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Record W2554966382 · doi:10.1121/1.4969417

Piezoelectric low frequency shear horizontal guided wave transduction

2016· article· en· W2554966382 on OpenAlexaff
Guillaume Boivin, Nicolas Tremblay, Ricardo J. Zednik, Pierre Bélanger

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2016
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMultiphysicsTransducerGuided wave testingMaterials scienceAcousticsPiezoelectricityOpticsFinite element methodIsotropyDispersion (optics)Physics

Abstract

fetched live from OpenAlex

Ultrasonic guided waves are now routinely used in non-destructive evaluation. In plate-like structures, three fundamental modes can propagate, namely, A0, S0, and SH0. Most of the guided wave literature has thus far focused on the use of A0 and/or S0 because these modes are easy to generate in plate-like structures using standard piezoceramic transducers. Yet, at low frequency, A0 and S0 are dispersive. The consequence of dispersion is that signal processing becomes complex for long propagation distances. SH0, on the other hand, has the particularity of being the only non-dispersive guided wave mode. Omnidirectional transduction of SH0 requires a torsional surface stress which cannot be easily generated using standard piezoceramic transducers. This paper compares a transducer concept based on piezoceramic patches assembled to form a discretized circle and a second concept based on a tellurium dioxide disk. The external diameter of the transducers was chosen to be half the SH0 wavelength at 100 kHz in an aluminium plate. Finite element simulations using the Comsol Multiphysics environment showed that in a 1.6 mm aluminium plate the modal selectivity as well as the omnidirectionality of the tellurium dioxide concept was superior at 100 kHz.

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)0.000
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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