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Record W2050024983 · doi:10.1115/fedsm2002-31431

The Measurements of Mean Flow Angles Between an Automotive Fan and Stator

2002· article· en· W2050024983 on OpenAlexafffund
Gregory A. Kopp, Robert J. Martinuzzi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTurbomachinery Performance and Optimization
Canadian institutionsWestern University
FundersCanada Research ChairsOntario Innovation Trust
KeywordsStatorRADIUSLeading edgeTrailing edgeAcousticsFlow (mathematics)MechanicsEnhanced Data Rates for GSM EvolutionOpticsPlane (geometry)PhysicsGeometryEngineeringMathematicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Measurements of the mean velocity vector were conducted to determine the exit angle from an automotive engine cooling fan module. The measurements were made at 15 locations along a radius between the hub and the band. The radius investigated was located in a plane roughly half-way between the blade trailing edge and stator leading edge. A two-component laser Doppler velocimeter and a four-wire hot-wire probe were used to measure the flow fields. It was found that the results obtained from hot-wire anemometry will have significant bias errors when used to measure the velocity vectors between the fan and the stator unless phase-averaged data are obtained with the probe re-oriented by phase. The differences between the techniques occur because the distribution of instantaneous swirl angles is bi-modal. Further, the mean flow angle is close to a local minimum in the probability density function of the swirl angle. This will act to increase errors in measurement devices whose accuracy depends on flow direction (the quantity being measured) such as five-hole probes which are used in industry.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.165

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 head0.029
GPT teacher head0.213
Teacher spread0.184 · 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

Citations4
Published2002
Admission routes2
Has abstractyes

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