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Record W2109843200 · doi:10.2514/6.2011-6272

Spherical Air Bearing Attitude Control Simulator for Nanosatellites

2011· article· en· W2109843200 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

VenueAIAA Modeling and Simulation Technologies Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsYork University
Fundersnot available
KeywordsTestbedAttitude controlBearing (navigation)Aerospace engineeringActuatorSimulationAir bearingCubeSatElectronicsEngineeringComputer scienceSatelliteMechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Spherical Air Bearing systems have been used as a testbed for attitude control systems for many decades. With the advancements of nanosatellite technologies as a platform for scientific missions, there is an increased demand for comprehensive, pre-launch testing of nanosatellites. Several spherical air bearing systems have been developed for larger satellite application and add too much parasitic mass to be applicable for nanosatellite applications. This paper focuses on the design and validation of a Spherical Air Bearing Attitude Control Simulator for Nanosatellites. The simulator consists of the physical design of the system, a complete electronics system, and validation of the simulator using low-cost reaction wheels as actuators. The design of the air bearing platform includes a manual balancing system to align the centre of mass with the centre of rotation. The electronics system is intended to measure the attitude of the platform and control the actuator system. Validation is achieved through a controlled slew maneuver of the air bearing platform.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score0.795

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 head0.051
GPT teacher head0.243
Teacher spread0.192 · 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