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Record W1591146383

Comparison of experimentaland modeled insertion loss of a complex multi-chamber muffler with temperature and flow effects

2004· article· en· W1591146383 on OpenAlexaffvenue
Helen Ule, Colin Novak, Tony Spadafora, Ramani Ramakrishnan, Robert Gaspar

Bibliographic record

VenueCanadian acoustics · 2004
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsToronto Metropolitan UniversityUniversity of Windsor
Fundersnot available
KeywordsMufflerInsertion lossAcousticsExpansion chamberFlow (mathematics)Transmission lossMechanicsMaterials scienceEngineeringPhysicsElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

The insertion loss of an off the shelf multi-chamber muffler was investigated using a computer simulation program known as Ricardo WAVE. The temperature and flow effects of multi-chamber muffler was also included to investigate insertion loss. The realized sound pressure level at the exit of the exhaust pipe was observed with both the muffler and straight pipe in place using a Ricardo WAVE by implementing a one-dimensional finite difference formulation. An insertion loss of up to 20 dB was realized with implementation of the muffler in the experimental exercise with the maximum occuring at the higher engine speeds.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.619

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 head0.022
GPT teacher head0.269
Teacher spread0.247 · 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

Citations0
Published2004
Admission routes2
Has abstractyes

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