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Record W2045553051 · doi:10.1177/1045389x11401450

Modeling of Shape Memory Alloy Actuators Using Likhachev’s Formulation

2011· article· en· W2045553051 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Intelligent Material Systems and Structures · 2011
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsShape-memory alloyActuatorAirfoilFinite element methodPseudoelasticityMechanical engineeringJoule heatingMaterials scienceStructural engineeringComputer scienceEngineeringComposite materialArtificial intelligence

Abstract

fetched live from OpenAlex

This article presents a simplified version of Likhachev’s micromechanical model and its integration in ANSYS, a commercial finite element software package used to simulate the response of a structure equipped with shape memory alloy wire actuators controlled by direct Joule heating. The original Likhachev’s formulation is adapted to obtain a model that is easy to characterize, numerically efficient, and general in the sense that it can simulate all the shape memory-related features using the same formulation (superelasticity, shape memory effect, stress generation, etc.). The adapted Likhachev’s formulation is coupled to an electro-thermal model to simulate temporal response of actuators heated by an electrical current. An experimental result obtained with a deformable airfoil powered by shape memory actuators is used to validate the proposed electro-thermo-mechanical model.

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 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 score0.151
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.062
GPT teacher head0.272
Teacher spread0.210 · 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