Simulations of JET pellet fuelled ITB plasmas
Bibliographic record
Abstract
Experiments were performed on JET where high-density plasmas with an internal transport barrier (ITB) were created by means of combined use of lower hybrid current drive (LHCD) and pellet injection before the barrier formation. Attempts were also made to use pellets to fuel the plasma and to sustain the density during the ITB phase. It was found that shallow pellets ablating in the region r/a ≥ 0.8 and far from the foot of the barrier did not destroy the ITB, whereas deeper pellets penetrating up to 0.6 ≤ r/a ≤ 0.7 affected the barrier and led to its disappearance. Modelling of these experimental scenarios has been performed with transport and fluid turbulence codes. The codes used in the analysis were: JETTO, a 1.5 dimensional transport code, TRB, a global electrostatic fluid turbulence code and CUTIE, a global electromagnetic fluid turbulence code. The results show that for the shallow pellet case all codes reproduce the general features of the experiment, whereas for the deep pellet case, there are differences in the degree of agreement between the different codes and the experiment. Runs performed varying the pellet penetration depth indicate that not only the pellet penetration, but also the barrier strength plays a key role in the dynamics of the pellet-ITB interaction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".