MétaCan
Menu
Back to cohort
Record W2173486502 · doi:10.1063/1.1449769

Kinetic modeling of the electron current collection to a moving bare electrodynamic tether

2002· article· en· W2173486502 on OpenAlexfundno aff
Éric Choinière, Brian Gilchrist

Bibliographic record

VenueAIP conference proceedings · 2002
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsElectronPlasmaKinetic energyVlasov equationThrustIonMechanicsLangmuir probePoisson's equationDebye sheathComputational physicsElectron temperatureClassical mechanicsAtomic physicsPlasma diagnosticsQuantum mechanics

Abstract

fetched live from OpenAlex

Tether electron current collection in the Orbital Motion Limited regime is the key mechanism allowing for power and/or thrust generation applications of space electrodynamic tethers. This paper presents a new approach, based on a kinetic model, for the accurate analysis of the electron collection problem to a bare tether moving in a collisionless plasma. The drift velocity associated with the translational speed of the tether is incompatible with 1-D, cylindrically symmetric models (Laframboise, 1966; Sanmartı́n and Estes, 1999) and its effects on current collection are not well understood. A kinetic model is developed for the two-dimensional plasma surrounding the tether. It consists in solving, self-consistently, the Vlasov and Poisson equations through a semi-analytical, semi-numerical process. A Maxwellian velocity distribution is assumed for the plasma species (electrons and ions) at the outer boundary of the solution space; no assumption is made regarding the velocity distributions in the vicinity of the tether. Initial results are validated with Langmuir cylindrical probe theory in the ion and electron saturation regimes as well as the electron retardation regime. Work is underway to allow the use of the model for cases with a drifting plasma.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.588

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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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 designSimulation or modeling
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

Citations2
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAIP conference proceedingsSame topicSpace Satellite Systems and ControlFrench-language works237,207