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Record W4405775389 · doi:10.1016/j.asr.2024.12.052

On the application of reflectivity control devices in spacecraft attitude control

2024· article· en· W4405775389 on OpenAlexaff
Houman Hakima, Michael C.F. Bazzocchi

Bibliographic record

VenueAdvances in Space Research · 2024
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsYork UniversityBrampton Civic Hospital
Fundersnot available
KeywordsSpacecraftRemote sensingReflectivityEnvironmental scienceControl (management)Attitude controlAstrobiologyAerospace engineeringComputer scienceOpticsPhysicsGeologyEngineering

Abstract

fetched live from OpenAlex

This paper investigates the application of reflectivity control devices in spacecraft attitude control. In reflectivity control devices, in particular, the polymer-dispersed liquid–crystal type, the light transmission properties of the film can be altered from transparent to opaque by adjusting the amount of applied voltage. This technology has previously been applied to residential and commercial buildings and, recently, it has been widely adopted in the automotive industry for purposes such as electrochromic glass roofs. Since spacecraft in orbit receive a continuous flow of photons emitted from the Sun (when in the sunlit portion of their orbits), the momentum transferred from these photons to the spacecraft can be utilized for attitude and orbit control. The focus of this paper is on attitude control through strategically adjusting the transparency of reflectivity-control panels attached to the spacecraft away from its center of mass. In this paper, a conceptual design for a spacecraft equipped with reflectivity-control device panels is presented, and the equations of attitude motion coupled with control torques produced by these devices are derived. Furthermore, a control strategy for detumbling a small satellite, such as a CubeSat, is investigated. To assess the viability of reflectivity-control technology in spacecraft attitude control, a number of case studies are presented. The performance of these devices is discussed in light of the results obtained from the numerical simulations.

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)0.002
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 score0.519
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.360
Teacher spread0.341 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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