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Record W1996289501 · doi:10.1121/1.4908239

Experimental investigation of the accuracy of a vibroacoustic model for sandwich-composite panels

2015· article· en· W1996289501 on OpenAlexaff
Raef Chérif, Noureddine Atalla

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2015
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsOrthotropic materialSandwich-structured compositeLoss factorSandwich panelComposite numberMaterials scienceSound transmission classTransmission lossAcousticsStructural engineeringModalWavenumberComposite materialOpticsFinite element methodEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a detailed experimental validation of a general laminate model to predict the vibroacoustic behavior of flat sandwich-composite panels. The accuracy of the model is investigated using a thin and a thick sandwich panel over a large frequency band. Several indicators are compared including the structural wavenumber, modal density, damping loss factor, radiation efficiency, and sound transmission loss. The accuracy of a simpler model based on identifying effective properties of an equivalent orthotropic panel from the General Laminate Model is also discussed. Results show that the vibroacoustic behaviors of flat sandwich-composite panels are accurately estimated using the used model and compare well to the equivalent panel model (for total transmission loss). This experimental investigation is generic and can be used as a benchmark to validate other sandwich models.

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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.661
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.288
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations20
Published2015
Admission routes1
Has abstractyes

Explore more

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