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Record W3184146453 · doi:10.2514/6.2021-3381

Study on Nozzle Shape of Radio-Frequency Inductively Coupled Plasma Thruster

2021· article· en· W3184146453 on OpenAlexaboutno aff
Kaho Akiyama, Takayasu Fujino

Bibliographic record

VenueAIAA Propulsion and Energy 2021 Forum · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSpecific impulsePropellantThrustMass flow rateNozzleVolumetric flow rateElectrically powered spacecraft propulsionMass flowMechanicsAerospace engineeringImpulse (physics)PlasmaMaterials sciencePropulsionPhysicsEngineeringNuclear physics

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2021-3381.vid Inductively coupled plasma (ICP) thrusters, which are one kind of electrodeless electro-thermal thrusters, utilizes radio-frequency (RF) electric power to heat propellant gas. In this work, thrust measurement experiments of a 0.5 kW class, ICP thruster model with a de Laval nozzle using argon as propellant gas were conducted. To improve the thrust performance of an ICP thruster, increasing the pressure in a reservoir part (plasma generation part) with an RF induction coil, which is located ahead of the de Laval nozzle, would be adequate. In this study, we assigned two approaches to increase the pressure in the reservoir: one is the decrease in nozzle throat cross section, and the other is the increase in propellant mass flow rate. The experimental results indicated that the thrust force of the ICP thruster model tended to be raised by narrowing the nozzle throat cross section. The results also showed that the increase in mass flow rate for the ICP thruster model raised thrust force, while the effect of mass flow rate on specific impulse varied strongly according to small or large mass flow rate cases. In small mass flow rate of about 10 to 80 mg/s, the increase in mass flow rate deteriorated the specific impulse. In contrast, in large mass flow rate of about 80 to 200 mg/s, it had no practical influence on specific impulse.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.222
Teacher spread0.208 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2021
Admission routes1
Has abstractyes

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