotron Radio Frequency waves (ICRF), the EVE code, a full-wave code for IC wave propagation, and SPOT, an orbit following Monte-Carlo code combined with the RFOF library which calculates the absorption of wave by ions, have been coupled together. This new package is used for simulating JET plasmas with strong interplay between ICRH and NBI (Neutral Beam Injection). Simulations shows that up to 20% of the neutron rate generated in recent JET D plasmas is due to the synergy between both heating mechanisms. However, the H concentration plays a critical role on such interplay, as beyond 2%, the synergy eciency weakens. Therefore, the control of the H concentration is mandatory for optimizing the fusion reaction rate generation at JET.

Alfvén eigenmodes driven by energetic particles are routinely observed in tokamak plasmas. These modes consist of poloidal harmonics of shear Alfvén waves coupled by inhomogeneity in the magnetic field. Further coupling is introduced by 3D inhomogeneities in the ion density during the assimilation of injected pellets. This additional coupling modifies the Alfvén continuum and discrete eigenmode spectrum. The frequencies of Alfvén eigenmodes drop dramatically when a pellet is injected in JET. From these observations, information about the changes in the ion density caused by a pellet can be inferred. To use Alfvén eigenmodes for MHD spectroscopy of pellet injected plasmas, the 3D MHD codes Stellgap and AE3D were generalised to incorporate 3D density profiles. A model for the expansion of the ionised pellet plasmoid along a magnetic field line was derived from the fluid equations. Thereby, the time evolution of the Alfvén eigenfrequency is reproduced. By comparing the numerical frequency drop of a toroidal Alfvén eigenmode (TAE) to experimental observations, the initial ion density of a cigar-shaped ablation region of length 4cm is estimated to be n * = 6.8×10 22 m −3 at the TAE location (r/a ≈ 0.75). The frequency sweeping of an Alfvén eigenmode ends when the ion density homogenises poloidally. Modelling suggests that the time for poloidal homogenisation of the ion density at the TAE position is τ h = 18 ± 4 ms for inboard pellet injection, and τ h = 26 ± 2 ms for outboard pellet injection. By reproducing the frequency evolution of the elliptical Alfvén eigenmode (EAE), the initial ion density at the EAE location (r/a ≈ 0.9) can be estimated to be n * = 4.8 × 10 22 m −3. Poloidal homogenisation of the ion density takes 2.7 times longer at the EAE location than at the TAE location for both inboard and outboard pellet injection. MHD spectroscopy, Alfvén eigenmodes, pellet injection ‡ See the author list of "Overview of the JET preparation for Deuterium-Tritium Operation" by E.

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