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Record W2014720422 · doi:10.2514/1.1759

Effect of Electromagnetic Forces on the Orbital Dynamics of Tethered Satellites

2005· article· en· W2014720422 on OpenAlexafffund
Eric L.-M. Lanoix, Arun K. Misra, V. J. Modi, George Tyc

Bibliographic record

VenueJournal of Guidance Control and Dynamics · 2005
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsLorentz forcePhysicsSatelliteDragOrbital mechanicsAerodynamic forceOrbit (dynamics)Dynamics (music)Classical mechanicsAerospace engineeringMechanicsElectrical conductorMagnetic fieldAerodynamicsEngineering

Abstract

fetched live from OpenAlex

Tethered satellites have a vast potential for space applications. If the tether is conductive, electrodynamic forces result from the motion of the conductive tether relative to the magnetic field of the Earth. The long-term effect of electrodynamic forces on the equinoctial orbital elements of a tethered system is studied with use of a detailed model of the Earth’s magnetic field as well as of the tether dynamics. A detailed gravity and aerodynamic model is used. In all cases studied, bare tethers induce larger electrodynamic forces than insulated tether systems. The results show that Lorentz forces can remove a satellite from orbit more effectively than air drag if a conductive tether is attached to it. A simple control law is used to stabilize tether librations caused by electrodynamic forces. Such an approach for junk removal is practical if the satellite mass is greater than 100 kg or so.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.189
Teacher spread0.186 · 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 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

Citations56
Published2005
Admission routes2
Has abstractyes

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