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Record W2065818713 · doi:10.1177/1045389x07082381

Optimizing the Thickness of Piezoceramic Actuators for Bending Vibration of Planar Structures

2007· article· en· W2065818713 on OpenAlexaff
Olivier Delas, Alain Berry, Patrice Masson, Yann Pasco

Bibliographic record

VenueJournal of Intelligent Material Systems and Structures · 2007
Typearticle
Languageen
FieldEngineering
TopicAeroelasticity and Vibration Control
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsActuatorPlanarMaterials scienceBendingFinite element methodVibrationCoupling (piping)Square (algebra)Substrate (aquarium)Noise (video)Structural engineeringVibration controlAcousticsComposite materialEngineeringGeometryElectrical engineeringComputer science

Abstract

fetched live from OpenAlex

An analytical approach is proposed to optimize the thickness of piezoceramic (PZT) actuators bonded on structures for active shape, noise, or vibration control. The optimal thickness corresponds to maximal mechanical coupling between the PZT actuator and the substrate. The analysis is carried out for a planar geometry, considering a square simply supported flexural plate with a square and a centered PZT actuator bonded either in symmetric or asymmetric configuration. Optimal thicknesses obtained from explicit analytical expressions are compared with finite element (FE) results for various substrate thicknesses and for various values of actuator coverage ratio. Static and dynamic strain profiles through the thickness of the plate—actuator system are plotted. Laboratory experiments are carried out on aluminum and steel plates with free and clamped boundary conditions to verify the analytical and FE predictions in terms of optimal PZT actuator thickness.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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