MétaCan
Menu
Back to cohort

A Systematic Approach to Performance Evaluation of Shape Memory Alloys as Actuator Material

2010· article· en· W2001326873 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

VenueMaterials science forum · 2010
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsActuatorSMA*Shape-memory alloyEnvelope (radar)Materials scienceMorphingStress (linguistics)Mechanical engineeringWork (physics)Mode (computer interface)DiagramFlight envelopeMaterial selectionMaterial propertiesComputer scienceStructural engineeringComposite materialEngineeringArtificial intelligenceAlgorithmAerospace engineering

Abstract

fetched live from OpenAlex

This work presents a combined performance evaluation approach for SMAs as actuator material – an approach based on the combination of three testing modes: a) stress-free thermal recovery mode, b) fixed-support stress generation mode and c) constant (or variable) bias-stress recovery mode. Based on this testing, a so-called “design diagram” can be constructed. This diagram demonstrates the mechanical work generation potential of an SMA and therefore represents a must-have tool for the application engineer. Given that the working envelope depends on the material composition, microstructure and number of actuation cycles, this approach allows the selection of an appropriate material and the processing technique that will meet the functional requirements of a specific application. To illustrate the proposed performance evaluation technique, we show how it can be applied to the design of an SMA actuator for a morphing wing.

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)0.011
metaresearch head score (Gemma)0.001
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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.000
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 head0.022
GPT teacher head0.277
Teacher spread0.255 · 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