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Record W4361275750 · doi:10.1007/s44205-023-00048-9

A theoretical thrust density limit for Hall thrusters

2023· article· en· W4361275750 on OpenAlexaff
Jacob Simmonds, Yevgeny Raitses, A. I. Smolyakov

Bibliographic record

VenueJournal of Electric Propulsion · 2023
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of Saskatchewan
FundersAir Force Office of Scientific ResearchU.S. Department of Energy
KeywordsThrustMagnetic fieldHall effectPhysicsLimit (mathematics)Electron densityElectronMathematicsThermodynamicsNuclear physicsMathematical analysisQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract Hall Thrusters typically operate at thrust densities on the order of 10 N/m $$^2$$ 2 , which appear to be orders of magnitude below the thrust density limits suggested in previous literature. These limits have been considered here and each component of thrust density is analyzed to demonstrate the relative contribution to the total thrust density. Dependencies of the thrust density limits upon the thruster geometry, electron mobility, and the applied magnetic field are revealed and compared with experimental measurements of thrust density. This analysis reveals that with conventional applied magnetic field strengths, Hall thruster thrust density appears to be on the order of 1000 N/m $$^2$$ 2 . It is shown that this limit can be further increased through higher applied magnetic fields, applied voltage, and suppression of anomalous electron transport. This suggests Hall thrusters can be made much more compact and operated at higher power densities, given improvements to the thermal management and materials.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.010
GPT teacher head0.227
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2023
Admission routes1
Has abstractyes

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