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Record W2751861630 · doi:10.15406/jteft.2017.02.00073

Laval Tube Design of Yarn Suction Gun for Fully Drawn Yarn

2017· article· en· W2751861630 on OpenAlexaboutno aff
Yonggui Li, Huizhen Ke, Mohan Zhang

Bibliographic record

VenueJournal of Textile Engineering & Fashion Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Launch and Propulsion Technology
Canadian institutionsnot available
FundersMinjiang University
KeywordsYarnTube (container)SuctionEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

In order to demonstrate the effect of Laval tube structure of yarn suction gun on the yarn suction performance, throat diameter and throat length of the Laval tube were determined by theoretical analysis of the fluid field in the gun. 12 Laval tubes were designed, and yarn suction force (F) and mass flow rate of compressed air (G) were determined. Thereafter, yarn suction efficiency () was analyzed, where =F/G. The rational geometrical parameters were obtained: converging angle of Laval tube =90 and diverging angle of Laval tube =6. The results indicated that there was a benefit to the airflow acceleration in the converging part of Laval tube and the formation of strong swirling flow by choosing the proper , finally resulting in the improvement of . The increase of super-sonic swirling airflow in the diverging section of Laval tube and the decrease of running resistance between the airflow and the yarn could be found when the reasonable was selected, which also improved . However, normal shock wave appeared in advance, the kinetic energy lost and the acceleration of airflow stopped due to the over-large , leading to the decrease of .

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.491
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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 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
Published2017
Admission routes1
Has abstractyes

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