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Record W4293267675 · doi:10.3397/in_2022_0778

Vibrational damping properties of finite microperforated plates

2023· article· en· W4293267675 on OpenAlexaff
Lucie Gallerand, Mathias Legrand, Thomas Dupont, Philippe Leclaire

Bibliographic record

VenueNOISE-CON proceedings · 2023
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiot numberDissipationViscoelasticityMaterials scienceVibrationPerforationMechanicsMagnetic dampingViscous dampingDamping capacityThermoelastic dampingAcousticsThermalComposite materialPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Microperforated plates (MPP) are traditionally used to advantageously absorb acoustic waves in sound control technologies. However, less is known concerning the additional structural damping they can induce. The latter is activated through exchanges in the viscous and thermal boundary layers near the fluid-structure interface of the microperforations. MPPs therefore offer an alternative to, or can be used together with, viscoelastic materials, commonly implemented to damp vibrations at medium and high frequencies. In this work, the structural damping capabilities of MPP are investigated. To this end, the damping performance of a finite size MPP is explored analytically through an alternative form of the Biot model, classically devoted to porous plates, and considering energy dissipation through viscous friction mechanisms. Analytical results are compared to experimental measurements of structural damping factors on various MPP samples. The model is validated and confirms the damping effect added by the microperforations in the low frequency range. A sensitivity analysis on the perforation rate and perforation diameter provides a condition for which additional damping is maximized.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.224
Teacher spread0.191 · 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 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
Published2023
Admission routes1
Has abstractyes

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