Numerical assessment of the new V-shape small-angle slot divertor on DIII-D
Bibliographic record
Abstract
The small-angle slot (SAS) divertor of the DIII-D tokamak, and its upcoming upgrade, the V-shape small-angle slot (SAS-V) divertor, are numerically investigated using the SOLPS-ITER code package, including the effect of particle drifts, for a range of plasma density, heating power, strike point position in the slot, and for both magnetic field directions. The simulations show that the electron temperature near the strike point is reduced in SAS-V compared to SAS, for both magnetic field directions, such that SAS-V achieves divertor detachment at a lower value of the outboard mid-plane separatrix electron density. The detachment threshold is lower because the V-shape focuses recycling neutrals on the V-end, densifying and cooling the plasma in the slot. At sufficiently high density, the V-shape also reduces the radial gradient of the temperature profile at the target, which in turns reduces the radial electric field and the E × B drift velocities, further densifying and cooling the plasma in the slot and leading to detachment. The V-shape effect, however, is reduced for higher heating power. With more heating power, the detachment density increases, reducing the ionization mean free path of recycled neutrals, which therefore become less sensitive to target shape changes. This suggests that in a fusion reactor, where the heating power is high, optimization of the divertor target shape needs to be combined with other strategies to lower the detachment density, such as in-slot injection of low- Z impurities.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".