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Record W4249275463 · doi:10.13052/ejcm.20.73-102

Structural multi-modal damping by optimizing shunted piezoelectric transducers

2011· article· en· W4249275463 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

VenueEuropean Journal of Computational Mechanics · 2011
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsSafran Electronics (Canada)
Fundersnot available
KeywordsPiezoelectricityModalTransducerAcousticsVibrationElectronic circuitPMUTModal analysisPiezoelectric sensorVibration controlCoupling (piping)Electronic engineeringStructural engineeringMaterials scienceEngineeringMechanical engineeringElectrical engineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

The capacity of different auto-supplied devices using shunted piezoelectric circuits are studied here to improve structural damping by avoiding implementation of complex and heavy control devices. The presented technique uses a dedicated numerical piezo-mechanical model combining both mechanical and electrical coupling parameters. An original methodology are also introduced for optimizing the parameters of electrical shunt circuits connected to piezoelectric elements and also structural locations of these integrated transducers. The results, experimentally validated (on beams and a plate), demonstrate that vibrations can be significantly reduced when shunted piezoelectric devices are mounted on a real structure. Finally, the proposed methodology is used for optimizing shape and location of the shunted piezoelectric patches to damp several modes of a plate.

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 score0.393
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.037
GPT teacher head0.255
Teacher spread0.217 · 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