Effects of a shallow SAS divertor on detachment in KSTAR
Bibliographic record
Abstract
Abstract For long pulse operation of fusion reactors, it is important to reduce sputter-erosion and power loading of the divertor target by means of plasma detachment. It has been reported that the small-angle-slot (SAS) divertor employed by the DIII-D tokamak can initiate detachment at a relatively low upstream plasma density as it can effectively dissipate heat by concentrating neutrals near the target. Motivated by these findings in DIII-D, we investigated the effects of a SAS-like divertor in KSTAR using SOLPS-ITER simulations without drifts. One remarkable feature revealed by our simulation study is that even a very shallow SAS can lead to a considerably lower heat load on the divertor target than the original flat, open divertor of KSTAR. Deuterium neutrals are concentrated along the divertor separatrix line in the shallow SAS, while deuterium density in the open divertor peaks in the far-scrape-off layer. Furthermore it was found that the neutral density and temperature-drop induced by SAS are both fairly incentive to the depth of the slot. The highest heat dissipation was obtained for a SAS depth of 10.3 cm.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".