Design and implementation of low-power low-cost quasi steady-state magnetoplasmadynamic propulsion using Ar-He and N<SUB align="right">2-He gas mixtures
Bibliographic record
Abstract
Current miniature plasma propulsion technologies use ion or Hall propulsion to provide thrust for miniature satellites.The problem with ion and Hall thrusters is the low thrust-to-power ratio (30 mN/kW-50 mN/kW), and it is not enough for high-speed manoeuvres in deep-space missions.Alternatively, magnetoplasmadynamic propulsion provides higher thrust to miniature satellites than ion thrusters without the increase in mass.Magnetoplasmadynamic propulsion is a technology that the plasma is accelerated electromagnetically.This research investigates the design and performance of a low-cost magnetoplasmadynamic thruster built for micro and nanosatellites.Gas mixtures are tested in this research to observe any improvement in the overall performance.The gases used in the thruster are pure helium, nitrogen and argon; with gas mixtures of 50% helium -50% nitrogen and 50% helium -50% argon.The specific impulse, impulse bit, thrust efficiency and thrust-weight ratios of 50% helium -50% nitrogen are 801 seconds, 6.29 μN•s, 19.8% and 15.72 mN/kg, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".