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Record W2022277908 · doi:10.1504/ijamechs.2008.020836

Modelling rate-dependent symmetric and asymmetric hysteresis loops of smart actuators

2008· article· en· W2022277908 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

VenueInternational Journal of Advanced Mechatronic Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicPiezoelectric Actuators and Control
Canadian institutionsConcordia University
Fundersnot available
KeywordsHysteresisActuatorControl theory (sociology)Displacement (psychology)Prandtl numberPhysicsTopology (electrical circuits)MathematicsComputer scienceMechanicsEngineeringCondensed matter physicsControl (management)Electrical engineeringConvection

Abstract

fetched live from OpenAlex

Smart material actuators invariably exhibit hysteresis that may be either symmetric or asymmetric depending upon the actuation principle. Moreover, the shape of hysteresis loop depends on the rate of change of the input. In this study, a generalised rate-dependent Prandtl-Ishlinskii model is proposed to characterise both the symmetric and asymmetric input-output hysteresis effects of smart material-based actuators. The model is realised upon formulation and integration of a generalised rate-dependent play operator. The validity of the generalised model is demonstrated by comparing its displacement responses with the measured symmetric and asymmetric responses obtained for piezoceramic and magnetostrictive actuators under different input frequencies in the 1?200 Hz and 10?100 Hz ranges, respectively. The results suggest that the proposed rate-dependent Prandtl-Ishlinskii model can effectively characterise the symmetric as well asymmetric hysteresis properties of the smart material actuators over a wide range of input frequencies.

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 score0.532
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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