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Record W7018678190

Effect of nozzle geometry on mixing characteristics of turbulent free orifice jets

2017· dissertation· en· W7018678190 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2017
Typedissertation
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsNucleofectionGestational periodTSG101LiquationDiafiltrationHemopericardium
DOInot available

Abstract

fetched live from OpenAlex

An experimental investigation was conducted using particle image velocimetry to study the effect of nozzle geometry on turbulent free orifice jets. The nozzle geometries studied include the round, cross, flower, star, rectangular and elliptical nozzles (aspect ratio 2). The spread rate of the rectangular nozzle was 61% greater than the square nozzle while the elliptical nozzle was 45% greater than the round nozzle using the conventional half velocity width. The superior mixing capacity of the rectangular and elliptical nozzles is attributed to the axis-switching mechanism. Evaluation of the energy budget showed a higher level of production of turbulence and convection of the mean flow for the rectangular nozzle compared with the round nozzle. Two-point auto-correlation function revealed larger structures in the non-circular nozzles and in particular the rectangular nozzle. The Kolmogorov and Taylor microscales however, did not show any significant dependency on nozzle geometry.

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)0.001
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.197
Teacher spread0.191 · 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
Published2017
Admission routes1
Has abstractyes

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