The (e, e 0 p) reaction was studied on targets of C, Fe, and Au at momentum transfers squared Q 2 of 0.6, 1.3, 1.8, and 3.3 GeV 2 in a region of kinematics dominated by quasifree electron-proton scattering. Missing energy and missing momentum distributions are reasonably well described by plane wave impulse approximation calculations with Q 2 and A dependent corrections that measure the attenuation of the final state protons. [S0031-9007 (98) The (e, e 0 p) reaction with nearly free electron-proton kinematics (quasifree) has proven to be a valuable tool to study the propagation of nucleons in the nuclear medium [1][2][3]. The relatively weak interaction of the electron with the nucleus allows the electrons to penetrate the nuclear interior and knock out protons. These studies complement nucleon-induced measurements of proton propagation in nuclei which give more emphasis to the nuclear surface. This paper reports the first results of a systematic study of the quasifree knockout of protons of 300-1800 MeV kinetic energy from carbon, iron, and gold targets. This energy range includes the minimum of the nucleon-nucleon (N-N) total cross section, the rapid rise in this cross section with energy above the pion production threshold, and extends to the long plateau in the energy dependence of the N-N total cross section. These features of the N-N interaction would be expected to be reflected in the energy dependence of attenuation of protons as they pass 5072 0031-9007͞98͞80(23)͞5072(5)$15.00

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.

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