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Record W3184148756 · doi:10.2514/6.2021-3438

Investigation of Droplet Mode Electrospray Emitters for use in Multimodal Systems for Spacecraft

2021· article· en· W3184148756 on OpenAlexaff
Peter Mallalieu, Manish Jugroot

Bibliographic record

VenueAIAA Propulsion and Energy 2021 Forum · 2021
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsSpacecraftElectrosprayAerospace engineeringPropulsionSpecific impulseIon thrusterThrustCommon emitterImpulse (physics)Computer scienceMaterials sciencePhysicsEngineeringIonOptoelectronics

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2021-3438.vid Electrospray thrusters have shown great promise as propulsion devices for micro spacecraft. The thrusters have the ability to operate in either a high thrust droplet mode or high specific impulse ion mode. The multimodal capability of the thruster could be utilized to greatly expand the mission capability and flexibility of micro spacecraft. The physical behaviour of an electrospray cone-jet and droplet formation for various emitter types is simulated using a computational fluid dynamics based solver. These simulations are complemented by estimated emitter performance parameters calculated using the Electrospray Propulsion Engineering Toolkit. Both these tools demonstrated their utility to assist with the development a multimodal electrospray thruster.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.008
GPT teacher head0.203
Teacher spread0.196 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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