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Record W1993835764 · doi:10.1121/1.4743772

Numerical and experimental characterization of the transmission loss of complex composite panels

2000· article· en· W1993835764 on OpenAlexaff
Maxime Bolduc, Raymond Panneton, Noureddine Atalla, Jean-Luc Wojtowicki

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2000
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsTransmission lossAcousticsAnechoic chamberSuperposition principleBiot numberBoundary value problemBoundary element methodSound transmission classFinite element methodComputer simulationMaterials scienceStructural acousticsStructural engineeringMechanicsPhysicsEngineeringVibrationMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

The noise reduction in aircrafts is one of the top priorities for the aerospace industry. In this paper, a thorough investigation is done on the reliability of numerical FEM/BEM methods to predict the sound transmission loss of aircraft-type panels. The investigation is based on the comparison between numerical predictions, using commercial and in-house software, and measurements for different configurations of panels: single plate, double plate with air cavity, and double plate with cavity absorption. Clamped boundary conditions are used for both the simulation and experiments. The porous material is modeled following Biot theory and the diffuse sound field is simulated as a superposition of plane waves at various directions. For the experimental part, the transmission loss is obtained by setting the panel between a reverberant and an anechoic room. The transmitted power is measured with an intensity probe allowing fine characterization of the effects of complexities such as the boundary conditions and leaks. Furthermore, the quadratic velocity is measured as a means of validation for the mode shapes. Discussions on the numerical procedure to follow for providing reliable transmission loss predictions and a discussion on the discrepancies between the experiments and the numerical simulations will be done.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.251
Teacher spread0.237 · 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

Citations2
Published2000
Admission routes1
Has abstractyes

Explore more

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