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Record W4255839125 · doi:10.32920/ryerson.14647989

CubeSat attitude determination

2021· preprint· en· W4255839125 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCubeSatAerospace engineeringSoftware deploymentOrientation (vector space)Mode (computer interface)SatelliteEclipseRemote sensingAttitude controlDragComputer sciencePhysicsEnvironmental scienceGeologyEngineeringAstronomy

Abstract

fetched live from OpenAlex

When satellites are placed in orbit, often times a specific orientation is required to achieve mission purposes. Different factors (such as atmospheric drag, magnetic fields, solar winds) or tumbling upon deployment from the launch vehicle, may result in an undesirable satellite orientation. To address these challenges, the ability to control the orientation, termed as attitude determination, becomes critical to any mission. This thesis will focus on developing an earth-pointing and sun-pointing mode in order to meet the objectives of the ESSENCE CubeSat. The earth-pointing mode orients the vehicle to point towards a desired target on the earth surface, and the sun-pointing mode orients the vehicle such that the maximum solar array surface area is exposed to the sun when the vehicle is out of eclipse.

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.

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: none
Teacher disagreement score0.685
Threshold uncertainty score0.639

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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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