Transport of Dispersed Tungsten Dust in the STOR-M Plasma
Bibliographic record
Abstract
Transport of dust particles in tokamak discharges is related to the safe operation of a fusion reactor since dusts in plasma pose a safety risk, particularly when they are tritiated. Since STOR-M tokamak discharge does not produce a significant amount of dust particles, a dust dispenser [1] has been designed, calibrated, and recently installed to study the transport of W-particles in the STOR-M tokamak plasma (R/a=46/12cm, Ip=20-30kA, Bt~1T). The dispenser is mounted on the top of the STOR-M tokamak. The dispensed spherical dust particle plume falls under gravity into the STOR-M chamber. The STOR-M discharge is initiated at various chosen delay times, td, after the dispenser is activated. The glow from W-particles in the STOR-M plasma is captured using a fast video camera operated at ~2156 frames/s. The trajectory and velocity of the identified particles are analyzed using velocimetry software. In addition, an Ocean Optics spectrometer is used to monitor line emission intensities from the W and other impurities. It has been found that the W-particles have an appreciable toroidal velocity in the direction opposing the tokamak discharge current direction. In the previous studies, Ion Doppler Spectroscopy (IDS) was used to measure the plasma flow velocity in STOR-M. It has been found that the plasma has a characteristic flow velocity at various radii [2]. When the STOR-M discharge current was configured to reverse the direction, the plasma flow changed the direction as well. In the planned studies, plasma flow velocity and the W-dust drift velocity will be measured simultaneously. The planned experiments are expected to enhance our understanding of the dust transport mechanism in a tokamak plasma.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".