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Record W2463907047

A Comparative Study Between Different Helmholtz Resonator Systems

2016· article· en· W2463907047 on OpenAlexvenueno aff
Md. Amin Mahmud, Md Shahriar Islam, Md. Zahid Hossain, Mir Md. Maruf Morshed

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsnot available
Fundersnot available
KeywordsResonatorAcousticsHelmholtz resonatorAttenuationBandwidth (computing)Transmission lossWavelengthHelical resonatorPhysicsOpticsNode (physics)Computer scienceTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Cet article propose un résonateur d'Helmholtz cylindrique connecté à un conduit pour en atténuer le bruit de basse fréquence et optimisé en utilisant la méthode des éléments finis.Au départ, un système de résonateur à deux degrés de liberté identiques (2-DDL) a été ajusté en termes de position relative et de l'orientation en adaptant une publication existante sur un système de résonateur unique à 2 DDL.La meilleure position relative des deux résonateurs est étudié en les plaçant en deça des ventres et noeuds de la longueur d'onde de la source sonore et de l'orientation relative optimale entre les résonateurs se trouve également à un espacement relatif optimal.Enfin, le système optimisé à deux degrées de libertés de résonateurs identiques a été comparée à trois études publiées d'un unique résonateur à 2 DDL, d'un unique résonateur à 1-DDL et à deux systèmes résonateurs à 1-DDL, et les résultats indiquent que le systèmes à deux résonateurs identiques 2-DDL peut fournir une gamme plus large d'atténuation pour une bande passante de 300 Hz.Les résultats analytiques et numériques de perte de transmission obtenus pour l'adaptation d'un unique système à2-DDL ont été validés avec les résultats expérimentaux publiés et une bonne concordance a été trouvée.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.041
GPT teacher head0.264
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2016
Admission routes1
Has abstractyes

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