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Record W1564244216

Application of SEA in vehicle sound package design

2000· article· en· W1564244216 on OpenAlexvenueno aff
Hugues Nélisse, Jie Pan, J. Van Buskirk

Bibliographic record

VenueCanadian acoustics · 2000
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsnot available
Fundersnot available
KeywordsStatistical energy analysisChassisSoftware packageComponent (thermodynamics)EngineeringSoftwareNoise (video)Marine engineeringAutomotive engineeringComputer scienceStructural engineeringFinite element method
DOInot available

Abstract

fetched live from OpenAlex

The construction, organization and validation of a trimmed-body vehicle statistical energy analysis (SEA) and component SEA models are discussed. The trimmed-body SEA model was built for a mid-size car using AutoSEA2 software package and contained all major structural components and acoustic spaces. The two load cases of 35 miles per hour chassis roll and 3000 revolutions per minute engine noise were employed for the validation of model. The model was utilized for the evaluation of various design changes on the sound package of the vehicle.

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 score0.308
Threshold uncertainty score0.594

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 head0.009
GPT teacher head0.195
Teacher spread0.186 · 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
Published2000
Admission routes1
Has abstractyes

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