This paper reports the successful installation of the JET ITER-like Wall and the realisation of its technical objectives. It also presents an overview of the planned experimental programme which has been optimised to exploit the new wall and other JET enhancement in 2011/12. IntroductionThe ITER reference materials [pitts] have been tested in isolation in tokamaks, plasma simulators, ion beams and high heat flux test beds. However, an integrated test demonstrating both acceptable tritium retention, predicted to be one to two orders of magnitude lower than for a carbon wall [roth], and an ability to operate a large high power tokamak within the limits set by these materials has not yet been carried out. The ITER-like Wall now installed in JET by remote handling comprises solid beryllium limiters and a combination of bulk W and Wcoated CFC divertor tiles.Work is also well advanced in defining the 2011/12 JET experimental programme and setting up the teams. A phased approach will be adopted which maximises the scientific output early in the programme on the basic materials and fuel retention questions whilst minimising the risk associated with operation in an all metal machine. However, re-establishing H-modes at similar power levels to those with the carbon walls is a priority for establishing a reference database. The JET upgrades also include an increase in neutral beam heating power, up to 35MW for 20s [ciric], this has led to a requirement that the most critical first wall Be and W components are monitored in real time by an appropriate imaging protection system [Alves, Jouve, Stephen]. In the main chamber, an array of thermocouples has been fitted to unambiguously monitor the bulk temperature of critical tiles. Before this upgrade, only a divertor system was available which proved essential for interpretation of IR data [Eich] and this will be even more the case with an all metal wall due to reflection and uncertain emissivity. Safe expansion of operating space will also be a priority. Experiments will have to be carefully managed if they have the potential to jeopardise interpretation of the long term samples which are planned to be removed in a 2012 intervention. Here the concern is that

Work is in progress to completely replace, in 2008/9, the existing JET CFC tiles with a configuration of plasma facing materials consistent with the ITER design. The ITER-like Wall (ILW) will be created with a combination of beryllium (Be), tungsten (W), W-Coated CFC and Be-Coated inconel tiles, with the material depending on the local anticipated heat flux and geometry. It is part of an integrated package of JET enhancements whose aim is to develop an understanding of the ITER materials issues and develop the techniques required to operate with inductive and advanced scenarios as close as possible to ITER parameters. Over 4000 tiles will be replaced and the ILW will accommodate additional heating up to at least 50 MW for 10 s. This paper describes the scientific background to the project, the technical objectives, the material configuration selected, the R&D behind the practical realisation of the objectives and the generic problems associated with the Be tiles (power handling capacity and disruption induced eddy currents). One of the objectives is to maintain or improve the existing CFC tile power handling performance which has been achieved in most cases by hiding bolt holes, optimising tile size and profile and introducing castellations on plasma facing surfaces.

The evaluation of hydrogenic retention in present tokamaks is of crucial importance to estimate the expected tritium (T) vessel inventory in ITER, limited from safety considerations to 350g. In the framework of the European Task Force on Plasma Wall Interaction (EU TF on PWI) efforts are underway to investigate gas balance and fuel retention during discharges, and to compare the data obtained with those from post-mortem analysis of in-vessel components exposed over whole experimental campaigns. This paper summarizes the principal findings from coordinated studies on gas balance and fuel retention from a number of European tokamaks, viz. ASDEX-Upgrade (AUG), JET, TEXTOR and Tore Supra (TS). For most devices, the long-term retention fraction deduced from integrated particle balance is ∼ 10-20 %. This is larger than the ~3-4% deduced from post mortem analysis of plasma facing components (PFCs). However, from the database available for tokamaks with their main PFCs made of carbon, the important conclusion is that the T inventory limit (set by the working guideline for operations) could be reached in ITER within fewer than 100 discharges. This, therefore, would seriously impact on operation of the device unless efficient T removal processes were developed.

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.

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