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Record W3120068593 · doi:10.2514/6.2021-1608

Solar Panel Deployment Using Shape Memory Alloy Actuator

2021· article· en· W3120068593 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 Scitech 2021 Forum · 2021
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsCarleton University
Fundersnot available
KeywordsActuatorShape-memory alloySMA*Linear actuatorDisplacement (psychology)Computer scienceMechanical engineeringSoftware deploymentResistive touchscreenHingeMaterials scienceStructural engineeringEngineering

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2021-1608.vid In this project, it is intended to apply the design methodologies of Shape Memory Alloys (SMA) acting as a linear actuator in a mechanical system. The object of study is a prototype satellite with a solar panel attached with a rotational hinge. The displacement of the linear actuator results in the deployment of the solar panel within the designed time of actuation. A bias tensile spring acts as the resistive load in order to deploy the panel. A dynamic simulation is performed, intending to characterize the variation of the tensile force of the actuator over time. The methodology of calculation for the SMA design, as well as the numerical results are presented. The design resulted in a selection of a Nitinol wire with 0.15mm diameter to be used as the linear actuator. The control method to deploy the panel is also presented. Finally, an experiment is conducted where the selected wire is implemented and tested successfully.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.040
GPT teacher head0.270
Teacher spread0.230 · 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