A power-balance model, with radiation losses from impurities and neutrals, gives a unified description of the density limit (DL) of the stellarator, the L-mode tokamak, and the reversed field pinch (RFP). The model predicts a Sudo-like scaling for the stellarator, a Greenwald- like scaling, alpha I-p(8/9), for the RFP and the ohmic tokamak, a mixed scaling, alpha (PIp4/9)-I-4/9, for the additionally heated L-mode tokamak. In a previous paper (Zanca et al 2017 Nucl. Fusion 57 056010) the model was compared with ohmic tokamak, RFP and stellarator experiments. Here, we address the issue of the DL dependence on heating power in the L-mode tokamak. Experimental data from high-density disrupted L-mode discharges performed at JET, as well as in other machines, arc taken as a term of comparison. The model fits the observed maximum densities better than the pure Greenwald limit.

Block-structured mesh generation techniques have been well addressed in the CFD community for automobile and aerospace studies, and their applicability to magnetic fusion is highly relevant, due to the complexity of the plasma-facing wall structures inside a tokamak device. Typically applied to non-linear simulations of MHD instabilities relevant to magnetically confined fusion, the JOREK code was originally developed with a 2D grid composed of isoparametric bi-cubic Bezier finite elements, that are aligned to the magnetic equilibrium of tokamak plasmas (the third dimension being represented by Fourier harmonics). To improve the applicability of these simulations, the grid-generator has been generalised to provide a robust extension method, using a block-structured mesh approach, which allows the simulations of arbitrary domains of tokamak vacuum vessels. Such boundary-aligned grids require the adaptation of boundary conditions along the edge of the new domain. Demonstrative non-linear simulations of plasma edge instabilities are presented to validate the robustness of the new grid, and future potential physics applications for tokamak plasmas are discussed. The methods presented here may be of interest to the wider community, beyond tokamak physics, wherever imposing arbitrary boundaries to quadrilateral finite elements is required.

The impurity concentration in the tokamak divertor plasma is a necessary input for predictive scaling of divertor detachment, however direct measurements from existing tokamaks in different divertor plasma conditions are limited. To address this, we have applied a recently developed spectroscopic N II line ratio technique for measuring the N concentration in the divertor to a range of H-mode and L-mode plasma from the ASDEX Upgrade and JET tokamaks, respectively. The results from both devices show that as the power crossing the separatrix, P-sep, is increased under otherwise similar core conditions (e.g. density), a higher N concentration is required to achieve the same detachment state. For example, the N concentrations at the start of detachment increase from approximate to 2% to approximate to 9% as P-sep, is increased from approximate to 2.5 MW to approximate to 7 MW. These results tentatively agree with scaling law predictions (e.g. Goldston et al.) motivating a further study examining the parameters which affect the N concentration required to reach detachment. Finally, the N concentrations from spectroscopy and the ratio of D and N gas valve fluxes agree within experimental uncertainty only when the vessel surfaces are fully-loaded with N.

Inconel-600 blocks and stainless steel covers for quartz microbalance crystals from remote corners in the JET-ILW divertor were studied with time-of-flight elastic recoil detection analysis and nuclear reaction analysis to obtain information about the areal densities and depth profiles of elements present in deposited material layers. Surface morphology and the composition of dust particles were examined with scanning electron microscopy and energy-dispersive X-ray spectroscopy. The analyzed components were present in JET during three ITER-like wall campaigns between 2010 and 2017. Deposited layers had a stratified structure, primarily made up of beryllium, carbon and oxygen with varying atomic fractions of deuterium, up to more than 20%. The range of carbon transport from the ribs of the divertor carrier was limited to a few centimeters, and carbon/deuterium co-deposition was indicated on the Inconel blocks. High atomic fractions of deuterium were also found in almost carbon-free layers on the quartz microbalance covers. Layer thicknesses up to more than 1 micrometer were indicated, but typical values were on the order of a few hundred nanometers. Chromium, iron and nickel fractions were less than or around 1% at layer surfaces while increasing close to the layer-substrate interface. The tungsten fraction depended on the proximity of the plasma strike point to the divertor corners. Particles of tungsten, molybdenum and copper with sizes less than or around 1 micrometer were found. Nitrogen, argon and neon were present after plasma edge cooling and disruption mitigation. Oxygen-18 was found on component surfaces after injection, indicating in-vessel oxidation. Compensation of elastic recoil detection data for detection efficiency and ion-induced release of deuterium during the measurement gave quantitative agreement with nuclear reaction analysis, which strengthens the validity of the results.

Hot spots on the divertor tiles at JET result in overestimation of the tile surface temperature which causes unnecessary termination of pulses. However, the appearance of hot spots can also indicate the condition of the divertor tile surfaces. To analyse the behaviour of the hot spots in the outer divertor tiles of JET, a simple image processing algorithm is developed. The algorithm isolates areas of bright pixels in the camera image and compares them to previously identified hot spots. The activity of the hot spots is then linked to values of other signals and parameters in the same time intervals. The operation of the detection algorithm was studied in a limited pulse range with high hot spot activity on the divertor tiles 5, 6 and 7. This allowed us to optimise the values of the controlling parameters. Then, the wider applicability of the method has been demonstrated by the analysis of the hot spot behaviour in a whole experimental campaign.

The analysis of the polarimetry measurements has the aim of validating models (De Marco and Segre 1972 Plasma Phys. 14 245), with a careful attention to the clarification of their limits of application. In this paper a new approximation method is introduced, the so-called special constant Omega direction (SCOD), which gives an analytical solution to the polarimetry exact Stokes model equations. The available approximate solutions (including SCOD) of the polarimetry propagation equations are presented, compared and their application limits determined, using a reference tokamak configuration, which is a simplified equilibrium for a circular tokamak. The SCOD approximation is compared successfully to the Stokes model in the context also of equilibria evaluated for two JET discharges. The approximation methods are analytical or very simple mathematical expressions which can also be used in equilibrium codes for their optimization.

The recently developed Monte-Carlo code ERO2.0 is applied to the modelling of limited and diverted discharges at JET with the ITER-like wall (ILW). The global beryllium (Be) erosion and deposition is simulated and compared to experimental results from passive spectroscopy. For the limiter configuration, it is demonstrated that Be self-sputtering is an important contributor (at least 35%) to the Be erosion. Taking this contribution into account, the ERO2.0 modelling confirms previous evidence that high deuterium (D) surface concentrations of up to similar to 50% atomic fraction provide a reasonable estimate of Be erosion in plasma-wetted areas. For the divertor configuration, it is shown that drifts can have a high impact on the scrape-off layer plasma flows, which in turn affect global Be transport by entrainment and lead to increased migration into the inner divertor. The modelling of the effective erosion yield for different operational phases (ohmic, L- and H-mode) agrees with experimental values within a factor of two, and confirms that the effective erosion yield decreases with increasing heating power and confinement.

Two high performance JET-ILW pulses, pertaining to the 2016 experimental campaign, have been numerically simulated with the self-consistent code COREDIV with the aim of predicting the ELM-averaged power load to the target when extrapolated to DT plasmas. The input power of about 33 MW as well as the total radiated power and the average density are similar in the two pulses, but for one of them the density is provided by combined low gas puff and pellet injection, characterized by low SOL density, for the other one by gas fuelling only, at higher SOT. density. Considering the magnetic configuration of theses pulses and the presence of a significant amount of Ni (not included in the version of the code used for these simulations), a number of assumptions are made in order to reproduce numerically the main core and SOL experimental data. The extrapolation to DT plasmas at the original input power of 33 MW, and taking into account only the thermal component of the alpha-power, does not show any significant difference regarding the power to the target with respect to the DD case. In contrast, the simulations at auxiliary power 40 MW, both at the original I-p = 3 MA and at I-p = 4 MA, show that the power to the target for both pulses is possibly too high to be sustained for about 5 s by strike-point sweeping alone without any control by Ne seeding. Even though the target power load may decrease to about 13-15 MW with substantial Ne seeding for both pulses, as from numerical predictions, there are indications suggesting that the control of the power load may be more critical for the pulse with pellet injection, due to the reduced SOL radiation.

Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays.

Post mortem analysis shows that mid and high atomic number metallic impurities are present in deposits on JET plasma facing components with the highest amount of Ni and W, and therefore the largest sink, being found at the top of the inner divertor. Sources are defined as "continuous" or "specific", in that "continuous" sources arise from ongoing erosion from plasma facing surfaces and "specific" are linked with specific events which decrease over time until they no longer act as a source. This contribution evaluates the sinks and estimates sources, and the balance gives an indication of the dominating processes. Charge exchange neutral erosion is found to be the main source of nickel, whereas erosion of divertor plasma facing components is the main source of tungsten. Specific sources are shown to have little influence over the global mid- and high-Z impurity concentrations in deposits.