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Record W1967004520 · doi:10.4271/2011-01-1541

Difficulties Encountered in the Correlation of Vehicle Response to Bench Testing of Driveline Gearboxes for NVH Attributes

2011· article· en· W1967004520 on OpenAlexaff
Steven F. Balistreri, Michael Browne

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2011
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsLinamar (Canada)
Fundersnot available
KeywordsNoise, vibration, and harshnessPowertrainAutomotive engineeringTest benchComputer scienceEngineeringVibrationAcousticsTorqueMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Correlating a bench test stand to predict the response of a driveline gearbox in the vehicle can be very difficult. Many sources of variation and error may prevent correlation. This paper outlines the issues related to both vehicle and bench testing that prevents proper correlation. The importance of understanding both the NVH measurements and statistics are vital to proper interpretation. The identified issues are backed up with real test cases where these issues occurred in a series production gearbox program. A successful correlation case study is presented for comparison.

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)0.011
metaresearch head score (Gemma)0.037
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.026
GPT teacher head0.241
Teacher spread0.215 · 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
Published2011
Admission routes1
Has abstractyes

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