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Record W2052471912 · doi:10.1121/1.3249419

Investigation of airborne versus structure-borne insertion loss of acoustic materials attached to a flat panel.

2009· article· en· W2052471912 on OpenAlexaff
Dilal Rhazi, Noureddine Atalla

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2009
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsAcousticsInsertion lossFinite element methodCoupling (piping)ExcitationTransfer-matrix method (optics)Computer scienceStatistical energy analysisMaterials scienceStructural acousticsSimple (philosophy)Energy (signal processing)Structural engineeringPhysicsVibrationComposite materialEngineeringElectrical engineeringOptoelectronics

Abstract

fetched live from OpenAlex

This paper discusses methods to predict airborne and structure-borne insertion loss of acoustic materials (fiber, foams, etc.) in single wall and double wall configurations attached to various structures. Specifically, a transfer matrix method based approach is proposed and compared to finite element and statistical energy analysis based predictions. Based on several numerical and experimental results, it is shown first that this method presents a simple and general model that can handle easily and automatically practical configurations. Next, a systematic comparison of structure-borne versus airborne excitation is presented for various structures and sound packages. In particular, the effect of damping and nature of coupling between the sound package and the main structure is discussed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.267
Teacher spread0.239 · 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
Published2009
Admission routes1
Has abstractyes

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