A pulsed high-current plasma beam under external and self-induced magnetic confinement in a linear device
Bibliographic record
Abstract
Abstract The previously developed governing equations for Magnetic Inertial Confinement Fusion, which combines the advantages of both magnetic and inertial confinement approaches, are improved to analyse a plasma beam in a linear device assisted by an external magnetic field. The equations are applied to simulate a steady state plasma beam sustained by a DC power supply as well as a transient beam generated by a separate pulsed discharge superimposed on the steady-state plasma. The calculated increase of plasma density during the pulse from the steady-state condition is compared with measurements using a laser interferometer at a relatively low voltage supply of 150 V for the pulses. The numerical and test results are found to agree within 20%. When the voltage rises, plasma instability is observed. This issue is inherent due to the use of a solid positive target electrode that blocks the plasma flow in the axial direction. As a remedy, additional tests were carried out using a hollow target electrode in a two-circuit design (to permit free gas flow in the axial direction) by replacing the DC power with transient, pulsed, high-voltage sources for plasma initiation and beam formation. These enhancements were successful in suppressing the instabilities. The peak plasma density was calculated at ∼10 22 m −3 for confinement times of the order of 1 ms. These results lie between the extremes for the current leading approaches yet are achieved for a more compact and inexpensive linear device.
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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 | 0.000 | 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".