Sustained ELM mitigation has been achieved on MAST and AUG using RMPs with a range of toroidal mode numbers over a wide region of low to medium collisionality discharges. The ELM energy loss and peak heat loads at the divertor targets have been reduced. The ELM mitigation phase is typically associated with a drop in plasma density and overall stored energy. In one particular scenario on MAST, by carefully adjusting the fuelling it has been possible to counteract the drop in density and to produce plasmas with mitigated ELMs, reduced peak divertor heat flux and with minimal degradation in pedestal height and confined energy. While the applied resonant magnetic perturbation field (b r res ) can be a good indicator for the onset of ELM mitigation on MAST and AUG there are some cases where this is not the case and which clearly emphasise the need to take into account the plasma response to the applied perturbations. The plasma response calculations show that the increase in ELM frequency is correlated with the size of the edge peelingtearing like response of the plasma and the distortions of the plasma boundary in the Xpoint region. In many cases the RMPs act to increase the frequency of type I ELMs, however, there are examples where the type I ELMs are suppressed and there is a transition to a small or type IV ELM-ing regime.

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.

Effect of the relative shift between the electron density and temperature pedestal position on the pedestal stability in JET-ILW and comparison with JET-C stability, when the relative shift is reduced. This has been ascribed mainly to the increase of the edge bootstrap current, and to minor effects related to the increase of the pedestal pressure gradient and narrowing of the pedestal pressure width. Pedestal predictive model EUROPED shows a qualitative agreement with experiment, especially for low values of the relative shift.

Abstract. This paper presents turbulence investigations in the scrape off layer (SOL) of ASDEX Upgrade in Ohmic, L-mode and H-mode discharges using electrostatic and electromagnetic probes. Detailed studies are performed on small scale turbulence and on ELM filaments. Simultaneous measurements of floating and plasma potential fluctuations revealed significant differences between these quantities. Large errors can occur when the electric field is extracted from floating potential measurements, even in Ohmic discharges. Turbulence studies in Ohmic plasmas show the existence of density holes inside the separatrix and blobs outside. Close to the separatrix a reversal of the poloidal blob propagation velocity occurs. Investigations on the Reynolds stress in the scrape-off layer show its importance for the momentum transport in L-mode while its impact for momentum transport during ELMs in H-mode is rather small. In the far SOL the electron density and temperature were measured during type-I ELMy H-mode at ASDEX Upgrade resolving ELM filaments. Strong density peaks and temperatures of several 10 eV were detected during the ELM events. Additional investigations on the ions in the filaments by a retarding field analyzer indicate ion temperatures of 50-80 eV. ELMs expel also current concentrated in filaments into the scrape off layer. Furthermore discharges with small ELMs were studied. In N 2 seeded discharges the type-I ELM frequency rises and the ELM duration decreases. For discharges with small type-II ELMs the mean turbulent radial particle flux is increased over the mean particle flux in type-I ELM discharges at otherwise similar plasma parameters.