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Record W3119953841 · doi:10.1115/gt2020-14116

A Non-Uniformity Factor to Assess Fuel/Air Mixing Quality

2020· article· en· W3119953841 on OpenAlexaff
Lei‐Yong Jiang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsVenturi effectCombustionMixing (physics)Air–fuel ratioMethaneMaterials scienceAir quality indexNuclear engineeringAutomotive engineeringEnvironmental scienceProcess engineeringMechanical engineeringEngineeringInternal combustion engineMeteorologyChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract A practical method to assess quantitatively the uniformity of fuel/air mixing is essential for research and development of advanced low-emission combustion systems. A non-uniformity factor, based on the fuel/air equivalence ratio, is proposed and demonstrated in a simple methane/air venturi mixer. It has two advantages over the unmixedness parameter and uniformity index approaches: it is correlated with the fuel/air mixture combustion property, and the maximum temperature deviation from the designed value caused by fuel/air non-uniformity can be estimated. Because of these, it can be used as a criterion to check fuel/air mixing quality, or as a target for fuel/air mixer design with acceptable maximum temperature deviation.

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)0.002
metaresearch head score (Gemma)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.282
Teacher spread0.232 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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