Application of high frequency biasing and its effect in STOR-M tokamak
Bibliographic record
Abstract
A pulsed oscillating power amplifier has been developed to apply high frequency biasing voltage to an electrode at the edge of the STOR-M tokamak plasma. The power amplifier can deliver a peak-to-peak oscillating voltage ±60 V and current 30 A within the frequency range 1 kHz–50 kHz. The electrode is located in the equatorial plane at radius ρ = 0.88. The frequency of the applied voltage has been varied between discharges. It is observed that the plasma density and soft x-ray intensity from the plasma core region usually increase at lower frequency regime 1 kHz–5 kHz as well as relatively higher frequency regime 20 kHz–25 kHz but seldom increase in between them. Increment of τ \! E has been observed 40% and 20% for the frequency regimes of 1 kHz–5 kHz and 20 kHz–25 kHz, respectively, and τ \! p increment is 25% for both frequency regimes. Transport simulation has been carried out using the ASTRA simulation code for STOR-M tokamak parameters to understand the physical process behind experimental observations at the higher frequency branch. The model is based on geodesic acoustic mode(GAM) excitement at resonance frequency associated with Ware-pinch due to the oscillating electric field produced by biasing voltage, which can suppress anomalous transport. Simulation results reproduce the experimental trends quite well in terms of the density, particle confinement, as well as energy confinement time evolution. All the results indicate that high frequency biasing is capable of improving confinement efficiently.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".