Metal impurity transport control in JET H-mode plasmas with central ion cyclotron radiofrequency power injection
Bibliographic record
Abstract
The scan of ion cyclotron resonant heating (ICRH) power has been used to systematically study the pump out effect of central electron heating on impurities such as Ni and Mo in H-mode low collisionality discharges in JET. The transport parameters of Ni and Mo have been measured by introducing a transient perturbation on their densities via the laser blow off technique. Without ICRH Ni and Mo density profiles are typically peaked. The application of ICRH induces on Ni and Mo in the plasma centre (at normalized poloidal flux ρ = 0.2) an outward drift approximately proportional to the amount of injected power. Above a threshold of ICRH power of about 3 MW in the specific case the radial flow of Ni and Mo changes from inwards to outwards and the impurity profiles, extrapolated to stationary conditions, become hollow. At mid-radius the impurity profiles become flat or only slightly hollow. In the plasma centre the variation of the convection-to-diffusivity ratio v/D of Ni is particularly well correlated with the change in the ion temperature gradient in qualitative agreement with the neoclassical theory. However, the experimental radial velocity is larger than the neoclassical one by up to one order of magnitude. Gyrokinetic simulations of the radial impurity fluxes induced by electrostatic turbulence do not foresee a flow reversal in the analysed discharges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".