Quality assurance for CMS Tracker LV and HV Power Supplies

This work describes the quality assurance measurements that have been carried out on about 2000 Power Supply Units produced in CAEN technology for the CMS Silicon Tracker Detector. The automate procedure and the characteristics of the dedicated Test Fixture developed for this activity are described in details. Magnetic field tolerance and radiation hardness of Tracker power supply units is also discussed at length

Transport analysis of high radiation and high density plasmas in the ASDEX Upgrade tokamak

Future fusion reactors, foreseen in the “European road map” such as DEMO, will operate under more demanding conditions compared to present devices. They will require high divertor and core radiation by impurity seeding to reduce heat loads on divertor target plates. In addition, DEMO will have to work at high core densities to reach adequate fusion performance. The performance of fusion reactors depends on three essential parameters: temperature, density and energy confinement time. The latter characterizes the loss rate due to both radiation and transport processes. The DEMO foreseen scenarios described above were not investigated so far, but are now addressed at the ASDEX Upgrade tokamak. In this work we present the transport analysis of such scenarios. Plasma with high radiation by impurity seeding

Integrated modelling and multiscale gyrokinetic validation study of ETG turbulence in a JET hybrid H-mode scenario

Previous studies with first-principle-based integrated modelling suggested that ETG turbulence may lead to an anti-GyroBohm isotope scaling in JET high-performance hybrid H-mode scenarios. A dedicated comparison study against higher-fidelity turbulence modelling invalidates this claim. Ion-scale turbulence with magnetic field perturbations included, can match the power balance fluxes within temperature gradient error margins. Multiscale gyrokinetic simulations from two distinct codes produce no significant ETG heat flux, demonstrating that simple rules-of-thumb are insufficient criteria for its onset

Role of NBI fuelling in contributing to density peaking between the ICRH and NBI identity plasmas on JET

Density peaking has been studied between an ICRH and NBI identity plasma in JET. The comparison shows that 8 MW of NBI heating/fueling increases the density peaking by a factor of two, being R/L (n) = 0.45 for the ICRH pulse and R/L (n) = 0.93 for the NBI one averaged radially over rho (tor) = 0.4, 0.8. The dimensionless profiles of q, rho *, upsilon *, beta (n) and T (i)/T (e) approximate to 1 were matched within 5% difference except in the central part of the plasma (rho (tor) < 0.3). The difference in the curvature pinch (same q-profile) and thermo-pinch (T (i) = T (e)) between the ICRH and NBI discharges is virtually zero. Both the gyro-kinetic simulations and integrated modelling strongly support the experimental result where the NBI fuelling is the main contributor to the density peaking for this identity pair. It is to be noted here that the integrated modeling does not reproduce the measured electron density profiles, but approximately reproduces the difference in the density profiles between the ICRH and NBI discharge. Based on these modelling results and the analyses, the differences between the two pulses in impurities, fast ions (FIs), toroidal rotation and radiation do not cause any such changes in the background transport that would invalidate the experimental result where the NBI fuelling is the main contributor to the density peaking. This result of R/L (n) increasing by a factor of 2 per 8 MW of NBI power is valid for the ion temperature gradient dominated low power H-mode plasmas. However, some of the physics processes influencing particle transport, like rotation, turbulence and FI content scale with power, and therefore, the simple scaling on the role of the NBI fuelling in JET is not necessarily the same under higher power conditions or in larger devices

Robust impurity detection and tracking for tokamaks

A robust impurity detection and tracking code, able to generate large sets of dust tracks from tokamak camera footage, is presented. This machine learning–based code is tested with cameras from the Joint European Torus, Doublet-III-D, and Magnum-PSI and is able to generate dust tracks with a 65–100% classification accuracy. Moreover, the number dust particles detected from a single camera shot can be up to the order of 1000. Several areas of improvement for the code are highlighted, such as generating more significant training data sets and accounting for selection biases. Although the code is tested with dust in single two-dimensional camera views, it could easily be applied to multiple-camera stereoscopic reconstruction or nondust impurities.</p