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Record W2157735057 · doi:10.2514/6.2012-4584

Hybrid Periodic Differential Element Control Using the Geomagnetic Lorentz Force

2012· article· en· W2157735057 on OpenAlexaff
Ludwik A. Sobiesiak, Christopher J. Damaren

Bibliographic record

VenueAIAA/AAS Astrodynamics Specialist Conference · 2012
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLorentz forceSpacecraftThrustEarth's magnetic fieldPhysicsLorentz transformationPerturbation (astronomy)Control theory (sociology)Aerospace engineeringClassical mechanicsMagnetic fieldComputer scienceEngineeringControl (management)

Abstract

fetched live from OpenAlex

The geomagnetic Lorentz force represents a propellantless means of altering a spacecraft’s orbit. This paper investigates the application of the Lorentz force to the control of spacecraft formations. A spacecraft formation flying system is determined to be not fully controllable with the Lorentz force alone, therefore additional control effort must be provided using thrusters. Several electromagnetic/thruster hybrid controllers are presented in this paper for the purpose of mitigating the effects of the J2 gravity perturbation on spacecraft formation geometry. Continuous thrust and impulsive thrust strategies are considered. It is shown that the majority of the required control effort can be realized with the Lorentz force; however, the ratio of electromagnetic actuation to thruster actuation is dependent on the formation’s orbit inclination.

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)0.000
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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