MétaCan
Menu
Back to cohort
Record W2352187875

Flow Field of High- speed Mixture in Laval Spray Tube

2006· article· en· W2352187875 on OpenAlex
Yao Ya

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJisuanji fangzhen · 2006
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleAutomotive engineeringMechanicsAirflowPetrol engineTorqueMechanical engineeringEngineeringTube (container)Spray nozzlePhysicsInternal combustion engineThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

Through the finite element simulation analysis for the mixed fuel in the Laval spray tube of the gasoline engine, the results reveal that the airflow velocity rapidly increases after it enters the Laval spray tube. There appear obvious vortices in the in - take pipe and the loop flow in two sides of nozzle. Tracking the particle locus, we find the mix proportion of fuel and air is small, and its mix uniformity is not good. Then we use an air- compensation equipment to improve the mixed standard of fuel and air. Experiments prove that the gasoline engine consumes less fuel, reduces the exhaust emission, but its power and torque increase. The experiment results coincide with theoretical analyses in a great degree. This may provide references for the research of the exhaust emission.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.636

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 head0.006
GPT teacher head0.230
Teacher spread0.225 · 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