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Record W2011856438 · doi:10.1121/1.4783131

Performance comparison of viscoelastic materials typically used for acoustical damping of aircraft fuselage structures.

2008· article· en· W2011856438 on OpenAlexaff
Esen Cintosun, Noureddine Atalla, Tatjana Stecenko, Maxime Bolduc

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsViscoelasticityFuselageShakerMaterials scienceLaser Doppler vibrometerAcousticsLoss factorVibrationOctave (electronics)Damping ratioStructural engineeringComposite materialPhysicsEngineering

Abstract

fetched live from OpenAlex

Vibration tests were performed to compare typical viscoelastic damping materials attached to two distinct representative aircraft fuselage structures. The fuselage structures were a 19×20-in2 Al ribbed panel and a 20×21-in2 carbon composite ribbed panel. A shaker was used to excite each panel with and without viscoelastic material treatment. Each test structure along with the shaker was situated in an environmental chamber to collect measurements at low temperatures of −20, −30, and −40 °C. A laser vibrometer was used to collect velocity measurements at 15–26 random locations on the surface of the panels. The parameters that were compared included input mobility, damping loss factor (DLF), and space averaged squared velocity. The DLF values that were obtained using the decay rate, power input, and half-power bandwidth methods were presented as averages in 1/3 octave frequency bandwidths (from 100 to 2500 Hz). The space and frequency averaged squared velocity was used to quantitatively categorize the viscoelastic damping materials. The effect of viscoelastic damping material coverage was also evaluated by comparing measurements collected at 50% and 80% coverages. The results of this experimental study are being utilized in finite element modeling, optimization of viscoelastic material treatment, and development of alternatives to viscoelastic damping. [Work supported by the MTI Polyfab Inc.]

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.278
Teacher spread0.253 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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