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Record W2514263203

Understanding sources and sound radiation of a snowmobile track

2016· article· en· W2514263203 on OpenAlexaffvenue
Stéphane Beuvelet, Raymond Panneton, Alain Desrochers, Rémy Oddo

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsTrack (disk drive)Noise (video)AcousticsVibrationSuspension (topology)Sound (geography)RadiationEngineeringComputer sciencePhysicsOpticsMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates snowmobile noise, more specifically the system composed of the track, the suspension and the tunnel. Two series of tests were made to understand the snowmobile track noise. The first used the Plackett and Burman design of experiment in order to identify the most important factors in the sources of vibration. In the second, isolated tests were carried out to evaluate the importance of the sound radiation and dynamics of the track and to understand the role of the snowmobile tunnel in the acoustic response of the system. The first part shows that the most important excitation source is the passage of the studs of the track between  the guide wheels and the ground. This excitation propagates in the suspension on which the tunnel of the snowmobile is attached. The second part shows that the sound radiation and the dynamics of the track are not important issues in the studied system. Depending on the track speed, the system has two preferred ways to generate noise: airborne noise from the suspension itself and structural sound radiation from the tunnel.

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 score0.409
Threshold uncertainty score0.270

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 head0.018
GPT teacher head0.184
Teacher spread0.166 · 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
Published2016
Admission routes2
Has abstractyes

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