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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 OpenAlexaff
Victor E. L. Gasparetto, Mila Kanevsky, Xin Jiang

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

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)0.0040.001

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

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 designBench or experimental
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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAIAA Scitech 2021 ForumSame topicShape Memory Alloy TransformationsFrench-language works237,207