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Horizontal Injection of Gas–Liquid Mixtures in a Water Tank

2008· article· en· W2046752883 on OpenAlexaff
Iran Eduardo Lima Neto, David Z. Zhu, N. Rajaratnam

Bibliographic record

VenueJournal of Hydraulic Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPetroleum engineeringEnvironmental scienceMechanicsHydrology (agriculture)Geotechnical engineeringGeologyMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Experiments were carried out to investigate the behavior of horizontal gas–liquid injection in a water tank. Measurements of bubble properties and mean liquid flow structure were obtained. The turbulence in the liquid phase appears to help generating bubbles with relatively uniform diameters of 1–4mm. Both bubble properties and mean liquid flow structure depended on the gas volume fraction and the densimetric Froude number at the nozzle exit. It was found that the bubbles strongly affected the trajectory of the water jet, which behaved similarly to single-phase buoyant jets. However, at gas volume fractions smaller than about 0.15, the water jet completely separated from the bubble core. Bubble slip velocity was also found to be higher than the terminal velocity for isolated bubbles reported in the literature. Dimensionless correlations were proposed to describe bubble characteristics and the trajectory of the bubble plumes and water jets as a function of the gas volume fraction and the densimetric Froude number. Finally, applications of the results for aeration/mixing purposes are presented.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.186
Teacher spread0.180 · 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

Citations48
Published2008
Admission routes1
Has abstractyes

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