First results from recent JET experiments in Hydrogen and Hydrogen-Deuterium plasmas

The hydrogen campaign completed at JET in 2016 has demonstrated isotope ratio control in JET-ILW using gas puffing and pellets for fuelling, Neutral Beam Injection alone or in combination, with D/H spectroscopy as a diagnostic. The plasma properties such as confinement, L-H threshold, density limit depend on the isotope composition. The L-H transition power increases with the hydrogen concentration with a wide plateau in the range 0.2<nH/(nD+nH)<0.8. Energy confinement is significantly lower in hydrogen than in comparable deuterium ELMy H-mode plasmas, suggesting an isotope mass scaling that is stronger than in IPB98(y,2). In L-mode, the isotope dependence of confinement is weaker. The H-mode density limit in hydrogen is up to 35% lower than in heuterium, whilst it is found to be higher in L-mode. The lower ion mass leads to reduced tungsten sputtering in hydrogen plasmas. During the campaign, the nD/(nD+nH) ratio dropped to ~1% in only a few discharges after the last deliberate introduction of deuterium, although it was seen to rise again to ~2% with several seconds of exposure of the divertor tiles to ~10MW of auxiliary heating. Several ICRH scenarios were also tested in hydrogen plasmas

Test of electical resistivity and current diffusion modelling on MAST and JET

Experiments have been carried out on the MAST and JET tokamaks intended to compare the electrical resistivity of the plasma with theoretical formulations. The tests consist of obtaining motional stark effect (MSE) measurements in MHD-free plasmas during plasma current ramp-up (JET and MAST), ramp-down (MAST) and in stationary state (JET and MAST). Simulations of these plasmas are then performed in which the current profile evolution is calculated according to the poloidal field diffusion equation (PFDE) with classical or neoclassical resistivity. Synthetic MSE data are produced in the simulations for direct comparison with the experimental data. It is found that the toroidal current profile evolution modelled using neoclassical resistivity did not match the experimental observations on either device during current ramp-up or ramp-down as concluded from comparison of experimental and synthetic MSE profiles. In these phases, use of neoclassical resistivity in the modelling systematically overestimates the rate of current profile evolution. During the stationary state however, the modelled toroidal current profile matched experimental observations to a high degree of accuracy on both devices using neoclassical resistivity. Whilst no solution to the mismatch in the dynamic phases of the plasma is proposed, it is suggested that some physical process other than MHD which is not captured by the simple diffusive model of current profile evolution is responsible.This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 under grant agreement No 633053 and from the RCUK Energy Programme (Grant number EP/P012450/1)

Validation of D–T fusion power prediction capability against 2021 JET D–T experiments

JET experiments using the fuel mixture envisaged for fusion power plants, deuterium and tritium (D–T), provide a unique opportunity to validate existing D–T fusion power prediction capabilities in support of future device design and operation preparation. The 2021 JET D–T experimental campaign has achieved D–T fusion powers sustained over 5 s in ITER-relevant conditions i.e. operation with the baseline or hybrid scenario in the full metallic wall. In preparation of the 2021 JET D–T experimental campaign, extensive D–T predictive modelling was carried out with several assumptions based on D discharges. To improve the validity of ITER D–T predictive modelling in the future, it is important to use the input data measured from 2021 JET D–T discharges in the present core predictive modelling, and to specify the accuracy of the D–T fusion power prediction in comparison with the experiments. This paper reports on the validation of the core integrated modelling with TRANSP, JINTRAC, and ETS coupled with a quasilinear turbulent transport model (Trapped Gyro Landau Fluid or QualLiKiz) against the measured data in 2021 JET D–T discharges. Detailed simulation settings and the heating and transport models used are described. The D–T fusion power calculated with the interpretive TRANSP runs for 38 D–T discharges (12 baseline and 26 hybrid discharges) reproduced the measured values within 20%. This indicates the additional uncertainties, that could result from the measurement error bars in kinetic profiles, impurity contents and neutron rates, and also from the beam-thermal fusion reaction modelling, are less than 20% in total. The good statistical agreement confirms that we have the capability to accurately calculate the D–T fusion power if correct kinetic profiles are predicted, and indicates that any larger deviation of the D–T fusion power prediction from the measured fusion power could be attributed to the deviation of the predicted kinetic profiles from the measured kinetic profiles in these plasma scenarios. Without any posterior adjustment of the simulation settings, the ratio of predicted D–T fusion power to the measured fusion power was found as 65%–96% for the D–T baseline and 81%–97% for D–T hybrid discharge. Possible reasons for the lower D–T prediction are discussed and future works to improve the fusion power prediction capability are suggested. The D–T predictive modelling results have also been compared to the predictive modelling of the counterpart D discharges, where the key engineering parameters are similar. Features in the predicted kinetic profiles of D–T discharges such as underprediction of ne are also found in the prediction results of the counterpart D discharges, and it leads to similar levels of the normalized neutron rate prediction between the modelling results of D–T and the counterpart D discharges. This implies that the credibility of D–T fusion power prediction could be a priori estimated by the prediction quality of the preparatory D discharges, which will be attempted before actual D–T experiments

New insights into the genetic etiology of Alzheimer’s disease and related dementias

Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele