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Record W1823423828

Assessment of acoustic properties of different recycled polymer-based materials for road work sound barrier walls application

2011· article· en· W1823423828 on OpenAlexaffvenue
Julien Biboud, Raymond Panneton, Saïd Elkoun, Rémy Oddo

Bibliographic record

VenueCanadian acoustics · 2011
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsGlass woolMaterials scienceAbsorption (acoustics)Work (physics)Glass recyclingComposite materialSound (geography)CompactionEnvironmentally friendlyPolymerAcousticsEngineeringMechanical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper examines environmentally-friendly alternatives for rock and glass wools in sound barrier walls applications. Around road-work construction sites, the most disturbing frequencies are between 500 and 2,000 Hz. Therefore, the materials should be acoustically efficient within this frequency range, and all measurements should be carried out. More interestingly, those 3 materials seem to be better than rock or glass wool as they exhibit higher absorption coefficients. Only material D appears to be less efficient in spite of its larger thickness. This result can be ascribed to a lack of compaction as it has the lowest density among the 4 selected materials. It was shown that, in terms of sound absorption, the selected recycled fiber-polymers seem to be equal or better than rock or glass wool. Due to this encouraging result, acoustic characterization of the recycled material on an experimental on-scale sound barrier wall and modeling are presently in progress.

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 score0.460
Threshold uncertainty score0.882

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 studies0.0000.000
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 head0.243
Teacher spread0.210 · 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
Published2011
Admission routes2
Has abstractyes

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