Bibliographic record
Abstract
One of the key features of a plasma is that the collisional friction resulting from Coulomb interactions decreases with the electron velocity. Therefore, in the presence of a parallel electric field larger than a critical value, electrons with sufficient velocity will be continuously accelerated. These so-called runaway electrons may reach energies on the order of several MeVs and cause serious damage to plasma facing components in ITER - the next large-scale tokamak. The runaway population may be multiplied through knock-on collisions, where an existing runaway electron can transfer a significant fraction of its energy to a secondary electron nearly at rest, while remaining in the runaway region. Understanding of the runaway electron formation processes is crucial in order to develop ways to mitigate them. In this context, modelling of runaway electron dynamics is performed using the 3-D linearized relativistic bounce-averaged electron Fokker-Planck solver LUKE, with a particular emphasis on knock-on collisions of fast electrons on thermal ones, which can lead to an avalanche of relativistic electrons. The theory of bounce-averaged knock-on collisions is derived, and the corresponding operator is implemented in the kinetic solver LUKE. The dependencies of the runaway electron growth rate on the electric field strength, density, temperature and magnetic configuration is investigated, in order to identify the relative importance between primary and secondary runaway generation, the latter resulting from the avalanche process. It is shown that avalanches of runaway electrons can be important even in non-disruptive regimes and this effect may become dominant in the build-up of the highly relativistic electron tail. Owing to their high magnetization, most of the knock-on electrons are born into the magnetic trapping domain in momentum space, which leads to a reduction of the runaway population off the magnetic axis. This accumulates the runaway electrons near the magnetic axis. The dynamics of the trapped electrons in the framework of runaway electron generation is investigated. Finally, the runaway electron formation in Ohmic discharges performed in the Tore Supra and COMPASS tokamaks is modelled with the LUKE code, using global plasma parameters such as parallel electric field and the toroidal MHD equilibrium calculated with the fast integrated modelling code, METIS. Details of the fast electron velocity distribution function are provided as well as quantitative comparison with non-thermal bremsstrahlung for the Tore Supra tokamak.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".