Enhancement of electrodynamic tether electron current collection using radio frequency power: numerical modeling and measurements
Bibliographic record
Abstract
Tether electron current collection in the Orbital Motion Limited regime is one of the limiting factors in power and thrust generation applications of electro dynamic tethers.Injection of radio frequency power along tethers is considered in order to enhance electron current collection.As a basic assessment tool, Particle-In-Cell modeling of the tether system is performed using a 1-d cylindrical code.Comparison of test electron trajectories shows that the time periodic field distribution created by the RF excitation results in electrons being scattered off their usual OML trajectories, which under some conditions increases their probability of being collected by the tether.Analysis of simulation results reveals that large current enhancements can occur at resonance frequencies of the input reactance (where X\^ = 0), but at the expense of high RF power.Current enhancement is best measured in terms of the relative current variation per unit of RF power dissipated for every 1-meter section of the tether.Optimum enhancements of about 9% per RF watt per meter were obtained by simulation at low frequencies (75 MHz).Similar enhancements were observed during Phase 1 of the experimental measurements on tether samples.Initial experimental results from Phase 2 of the tests are presented in which the RF power was kept constant at a reference plane along the transmission line connecting to a tether sample.These results show some frequency dependence of the current enhancement for a fixed power level.Further measurements are needed •which will control the RF power sent at the tether sample itself, rather than at an upstream position on the transmission line.
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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 | 0.001 |
| 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".