Numerical modeling of air plasma flow in air-breathing micro-plasma thrusters at atmospheric pressure
Bibliographic record
Abstract
This paper presents a numerical model for air plasma properties, developed to simulate air-breathing micro-magnetoplasmadynamic thrusters at atmospheric pressure. Model equations are derived from literature data for properties of dry air plasma at atmospheric pressure and integrated into a finite volume method that solves the magnetohydrodynamic (MHD) equations, originally developed for conventional magnetoplasmadynamic thrusters (MPDTs). The numerical model, referred to as the arMHD-solver, is validated against experimental and numerical results for conventional MPDTs. This demonstrates ability of the model to simulate thrust generation and flow patterns for various discharge currents in a vacuum with argon as the propellant. First, a micro-sized geometry is evaluated, which is followed by an operation at atmospheric pressure, and finally using air as the propellant. Results show that atmospheric pressure significantly reduces thrust generation and causes a constriction of the exhaust flow. The influence of air as the propellant is small, as expected from previous theoretical considerations. Reverse flow regions are observed along the anode and downstream of the cathode tip, induced by the new conditions. All observed effects are physically explained, demonstrating that the developed arMHD-solver, with its integrated model for air plasma properties, provides meaningful results for simulating air-breathing micro-MPDTs at atmospheric pressure. Furthermore, based on the assumptions made, this study proves the feasibility of the concept for an air-breathing micro-MPDT, as significant thrust generation is calculated. Only technological challenges remain for practical application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".