OEDGE Modeling of {sup 13}C Deposition in the Inner Divertor of DIII-D
Bibliographic record
Abstract
Use of carbon in tokamaks leads to a major tritium retention issue due to co-deposition. To investigate this process a low power (no beams) L-mode experiment was performed on DIII-D in which {sup 13}CH{sub 4} was puffed into the main vessel through the toroidally-symmetric pumping plenum at the top of lower single-null discharges. Subsequently, the {sup 13}C content of tiles taken from the vessel wall was measured. The interpretive OEDGE code was used to model the results. It was found that the {sup 13}C deposition pattern is controlled by: (a) source strength of {sup 13}C{sup +}, (b) radial location of the {sup 13}C{sup +} source, (c) D{sub {perpendicular}}, (d) M{sub {parallel}}, the scrape-off layer parallel Mach number. Best agreement was found for (a) {approx}50% conversion efficiency {sup 13}CH{sub 4} {yields} {sup 13}C{sup +}, (b) {sup 13}C{sup +} source {approx}3.5 cm outboard of separatrix near {sup 13}CH{sub 4} injection location, (c)D{sub {perpendicular}} {approx} 0.3 m{sup 2}s{sup -1}, (d) M{sub {parallel}} {approx} 0.4 toward inside.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".