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Record W2324980792 · doi:10.2514/6.2012-5294

Dynamics of Deorbiting of Low Earth Orbit Nano-satellites by Bare Electrodynamic Tether

2012· article· en· W2324980792 on OpenAlexafffund
Rui Zhong, Zheng Zhu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAstrobiologyNano-Low earth orbitEarth (classical element)Orbit (dynamics)SatelliteGeocentric orbitPhysicsAerospace engineeringEarth's orbitRemote sensingAstronomySpacecraftGeologyEngineering

Abstract

fetched live from OpenAlex

This paper studies orbital and librational dynamics of deorbiting a nano-satellite by a bare electrodynamic tether. The orbital motion and tether libration are modeled by considering multiple space environmental perturbations including the current-induced electrodynamic force, atmospheric drag, Earth’s oblateness effect, irregularity of Earth’s geomagnetic field, ambient plasma density affected by the variation of geomagnetic and solar condition, solar radiation pressure, and lunisolar gravitational attractions. Approximated analytical and numerical calculation methods of the perturbation torques are provided. Numerical simulations are conducted to study the electrodynamic tether’s orbital and libration motion during deorbiting. The effect of tether libration on the induced voltage is also analyzed. Nomenclature E r a = acceleration of the Earth EDT r a = acceleration of the electrodynamic tethered system a = semi major axis of the orbit A = cross section area of the electrodynamic tether d A = projected area of nano!satellites for atmospheri c drag r

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 score0.177
Threshold uncertainty score0.632

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 head0.002
GPT teacher head0.171
Teacher spread0.169 · 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

Citations3
Published2012
Admission routes2
Has abstractyes

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