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Record W1707179431

A new method of acoustical remote evaluation of defective structures and material characterization

2007· article· en· W1707179431 on OpenAlexaffvenue
Etienne Mfoumou, Claes M. Hedberg, C. Kao-Walter, Sivakumar Narayanswamy

Bibliographic record

VenueCanadian acoustics · 2007
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsConcordia University
Fundersnot available
KeywordsLaser Doppler vibrometerAcousticsNondestructive testingLoudspeakerBroadbandVibrationLaser scanning vibrometryLaserMaterials scienceFrequency responseCharacterization (materials science)OpticsEngineeringLaser power scalingPhysicsElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

The feasibility of a remote monitoring of structures for a progressive damage assessment as well as material characterization using a simple and inexpensive experimental setup is discussed. The method is based on a remote acoustic excitation of transverse vibrations on a membrane using an ordinary broadband low frequency loudspeaker, and the measurement of the response using a Laser Doppler Vibrometer (LDV). Theoretical modeling is also developed to correlate the experimental results obtained, and this yields a new method for Non Destructive Testing (NDT) of sheet-like materials. The function generator provides an input voltage of a sine signal to the loudspeaker, and laser detection of the surface vibrational response of the sample is accomplished with the laser vibrometer.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.258
Teacher spread0.246 · 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
GenreMethods

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
Published2007
Admission routes2
Has abstractyes

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