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.
The JET 2019-2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major Neutral Beam Injection (NBI) upgrade providing record power in 2019-2020, and tested the technical & procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle physics in the coming D-T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed Shattered Pellet Injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design & operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D-T benefited from the highest D-D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER.
Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.
The pedestal structure, edge transport and linear MHD stability have been analyzed in a series of JET with the ITER-like wall hydrogen (H) and deuterium (D) type I ELMy H-mode plasmas. The pedestal pressure is typically higher in D than in H at the same input power and gas rate, with the difference mainly due to lower density in H than in D (Maggi et al (JET Contributors) 2018 Plasma Phys. Control. Fusion 60 014045). A power balance analysis of the pedestal has shown that higher inter-ELM separatrix loss power is required in H than in D to maintain a similar pedestal top pressure. This is qualitatively consistent with a set of interpretative EDGE2D-EIRENE simulations for H and D plasmas, showing that higher edge particle and heat transport coefficients are needed in H than in D to match the experimental profiles. It has also been concluded that the difference in neutral penetration between H and D leads only to minor changes in the upstream density profiles and with trends opposite to experimental observations. This implies that neutral penetration has a minor role in setting the difference between H and D pedestals, but higher ELM and/or inter-ELM transport are likely to be the main players. The interpretative EDGE2D-EIRENE simulations, with simultaneous upstream and outer divertor target profile constraints, have indicated higher separatrix electron temperature in H than in D for a pair of discharges at low fueling gas rate and similar stored energy (which required higher input power in H than in D at the same gas rate). The isotope dependence of linear MHD pedestal stability has been found to be small, but if a higher separatrix temperature is considered in H than in D, this could lead to destabilization of peeling-ballooning modes and shrinking of the stability boundary, qualitatively consistent with the reduced pedestal confinement in H.
The potential to use liposomes (LIPs) as a cellular model in order to study interactions of cold atmospheric-pressure plasma with cells is herein investigated. Cold atmospheric-pressure plasma is formed by a dielectric-barrier discharge reactor. Large multilamellar vesicle liposomes, consisted of phosphatidylcholine and cholesterol, are prepared by the thin film hydration technique, to encapsulate a small hydrophilic dye, i.e., calcein. The plasma-induced release of calcein from liposomes is then used as a measure of liposome membrane integrity and, consequently, interaction between the cold atmospheric plasma and lipid bilayers. Physical mechanisms leading to membrane disruption are suggested, based on the plasma characterization including gas temperature calculation.
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